## Perceptron & Dialog Systems 2017

Notes:

In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers.

Wikipedia:

References:

Best Dialog System Classifiers

RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems
C Tao, L Mou, D Zhao, R Yan – arXiv preprint arXiv:1701.03079, 2017 – arxiv.org
… In this paper, we propose RUBER, a Referenced metric and Unreferenced metric Blended Evalua- tion Routine for open-domain dialog systems … Finally, a multi-layer perceptron (MLP) pre- dicts a scalar score as our unreferenced metric sU …

An end-to-end trainable neural network model with belief tracking for task-oriented dialog
B Liu, I Lane – arXiv preprint arXiv:1708.05956, 2017 – arxiv.org
… 2.2. End-to-End Task-Oriented Dialog Models Conventional task-oriented dialog systems typically require a large number of domain-specific rules and handcrafted features … where SlotDistm is a multilayer perceptron (MLP) with softmax activation function over the slot type m ? M …

Hybrid dialog state tracker with asr features
M Vodolán, R Kadlec, J Kleindienst – arXiv preprint arXiv:1702.06336, 2017 – arxiv.org
… Understanding (SLU) out- puts with reference transcriptions, together with annotation on the level of dialog acts and user goals on slot-filling tasks where dialog system tries to … The function G(ft,vi,vj) corrects the generic behavior of F. G is implemented as a multi-layer perceptron …

Integrated learning of dialog strategies and semantic parsing
A Padmakumar, J Thomason, RJ Mooney – … of the 15th Conference of the …, 2017 – aclweb.org
… 5 Dialog System … Perceptron-style updates to parameter values, that minimize the log-likelihood of the training data, are used dur- ing training to weight parses to speed search and give confidence scores in parse hypotheses (Zettle- moyer and Collins, 2005) …

A “small-data”-driven approach to dialogue systems for natural language human computer interaction
T Boros, SD Dumitrescu – Speech Technology and Human …, 2017 – ieeexplore.ieee.org
… A scenario is the equivalent of a frame in a in frame-based dialogue system, but by default we don’t log any previous dialogue … We obtained a similar behavior when we used a linear classifier (a single layer perceptron), in which case function words such as “pe” (en …

Out-of-Domain Detection Method Based on Sentence Distance for Dialogue Systems
KJ Oh, DK Lee, C Park, HJ Choi, YS Jeong, S Hong… – ant.sch.ac.kr
… The domain feature is used as the basic feature for a dialogue system responding to a user to identify generated answers or existing examples … An fully connected multi-layer perceptron(FC- MLP) is an easy to configure classifier that has a hierarchical structure similar to the …

A Survey on Dialogue Systems: Recent Advances and New Frontiers
H Chen, X Liu, D Yin, J Tang – arXiv preprint arXiv:1711.01731, 2017 – arxiv.org
… eij = g(st?1, hj), where g is a multilayer perceptron … 3.1.2 Dialogue Context The ability to take into account previous utterances is key to building dialog systems that can keep conversations active and engaging. [67] addressed the challenge of the context Page 5 …

A Multimodal Dialog System for Language Assessment: Current State and Future Directions
D Suendermann?Oeft… – ETS Research …, 2017 – Wiley Online Library
… Multimodal Dialog System for Language Assessment … framework also jointly optimizes the module for feature engineering and the module for scoring using a hybrid model of a bidirectional long short-memory recurrent neural network (BLSTM) and a multilayer perceptron (MLP) …

Dependency Parsing and Dialogue Systems: an investigation of dependency parsing for commercial application
A Adams – 2017 – diva-portal.org
… In particular, we discuss potential areas of application of dependency-based syntactic information in dialogue systems. 7 Page 8. 2 Background 2.1 Dependency syntax … 2. Tuning the neural network. 3. Adding a structured perceptron with beam search to the training procedure …

Speech recognition in a dialog system: from conventional to deep processing
A Becerra, JI de la Rosa, E González – Multimedia Tools and Applications, 2017 – Springer
Multimed Tools Appl DOI 10.1007/s11042-017-5160-5 Speech recognition in a dialog system: from conventional to deep processing … Keywords Speech recognition · Neural networks · Gaussian mixture models · Hidden Markov models · Deep learning · Spoken dialog system …

Novel Methods for Natural Language Generation in Spoken Dialogue Systems
O Dušek – 2017 – dspace.cuni.cz
… This thesis explores novel approaches to natural language generation (NLG) in spoken dialogue systems (ie, generating system responses to be presented the … in all of them: First, our gen- erators, which are based on statistical methods (A* search with perceptron ranking and …

A practical approach to dialogue response generation in closed domains
Y Lu, P Keung, S Zhang, J Sun, V Bhardwaj – arXiv preprint arXiv …, 2017 – arxiv.org
… In dialogue systems, Vinyals et al [1] and Serban et al [2] demonstrated that encoder-decoder networks with LSTM units can generate … The embeddings are then concatenated and passed to a multi-layer perceptron (MLP) which outputs the probability that the question and …

Dialogue Breakdown Detection Considering Annotation Biases
J Takayama, E Nomoto, Y Arase – workshop.colips.org
… As chat-oriented dialogue systems, which are known as chat- bots, implemented by generation-based and example-based ap- proaches gain … Then the three-layered perceptron receives the concatenated vector comprised of the outputs of two encoders and outputs …

Learning Robust Dialog Policies in Noisy Environments
M Fazel-Zarandi, SW Li, J Cao, J Casale… – arXiv preprint arXiv …, 2017 – arxiv.org
… the bot doesn’t answer correctly), logical progression of the dialog, specific goals that humans have regardless of the dialog system’s response, and … For the deep RL experiments we used DQN and Dueling DDQN [33], with a fully-connected Multi-Layer Perceptron (MLP) to …

Learning Dynamic Memory Network with Two Views
CU Shin, JW Cha – workshop.colips.org
… The POMDP-based dialog system consists of a language understanding model for analyzing input utterances … is a simple multi-layer perceptron takes above feature vector and has one output node. If there is no previous memory, we use instead of …

Interaction Quality Estimation Using Long Short-Term Memories
N Rach, W Minker, S Ultes – Proceedings of the 18th Annual SIGdial …, 2017 – aclweb.org
… The increasing complexity of Spoken Dialogue Systems (SDS) and the requirements that come with this progress made automatized recognition and modeling of user … is thus built of a LSTM unit, consisting of two stacked LSTM cells, followed by a two-layer perceptron unit with …

FRB-Dialog: A Toolkit for Automatic Learning of Fuzzy-Rule Based (FRB) Dialog Managers
D Griol, AS de Miguel, JM Molina – International Conference on Hybrid …, 2017 – Springer
… Our proposal is focused on slot-filling dialog systems, for which dialog managers use a structure comprised of one slot per piece of … In this work, we have used three approaches for the definition of the classification function: a multilayer perceptron (MLP), a multinomial naive …

Feature Inference Based on Label Propagation on Wikidata Graph for DST
Y Murase, K Yoshino, M Mizukami, S Nakamura – woolon.org
… Multi-layer perceptron is adopted as machine learning model of the dialog state tracker, which predicts user intentions … Knowledge graph has been widely used as resources for spoken dialog systems [9, 1], especially on Bayesian update of dialog state [4, 2, 7]. These works …

Topic Aware Neural Response Generation.
C Xing, W Wu, Y Wu, J Liu, Y Huang, M Zhou, WY Ma – AAAI, 2017 – aaai.org
… Although previous research fo- cused on dialog systems, recently, with the large amount of conversation data available on the Internet, chatbots are be- coming a major focus of both … ? is usually implemented as a multi-layer perceptron (MLP) with tanh as an activation function …

Could Emotions Be Beneficial for Interaction Quality Modelling in Human-Human Conversations?
A Spirina, W Minker, M Sidorov – International Conference on Text …, 2017 – Springer
… different metrics which are used in call centres or Spoken Dialogue Systems (SDSs) as … 4, 26] trained by Sequential Minimal Optimization (SVM) [13], Multilayer Perceptron [16] (MLP … Rosenblatt, F.: Principles of Neurodynamics Perceptrons and the Theory of Brain Mechanisms …

Using Context Information for Dialog Act Classification in DNN Framework
Y Liu, K Han, Z Tan, Y Lei – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
… man conversations, as well as for developing intel- ligent human-to-computer dialog systems (either written or spoken dialogs) … which is then used as the input in a multi-layer perceptron (MLP) or feedforward neural network for sentence classification …

Towards Implicit Content-Introducing for Generative Short-Text Conversation Systems
L Yao, Y Zhang, Y Feng, D Zhao, R Yan – Proceedings of the 2017 …, 2017 – aclweb.org
… For- mally, Ci is defined as Ci = ?T j=1 ?ijhj, where ?ij is given by: ?ij = exp(eij) ?T k=1 exp(eik) ;eij = ?(si?1,hj) (4) where ? is usually implemented as a multi-layer perceptron (MLP) with tanh as an activation func- tion. 2191 Page 3. ( ) … … … Online process …

RUCIR at the NTCIR-13 STC-2 Task
Y Zhu, X Wang, X Zuo, S Lu, Z Ma, X Zhang, Z Dou – research.nii.ac.jp
… Common retrieval-based dialog systems work in a 1To make it clearly, we use STC-1 to denote the STC task in NTCIR-12 and STC-2 for NTCIR-13 … ? is usually implemented as a multi-layer perceptron (MLP) with tanh as the activation function …

Article/Book Information
???? – t2r2.star.titech.ac.jp
… The SLU system was integrated in our spoken dialogue system, namely Thai Interactive Hotel Reservation Agent (TIRA) … word and utterance level confidence scoring in a speech understanding system [3]. More complicated techniques such as multi-layer perceptron [4], support …

Analysis of Overlapping Speech and Emotions for Interaction Quality Estimation
A Spirina, O Vaskovskaia, M Sidorov – International Conference on …, 2017 – Springer
… Vector Machines [20, 21] trained by Sequential Minimal Optimization (SVM) [22], Multilayer Perceptron [23] (MLP … In: Natural Language Dialog Systems and Intelligent Assistants, pp … Rosenblatt, F.: Principles of Neurodynamics Perceptrons and the Theory of Brain Mechanisms …

Hierarchical RNN with Static Sentence-Level Attention for Text-Based Speaker Change Detection
Z Meng, L Mou, Z Jin – Proceedings of the 2017 ACM on Conference on …, 2017 – dl.acm.org
… [5], for ex- ample, train sequence-to-sequence neural networks to automati- cally generate replies in an open-domain dialog system … But vanilla RNNs with perceptron-like hidden states suffer from the problem of vanishing or exploding gradients, being less effective to model …

Unsupervised text classification for natural language interactive narratives
J Bellassai, AS Gordon… – Proceedings of the …, 2017 – pdfs.semanticscholar.org
… in interactive narratives has his- torically shared many of the methods and technologies of research in natural language dialogue systems … Averaged Perceptron For our supervised algorithms, we used the Averaged Perceptron machine learning algorithm trained on unigram …

Shadowing synthesized speech–segmental analysis of phonetic convergence
I Gessinger, E Raveh, S Le Maguer… – Proc. Interspeech …, 2017 – coli.uni-saarland.de
… As spoken dialogue systems are being developed with the goal to eventually emulate natural dialogue situations, the implementation of convergence … showed fewer ar- tifacts in the rendered signal and was therefore applied using a multi-layer perceptron (MLP) architecture …

Probabilistic record type lattices for incremental reference processing
J Hough, M Purver – Modern perspectives in type-theoretical semantics, 2017 – Springer
… Dobnik et al. 2013), demonstrating its potential for situated, embodied and multi-modal dialogue systems. The possibility of integration of perceptron learning (Larsson 2011) and Naive Bayes learning (Cooper et al. 2014) into …

Neural Network Configurations Analysis for Recognition System of Pattern of Speech Signal based on Low Order DCT Parameters
P Lima, A Barros, W Silva – researchgate.net
… Thus, the Multilayer Perceptron and Learning Vector Quantization networks have the performance evaluated du- ring training, validation and testing in speech signal recognition, whose pattern of speech signal is given by a two-dimensional time matrix, resulted of the encoding …

Emergence of language with multi-agent games: learning to communicate with sequences of symbols
S Havrylov, I Titov – Advances in Neural Information Processing …, 2017 – papers.nips.cc
… (2017), we consider learning the inverse-temperature with a multilayer perceptron: 1 ?(hs i ) = log(1 + exp(wT ? hs i )) + ?0, (4) … Learning dialogue systems for collaborative activities between machine and human were previously considered by Lemon et al. (2002) …

Action-based grammar
R Kempson, R Cann, E Gregoromichelaki… – Theoretical …, 2017 – degruyter.com

Utterance Retrieval based on Recurrent Surface Text Patterns
GD Duplessis, F Charras, V Letard, AL Ligozat… – … on Information Retrieval, 2017 – Springer
… The main goal is to provide a dialogue system with the ability to appropriately react to a large variety of unexpected out-of-domain human … TF-IDF) retrieval models [3, 5]. This has also been framed as a multi-class classification problem, eg, resolved with a perceptron model [5 …

A Chatbot by Combining Finite State Machine, Information Retrieval, and Bot-Initiative Strategy
S Yi, K Jung – sanghyunyi.ml
… In fact, it is impossible to keep all the conversation to be machine-initiative in general purpose dialogue system. However … RM. But in RMMLP, we used multi-layer perceptron(MLP) as a classifiesr instead of the SVM classifiers …

Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System
R Yan, D Zhao – Proceedings of the 40th International ACM SIGIR …, 2017 – dl.acm.org
… ??? Figure 2: Dual-LSTM Chain Model with the first LSTM chain to characterize query-response and the second LSTM chain to characterize response-suggestion. The two LSTM chains are coupled by an external memory states and a multi-layer perceptron (MLP) …

Hierarchical Recurrent Attention Network for Response Generation
C Xing, W Wu, Y Wu, M Zhou, Y Huang… – arXiv preprint arXiv …, 2017 – arxiv.org
… Recently, multi- turn response generation has drawn attention from academia. For example, Sordoni et al. (2015) proposed DCGM where context information is en- coded with a multi-layer perceptron (MLP). Ser- ban et al. (2016a …

Incorporating loose-structured knowledge into conversation modeling via recall-gate LSTM
Z Xu, B Liu, B Wang, C Sun… – Neural Networks (IJCNN) …, 2017 – ieeexplore.ieee.org
… methods as the baselines. MLP: For our task, Multi-Layer Perceptron (MLP) is de- signed to take the concatenated vector of both contexts and candidate responses as the input, and outputs the probability of candidates. LSTM: is an …

Predicting Users’ Negative Feedbacks in Multi-Turn Human-Computer Dialogues
X Wang, J Wang, Y Liu, X Wang, Z Wang… – Proceedings of the Eighth …, 2017 – aclweb.org
… User experience is essential for human- computer dialogue systems … work, where the representations of the query and the response are learned with two CNNs respectively and the concatenation of the representations is used as input of a multi-layer perceptron (MLP) classifier …

Quotation in dialogue
E Gregoromichelaki – The semantics and pragmatics of quotation, 2017 – Springer
Quotation is ubiquitous in natural language (NL). Recent grammars that take a dialogical view on the formal and semantic properties of NLs (Ginzburg, The interactive stance: meaning for conversation.

Compositional Sentence Representation from Character within Large Context Text
G Kim, H Lee, B Kim, S Lee – International Conference on Neural …, 2017 – Springer
… character model (CC), the compositional word model (CW), the compositional sentence model (CS), and the multi layer perceptron (MLP) … Serban, IV, Sordoni, A., Bengio, Y., Courville, A., Pineau, J.: Building end-to-end dialogue systems using generative hierarchical neural …

Referenceless Quality Estimation for Natural Language Generation
O Dušek, J Novikova, V Rieser – arXiv preprint arXiv:1708.01759, 2017 – arxiv.org
… imitation learning, • RNNLG (Wen et al., 2015), a RNN-based system, • TGen (Dušek & Jurc?cek, 2015), a system using perceptron-guided incremental … However, our work is also related to QE research in other areas, such as MT (Specia et al., 2010), dialogue systems (Lowe et …

e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations
C Rosenbaum, T Gao, T Klinger – arXiv preprint arXiv:1708.01776, 2017 – arxiv.org
… As shown in Figure 2, our network architecture extends the End-to-End Memory architecture of (Sukhbaatar et al., 2015), adding a two layer Multi-Layer Perceptron to a concatenation of all “hops” of the … Evaluating prerequisite qualities for learning end-to-end dialog systems …

Label-dependency coding in Simple Recurrent Networks for Spoken Language Understanding
M Dinarelli, V Vukotic, C Raymond – Interspeech, 2017 – hal.inria.fr
… MEDIA The research project MEDIA [13] evaluates different SLU mod- els of spoken dialogue systems dedicated to provide tourist in … We will compare our eJordan model against several competitor architectures: • the basic Multi-Layer Perceptron (MLP) with softmax output layer …

Deep Text Generation–Using Hierarchical Decomposition to Mitigate the Effect of Rare Data Points
N Dethlefs, A Turner – International Conference on Language, Data and …, 2017 – Springer
… A neural network, such as a multi-layer perceptron, learns a hidden representation $$\mathbf {h}$$ of an input sequence \(\mathbf {x … M., Mrkši?, N., Su, PH, Vandyke, D., Young, S.: Semantically conditioned LSTM-based natural language generation for spoken dialogue systems …

Spanish Sign Language Recognition with Different Topology Hidden Markov Models
CD Mart?nez-Hinarejos… – Proc. Interspeech …, 2017 – pdfs.semanticscholar.org
… last decades to provide solutions for many language related prob- lems, such as speech recognition [1], machine translation [2], dialogue systems [3], or … This is the case of [5], where video capture and Multilayer Perceptron (MLP) neural networks are used to recognise 23 static …

Using an Automated Content Scoring System for Spoken CALL Responses: The ETS submission for the Spoken CALL Challenge
K Evanini, M Mulholland, E Tsuprun, Y Qian – regulus.unige.ch
… Recent improvements in automatic speech recognition (ASR), natural language processing (NLP), and spoken dialog system (SDS) infrastructure have enabled the creation of … [13] Y. Zhang and S. Clark, “Syntactic processing using the gener- alized perceptron and beam search …

Non-Contextual Modeling of Sarcasm using a Neural Network Benchmark
ND Radpour, V Ashokkumar – arXiv preprint arXiv:1711.07404, 2017 – arxiv.org
… method that we present to capture different forms of nuances in communication and making for much more natural and engaging dialogue systems … which is, cumulatively compiled and aggregated as values to be fed into a two layer feed forward multi perceptron network to …

Piecewise latent variables for neural variational text processing
IV Serban, AG Ororbia, J Pineau… – Proceedings of the 2017 …, 2017 – aclweb.org
… multi-modal distributions — such as the distribu- tion over topics in a text corpus, or natural lan- guage responses in a dialogue system — the uni … Therefore, each model uses a bag-of-words encoder, defined as a multi-layer perceptron (MLP) Enc(c = ?,x) = Enc(x). Based on …

Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots
Y Wu, W Wu, C Xing, M Zhou, Z Li – … of the 55th Annual Meeting of the …, 2017 – aclweb.org
Page 1. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 496–505 Vancouver, Canada, July 30 – August 4, 2017. c 2017 Association for Computational Linguistics https://doi.org/10.18653/v1/P17-1046 …

Combining speech-based and linguistic classifiers to recognize emotion in user spoken utterances
D Griol, JM Molina, Z Callejas – Neurocomputing, 2017 – Elsevier
… Although emotion is receiving increasing attention from the dialog systems community, most research described in the literature is devoted … Once we have obtained the normalized features, we classify the corresponding utterance with a multilayer perceptron (MLP) into two …

Deep reinforcement learning: An overview
Y Li – arXiv preprint arXiv:1701.07274, 2017 – arxiv.org
… A feedforward deep neural network or multilayer perceptron (MLP) is to map a set of input values to … For example, we can combine spoken dialogue systems, machine translation and text sequence prediction as a single … (2014) modelled G and D with multilayer perceptrons: G(z …

Identifying and avoiding confusion in dialogue with people with alzheimer’s disease
H Chinaei, LC Currie, A Danks, H Lin, T Mehta… – Computational …, 2017 – MIT Press
… interaction. Given that 33% of conversations with people with middle-stage AD involve a breakdown in communication, it is vital that automated dialogue systems be able to identify those breakdowns and, if possible, avoid them …

Affect-lm: A neural language model for customizable affective text generation
S Ghosh, M Chollet, E Laksana, LP Morency… – arXiv preprint arXiv …, 2017 – arxiv.org
… verbal communication is of great importance to understanding spoken language sys- tems, particularly for emerging applications such as dialogue systems and conversational … The affect category et-1 is processed by a multi-layer perceptron with a sin- gle hidden layer of 100 …

Active Learning for Visual Question Answering: An Empirical Study
X Lin, D Parikh – arXiv preprint arXiv:1711.01732, 2017 – arxiv.org
… Deep VQA models may combine Multi-Layer Perceptrons (MLPs), Convolutional Neural Nets (CNNs), Recurrent Neural Nets (RNNs) and even attention … into a feature vector by learning a Long Short Term Memory (LSTM) RNN, and then learns a multi-layer perceptron on top …

Literature Survey
R Chakraborty, M Pandharipande… – Analyzing Emotion in …, 2017 – Springer
… In [106], authors presented results with popular classifiers (support vectormachines (SVMs), multilayer perceptron (MLP) networks, k-nearest neighbor (k … speech and speech acquired through WoZ scenario, where users believe that they are in conversation with dialogue system …

Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering
S Yoon, J Shin, K Jung – arXiv preprint arXiv:1710.03430, 2017 – arxiv.org
… Note that the input sequence of the LTC could be any type of neural network based encoding function x = fenc ? (w) such as RNN, CNN and multilayer perceptron model (MLP). In addition, if the dimension size of x is dif- Page 4 …

Parsing natural language conversations using contextual cues
S Srivastava, A Azaria, T Mitchell – Proceedings of the 26th …, 2017 – azariaa.com
… On the other hand, a notable application area that has ex- plored conversational context within highly specific settings is state tracking in dialog systems … Learning: The model parameters w can be trained via the la- tent variable Structured Perceptron algorithm [Collins, 2002; …

Improvements in IITG Assamese Spoken Query System: Background Noise Suppression and Alternate Acoustic Modeling
S Shahnawazuddin, D Thotappa, A Dey… – Journal of Signal …, 2017 – Springer
… On the other hand, DNN employs multiple hidden layers in a multi-layer perceptron (MLP) to capture the nonlinearities of the training speech … In Proc. Interspeech.Google Scholar. 4. Glass, JR (1999). Challanges for spoken dialogue systems. In Proc …

Robust stress classifier using adaptive neuro-fuzzy classifier-linguistic hedges
AA Mand, JSJ Wen, MS Sayeed… – … and Sciences (ICORAS) …, 2017 – ieeexplore.ieee.org
… The primary classification method used in this research in Adaptive Neuro-Fuzzy Classifier using Linguistic Hedges (ANFC-LH) which will be compared to Multilayer Perceptron (MLP), Linear Discriminant Analysis (LDA), and k-Nearest … Affective Dialogue Systems, i, 36–48 …

Style Transfer in Text: Exploration and Evaluation
Z Fu, X Tan, N Peng, D Zhao, R Yan – arXiv preprint arXiv:1711.06861, 2017 – arxiv.org
… Sequence to sequence (seq2seq) neural network models (Sutskever, Vinyals, and Le 2014) have demonstrated great success in many generation tasks, such as machine transla- tion, dialog system and image … Multi-layer Perceptron (MLP) and Softmax constitute the classifier …

Automated Speech Recognition System–A Literature Review
M Manjutha, J Gracy, P Subashini… – COMPUTATIONAL … – researchgate.net
… Some of the major growing applications are Language Identification, Speech Enhancement, Spoken Dialog System, Speaker Recognition and Verification … rate 12kHz Digitized with 14bit A/D converter 288 digits used for segmentation Analog Perceptron Learning Algorithm …

EEG: Knowledge Base for Event Evolutionary Principles and Patterns
Z Li, S Zhao, X Ding, T Liu – Chinese National Conference on Social Media …, 2017 – Springer
… events are of great value and important for many tasks, such as event prediction, decision-making and scenario design of dialog system … are used for these classification tasks, which are naive bayes classifier (NB), logistic regression (LR), multiple layer perceptron (MLP) and …

Deep Speech Recognition
L Deng – microsoft.com
… learning algorithm for adjusting the weights. – But perceptrons are fundamentally limited in what they can learn to do. non-adaptive hand-coded features output units eg class labels input units eg pixels Sketch of a typical perceptron from the 1960’s Bomb Toy (Slide from Hinton) …

A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media.
H He, X Sun – AAAI, 2017 – aaai.org
Page 1. A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media Hangfeng He, Xu Sun MOE Key Laboratory of Computational Linguistics, Peking University School of Electronics …

Can Discourse Relations be Identified Incrementally?
F Yung, H Noji, Y Matsumoto – Proceedings of the Eighth International …, 2017 – aclweb.org
… On top of generating more natural and timely response in dialogue systems and im- proving language modeling in speech recognition, 157 Page 2 … Ldc2002t07: Rst discourse treebank. Michael Collins and Brian Roark. 2004. Incremen- tal parsing with the perceptron algorithm …

A Voice and Pointing Gesture Interaction System for Supporting Human Spontaneous Decisions in Autonomous Cars
P Sauras-Perez – 2017 – search.proquest.com
… A method for target point estimation from a pointing gesture by means of a lowcost. monocular camera mounted on a mobile robot and a multilayer perceptron neural … importance of designing proper feedback dialog systems to provide a natural humanmachine …

Mention recommendation for twitter with end-to-end memory network
H Huang, Q Zhang, X Huang – Proceedings of the 26th International …, 2017 – static.ijcai.org
… 2.4 Final Prediction Based on the representation obtained from the above process, we introduce a multi-layer perceptron(MLP) and a … Recently, variants of memory networks have also been studied and applied on various tasks, such as dialog systems [Dodge et al., 2015 …

Speech emotion recognition with skew-robust neural networks
PY Shih, CP Chen, HM Wang – Acoustics, Speech and Signal …, 2017 – ieeexplore.ieee.org
… For examples of applications, SER can be incorporated in automatic speech recognition sys- tems or spoken dialogue systems to improve recognition ac- curacy or user experience … NN: A multi-layer perceptron with a hidden layer …

Deep learning based recommender system: A survey and new perspectives
S Zhang, L Yao, A Sun – arXiv preprint arXiv:1707.07435, 2017 – arxiv.org
… Multilayer Perceptron (MLP), MLP is a feedforward neural network with multiple (one or more) layers (hidden layers) between input and output layer. e perceptron can employ arbitrary activation function and does not necessarily represent strictly binary classi er …

Recent trends in deep learning based natural language processing
T Young, D Hazarika, S Poria, E Cambria – arXiv preprint arXiv …, 2017 – arxiv.org
… White, 2014). NLP enables computers to perform a wide range of natural language related tasks at all levels, ranging from parsing and part-of-speech (POS) tagging, to machine translation and dialog systems. Deep learning …

Repetition detection in dysarthric speech
G Diwakar, V Karjigi – Wireless Communications, Signal …, 2017 – ieeexplore.ieee.org
… Perceptron logic was employed to decide the word repetition … To detect repetition in spoken dialogue systems, a neural network based phoneme recognizer was proposed in [5]. Repetition detection involved two phases, in the first phase a phoneme posterior vectors were …

Natural text to abstract concept mapping for collaborative HRI
U Kara – ipvs.informatik.uni-stuttgart.de
… 25 4.4 Dialogue system … It must understand the meaning of a natural language command, that can be mapped to an abstract subtask. The dialogue system, that is used to resolve any ambiguity, should be able to ask for specific details of the concept, if information is missing …

Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms
NURF FAUZI, ASM JAYA, MI JARRAH, H AKBAR… – Journal of Theoretical …, 2017 – jatit.org
… 2017 — Vol. 95. No. 24 — 2017. Full Text. Title: ONLINE PERFORMANCE DIALOGUE SYSTEM MODEL (e-DP): A REQUIREMENT ANALYSIS STUDY AT BATU PAHAT DISTRICT EDUCATION OFFICE. Author: ASRAR NAJIB …

Learning to attend, copy, and generate for session-based query suggestion
M Dehghani, S Rothe, E Alfonseca, P Fleury – arXiv preprint arXiv …, 2017 – arxiv.org
… sequence: lt,i =?(st?1,hi ) (1) at,i = exp(lt,i ) n j exp(lt,j ) (2) where ? is a mapping (usually a multilayer perceptron (MLP) or a bilinear function),st?1 is the previous decoder’s hidden state. is mapping will give us the logitsl which …

Denoised Bottleneck Features From Deep Autoencoders for Telephone Conversation Analysis
K Janod, M Morchid, R Dufour… – … /ACM Transactions on …, 2017 – ieeexplore.ieee.org
… A bag of these products is the input feature set. The input is then processed by a stack of autoencoders and a DAE to obtain robust latent features sets to be used for hypothesizing conversation themes with a multi-layer perceptron (MLP) clas- sifier …

Deconvolutional paragraph representation learning
Y Zhang, D Shen, G Wang, Z Gan… – Advances in Neural …, 2017 – papers.nips.cc
… a required first step toward more applied tasks, such as sentiment analysis [1, 2, 3, 4], machine translation [5, 6, 7], dialogue systems [8, 9 … The classifier function, f(·), that attempts to reconstruct yd from hd can be either a Multi-Layer Perceptron (MLP) in classification tasks, or a …

An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image Classification
AF Agarap – arXiv preprint arXiv:1712.03541, 2017 – arxiv.org
… The distinction of CNN from a “plain” multilayer perceptron (MLP) network is its usage of convolutional layers, pooling, and non-linearities such as tanh, si?moid, and ReLU … 2015. Semantically conditioned lstm-based natural language generation for spoken dialogue systems …

Steering output style and topic in neural response generation
D Wang, N Jojic, C Brockett, E Nyberg – arXiv preprint arXiv:1709.03010, 2017 – arxiv.org
… The sample selector, which is a multilayer perceptron in our experiments, takes the following features: 1) the log-probability of current sample word in p(wt|S); 2) the entropy of current predicted word distribution, ? wt P(wt|S) log P(wt|S) for all wt in the vo- cabulary; 3) the log …

Quotation in Dialogue Eleni Gregoromichelaki King’s College London and Osnabrück University elenigregor@ gmail. com 0049 015171228 646
E Gregoromichelaki – kcl.ac.uk
Page 1. 1 Quotation in Dialogue Eleni Gregoromichelaki King’s College London and Osnabrück University elenigregor@gmail.com 0049 015171228 646 Abstract Quotation is ubiquitous in natural language (NL). Recent grammars that take a …

Natural language understanding and communication for human-robot collaboration
MI Bloch – ipvs.informatik.uni-stuttgart.de
… semantic parsing. Considering autonomously working robots with planning abilities, a dialog system makes these robots to co-workers instead of subordinates, as a dialog system enables these robots to suggest tasks. [Tho …

Transition-Based Deep Input Linearization
R Puduppully, Y Zhang, M Shrivastava – … of the 15th Conference of the …, 2017 – aclweb.org
… eraged perceptron classifier (Collins, 2002) to pre- dict function words, which is consistent with the joint model. 3.2 Linearization … Given a set of labeled training examples, the averaged perceptron with early update (Collins and Roark, 2004) is used …

Automatic Neural Question Generation using Community-based Question Answering Systems
T Baghaee – 2017 – uleth.ca
… That is the reason behind the word deep in this method’s name. The deep feedforward network or multi-layer perceptron (MLP) is a typical example of a deep learning model. MLP is a mathematical function that maps some input values to …

AppTechMiner: Mining Applications and Techniques from Scientific Articles
S Agarwal, M Singh, S Dan, P Goyal… – arXiv preprint arXiv …, 2017 – arxiv.org
… nition, Word Alignment, Conditional Random Fields, Maximum Entropy, Coreference Resolution, Machine Learning, Dialogue Systems, Textual Entailment … Moses Toolkit, Word Sense Disambiguation, Maximum Entropy, IBM Model, Bleu Score, Perceptron Algorithm, Word …

Detection of Sarcasm in Text Data using Deep Convolutional Neural Networks
P Mehndiratta, S Sachdeva, D Soni – Scalable Computing: Practice and …, 2017 – scpe.org
… [18] wrote that recognition of sarcasm can benefit multiple communities working in various areas of natural language processing like a summarization of reviews, ranking systems, and dialog systems … The model is less complex than a simple multilayer perceptron architecture …

Learning to A end, Copy, and Generate for Session-Based ery Suggestion
M Dehghani, S Rothe, E Alfonseca, P Fleury – 2017 – pdfs.semanticscholar.org
… sequence: lt,i =?(st?1,hi ) (1) at,i = exp(lt,i ) n j exp(lt,j ) (2) where ? is a mapping (usually a multilayer perceptron (MLP) or a bilinear function),st?1 is the previous decoder’s hidden state. is mapping will give us the logitsl which …

Improving the understanding of spoken referring expressions through syntactic-semantic and contextual-phonetic error-correction
I Zukerman, A Partovi – Computer Speech & Language, 2017 – Elsevier
… system. Abstract. Despite recent advances in automatic speech recognition, one of the main stumbling blocks to the widespread adoption of Spoken Dialogue Systems is the lack of reliability of automatic speech recognizers …

Learning proactive behavior for interactive social robots
P Liu, DF Glas, T Kanda, H Ishiguro – Autonomous Robots, 2017 – Springer
… action using a timing threshold. This assumption has been made in HRI (Thomaz and Chao 2011; Chao and Thomaz 2011) and other spoken dialogue systems as well (Raux and Eske- nazi 2008). To determine a time threshold …

A Sequential Matching Framework for Multi-turn Response Selection in Retrieval-based Chatbots
Y Wu, W Wu, C Xing, C Xu, Z Li, M Zhou – arXiv preprint arXiv:1710.11344, 2017 – arxiv.org
… Dialog systems focus on helping people complete specific tasks in vertical domains (Young et al … In multi-turn con- versation, Sordoni et al. (Sordoni et al. 2015) compressed a context to a vector with a multi-layer perceptron in response generation; Serban et al. (Serban et al …

Non-Markovian Control with Gated End-to-End Memory Policy Networks
J Perez, T Silander – arXiv preprint arXiv:1705.10993, 2017 – arxiv.org
… alternative on sev- eral sequential decision tasks with immediate reward maximization like natural language translation [BCB14] or end-to-end dialog systems … Page 6. hidden layer of the perceptron reconstructing the noisy input of the time frame is placed into the memory blocks …

A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models
K Goyal, G Neubig, C Dyer… – arXiv preprint arXiv …, 2017 – arxiv.org
… [6] IV Serban, A. Sordoni, Y. Bengio, A. Courville, and J. Pineau, “Building end-to-end dialogue systems using generative hierarchical neural network models,” in … [20] M. Collins and B. Roark, “Incremental parsing with the perceptron algorithm,” in Proceedings of the 42nd Annual …

A Vieira – Ubiquitous Machine Learning and Its Applications, 2017 – books.google.com
… An example of a multilayered perceptron MLP is shown in next Figure: 43 … a softmax layer and applying supervised backpropagation-as if they were multilayer perceptrons … Chatbots Chatbots, also called Conversational Agents or Dialog Systems, are algorithms designed to …

Emotion-Based 3D CG Character Behaviors
K Kaneko, Y Okada – Encyclopedia of Computer Graphics and Games, 2017 – Springer
… The model was applied to their pro- totype application which has a dialogue system and a talking head with synchronized speech and … Neutral, from speech utterances data by using RBM and DBN which obtained better scores than a multilayer perceptron classifier (Albornoz et …

Active learning from peers
K Murugesan, J Carbonell – Advances in Neural Information …, 2017 – papers.nips.cc
… Our approach follows a perceptron-based update rule in which the model for a given task is updated only when the … optimizing financial trading, email prioritization and filtering, personalized news, crowd source-based annotation, spam filtering and spoken dialog system, etc …

Combining Domain Knowledge and Deep Learning Makes NMT More Adaptive
L Ding, Y He, L Zhou, Q Liu – China Workshop on Machine Translation, 2017 – Springer
… Thus, prior knowledge is well retained and helps benefit many NLP task, such as dictionary compilation, sentiment classification, machine translation and dialogue system etc … In the deep fusion model of neural network, a multi-layer perceptron is designed in the top layer as Fig …

Incorporating Structural Bias into Neural Networks
Z Yang – 2017 – cs.cmu.edu
Page 1. November 2, 2017 DRAFT Thesis Proposal Incorporating Structural Bias into Neural Networks Zichao Yang Nov 2017 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee …

Transition-Based Technique for Syntactic Linearization and Deep Input Linearization
RS Puduppully – 2017 – web2py.iiit.ac.in
… In a hash-based parameter model, it significantly improves the time efficiency. Given a set of labeled training examples, the averaged perceptron with early update [12] is used 2.3.0.1 Input syntactic constraints Following earlier work [43, 50, 47], Liu et al …

Telugu dependency parsing using different statistical parsers
BVS Kumari, RR Rao – Journal of King Saud University-Computer and …, 2017 – Elsevier
… Parsing is useful in major NLP applications like Machine Translation, Dialogue Systems, Question Answering, etc. This led to the development of grammar-driven, data-driven and hybrid parsers … Averaged perceptron (Collins, 2002) is used for learning …

Analyzing User Emotions via Physiology Signals
B Myroniv, CW Wu, Y Ren, A Christian, E Bajo… – ikelab.net
… SVM), and Multilayer Perceptron Neural Net- works (abbr. MP). 3.2 … [26] Andreas Haag, Silke Goronzy, Peter Schaich, Jason Williams,“Emotion Recognition Using Biosen- sors: First Steps towards an Automatic System,” Affective Dialogue Systems, Tutorial and Research …

A class-specific copy network for handling the rare word problem in neural machine translation
F Wang, W Chen, Z Yang, X Zhang… – Neural Networks (IJCNN …, 2017 – ieeexplore.ieee.org
… The gate softmax is modeled as a multi-layer perceptron followed with a softmax layer: p(zt|(y, z)<t,x) = ?(f(x, ht?1; ?)) (15) … In the future, we will try to apply the class-specific copy network in other NLP tasks, such as the dialogue system and the question answering …

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
M Palmer, R Hwa, S Riedel – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
Page 1. EMNLP 2017 The Conference on Empirical Methods in Natural Language Processing Proceedings of the Conference September 9-11, 2017 Copenhagen, Denmark Page 2. c?2017 The Association for Computational Linguistics …

Využití uživatelské odezvy pro zvýšení kvality ?e?ové syntézy
V Hude?ek – 2017 – dspace.cuni.cz
… Linguistics Abstract: Although spoken dialogue systems have greatly improved, they still cannot handle communications involving unknown topics … We will investigate methods that can improve spoken dialogue systems by correcting the pronunciation of unknown words …

A radial base neural network approach for emotion recognition in human speech
L Hussain, I Shafi, S Saeed, A Abbas, IA Awan… – IJCSNS, 2017 – paper.ijcsns.org
… Besides, there are some other emotion recognition systems to recognize real-life emotions such as dialogue systems, surveillance, tasks and media retrieval. Likewise, for acoustic features, the linguistic information is derived from the Dynamic Bayesian Network (DBN) …

BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
Z Lipton, X Li, J Gao, L Li, F Ahmed, L Deng – arXiv preprint arXiv …, 2017 – arxiv.org
… Figure 1: Components of a dialogue system ets, and ultimately completes a booking … For simplicity, we explain the idea for multilayer perceptrons (MLPs). An L-layer MLP for model P(y|x, w) is parame- terized by weights w = {Wl,bl}L l=1: y = WL · ?(WL?1 · … · ?(W1 · x + b1) + …

Natural Logic Inference for Emotion Detection
H Ren, Y Ren, X Li, W Feng, M Liu – Chinese Computational Linguistics …, 2017 – Springer
… As one of the most important research topics in natural language processing, emotion detection is widely used in opinion mining, product recommendation, dialog system, and so on [1] … We apply averaged perceptron, a supervised linear learning model, to estimate parameters …

Towards Interpretable Vision Systems
P Zhang – 2017 – vtechworks.lib.vt.edu
Page 1. Towards Interpretable Vision Systems Peng Zhang Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Engineering Devi Parikh, Chair …

Improving native language (L1) identifation with better VAD and TDNN trained separately on native and non-native English corpora
Y Qian, K Evanini, PL Lange, RA Pugh… – … (ASRU), 2017 IEEE, 2017 – ieeexplore.ieee.org
… native speakers and L1-specific speakers [3], and (c) other human-machine voice interface applications, eg, facilitating a spoken dialog system, which can … We investigate multi-layer perceptron (MLP) based multi-class classification for 25 L1s when i-vectors are used as inputs …

A conditional variational framework for dialog generation
X Shen, H Su, Y Li, W Li, S Niu, Y Zhao… – arXiv preprint arXiv …, 2017 – arxiv.org
… Abstract Deep latent variable models have been shown to facilitate the response generation for open-domain dialog systems … This classifier can be designed as, but not restricted to, multilayer perceptrons (MLP) or support vector machines (SVM) …

Application to Sentiment Analysis
R Satapathy, E Cambria, A Hussain – … Analysis in the Bio-Medical Domain, 2017 – Springer
… develop plots or to compose music on the fly, or as a part of human-machine communication in dialogue systems and conversational … PIERRE then learns multiple multi-layer perceptrons on different levels of abstraction to model the relation between different recipes (essentially …

Image Description Using Deep Neural Network
AP Deshmukh, AS Ghotkar – 2017 – ijsrst.com
… and is core to a wide range of NLP applications such as machine translation, summarizing, dialogue systems and machine assisted revision … A. Convolution Neural Network Convolutional Neural Networks (CNN) are biologically- inspired variants of Multi Layered Perceptrons …

Phonemic Restoration Based on the Movement Continuity of Articulation
C Zhao, L Wang, J Dang – International Conference on Neural Information …, 2017 – Springer
… A DNN is a multi-layer perceptron with several hidden layers between the input layer and the output layer, as illustrated in Fig … K., Traum, DR: Detecting the status of a predictive incremental speech understanding model for real-time decision-making in a spoken dialogue system …

Towards Natural Language Understanding using Multimodal Deep Learning
S Bos – pdfs.semanticscholar.org
Page 1. Towards Natural Language Understanding using Multimodal Deep Learning Steven Bos Delft Un iversity of T echnolog y Page 2. Page 3. Towards Natural Language Understanding using Multimodal Deep Learning THESIS …

Natural Language Inference with External Knowledge
Q Chen, X Zhu, ZH Ling, D Inkpen – arXiv preprint arXiv:1711.04289, 2017 – arxiv.org
… 2 Page 3. 2016), and dialogue system (Chen et al., 2016) … We concatenate all pooling vectors, ie, mean, max, and weighted pooling, into a fixed-length vector and then put the vector into a final multilayer perceptron (MLP) classifier …

Multiple relations extraction among multiple entities in unstructured text
J Liu, H Ren, M Wu, J Wang, H Kim – Soft Computing, 2017 – Springer
… relations among entities, mine latent relations among entities, and perform other complex NLP work such as spoken dialog systems and conversational … A mul- tilayer perceptron was used for combining sentence level feature and lexical feature into the final extracted feature …

Learning Algorithms for Broad-Coverage Semantic Parsing
S Swayamdipta – 2017 – cs.cmu.edu
Page 1. Learning Algorithms for Broad-Coverage Semantic Parsing Swabha Swayamdipta September 2017 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee: Noah A. Smith, Chair …

B Cabaleiro, A Peñas, S Manandhar – Knowledge-Based Systems, 2017 – Elsevier
… the supervision problem by using forms of distant supervision, ie observation of system behaviour [11], conversations from dialog systems [12], schema … It uses a Structured Perceptron that employs several kinds of features from the alignment between logic forms and properties …

AI for Classic Video Games using Reinforcement Learning
S Sodhi – 2017 – scholarworks.sjsu.edu
… algorithm and model-free, and thus approximated the value function with the help of a multi-layer perceptron having only one hidden layer … But for a multilayer perceptron model, the image needs to be reduced down to a vector of pixels, hence …

Special Issue in Computational Biological Data science
… Find the global optimum to get the reduced feature using Particle Swarm Optimization (PSO) method. Finally, Multilayer Perceptron (MLP) classifier is trained using reduced features to classify the IAN (Inferior Alveolar Nerve) injured on a healthy object …

Learning an Executable Neural Semantic Parser
J Cheng, S Reddy, V Saraswat, M Lapata – arXiv preprint arXiv …, 2017 – arxiv.org
… The grammar defines the space of derivations from sentences to logical forms, and the model together with the parsing algorithm find the most likely derivation. The model which can take the form of a struc- tured perceptron (Zettlemoyer and Collins 2007; Lu et al …

A Content Analysis Of The Research Approaches In Speech Emotion Recognition
T Özseven, M Dü?enci, A Durmu?o?lu – ijesrt.com
Page 1. ISSN: 2277-9655 [Ozseven* et al., 7(1): January, 2018] Impact Factor: 4.116 IC™ Value: 3.00 CODEN: IJESS7 http: // www.ijesrt.com © International Journal of Engineering Sciences & Research Technology [1] IJESRT …

Classifying a Person’s degree of accessibility from natural body language during social human–robot interactions
D McColl, C Jiang, G Nejat – IEEE transactions on cybernetics, 2017 – ieeexplore.ieee.org
… The joint data corre- sponded to postures representing affect after winning or losing scenarios. A multilayer perceptron was used to recognize four affective states: 1) triumphant; 2) defeated; 3) concentrating; and 4) frustrated …

A Framework For Enhancing Speaker Age And Gender Classification By Using A New Feature Set And Deep Neural Network Architectures
A Abumallouh – 2017 – scholarworks.bridgeport.edu
… Perceptron Network MSM MFCCs-Speakers Models NB Naïve Bayes PLP Perceptual Linear Prediction PPR Parallel Phone Recognizer RBM Restricted Boltzmann Machine ROC Receiver Operating Characteristics SCM SDC Class Models SDS Spoken Dialogue Systems …

WORKSHOP PROGRAM
A ANANDKUMAR, FEI SHA – 2017 – pdfs.semanticscholar.org
… Page 6 of 30 02:00 PM Joelle Pineau: Discriminative and Generative Models for Building Dialogue Systems … Abstract 7: Joelle Pineau: Discriminative and Generative Models for Building Dialogue Systems in Learning to Generate Natural Language, 02:00 PM …

Speech perception by humans and machines
MH Davis, O Scharenborg – Speech perception and spoken word …, 2017 – books.google.com
… probable word sequence can then be transcribed, used to drive a dialogue system, or for … Among the earliest of these was the perceptron learning procedure of Rosenblatt (1958) … learn non-linearly separable mappings that evade simpler methods such as perceptrons or HMMs …

Variational Reasoning for Question Answering with Knowledge Graph
Y Zhang, H Dai, Z Kozareva, AJ Smola… – arXiv preprint arXiv …, 2017 – arxiv.org
… moving average. b(a, q) is another neural network that fits the expected normalized learning signal. In our experiments, we simply build a two-layer perceptron with concatenated one-hot answer and question features. Here b …

Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
S Poria, H Peng, A Hussain, N Howard, E Cambria – Neurocomputing, 2017 – Elsevier

Detecting sarcasm in customer tweets: an NLP based approach
S Mukherjee, PK Bala – Industrial Management & Data Systems, 2017 – emeraldinsight.com
… Despite the difficulties, the huge benefit of detecting sarcasm has been recognized in many computer interaction-based applications, such as review summarization, dialogue systems and review ranking systems (Davidov et al., 2010) …

ASVspoof: the automatic speaker verification spoofing and countermeasures challenge
Z Wu, J Yamagishi, T Kinnunen… – IEEE Journal of …, 2017 – ieeexplore.ieee.org
… The reliability of ASV technology has advanced consider- ably recently and is currently deployed in a growing variety of practical applications such as in call centres, for spoken dialogue systems, and in many mass … A multi- layer perceptron (MLP) was trained for each feature …

Advances in Neural Networks-ISNN 2017: 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017 …
F Cong, A Leung, Q Wei – 2017 – books.google.com
Page 1. Fengyu Cong· Andrew Leung Qinglai Wei (Eds.) Advances in Neural Networks – ISNN 2017 14th International Symposium, ISNN 2017 Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017 Proceedings, Part I 123 Page 2 …

Deep Reinforcement Learning in Natural Language Scenarios
J He – 2017 – digital.lib.washington.edu
… Figure Number Page 2.1 A multilayer perceptron with input dimension 2, output dimension 2, and one hidden layer with hidden dimension 3 . . . . . 9 … such as video gaming, human-computer dialogue systems, newsfeed recommendation, and …

Neural network methods for natural language processing
Y Goldberg – Synthesis Lectures on Human Language …, 2017 – morganclaypool.com
… Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 … For over a decade, core NLP techniques were dominated by linear modeling approaches to supervised learning, centered around algorithms such as Perceptrons, linear Support Vector Machines, and …

Reconstruct & Crush Network
E Merdivan, MR Loghmani, M Geist – Advances in Neural …, 2017 – papers.nips.cc
… We plan to study further this aspect in the near future, in order to provide an alternative metric for dialogue systems evaluation. Acknowledgments … [3] H. Bourlard and Y. Kamp. Auto-association by multilayer perceptrons and singular value decomposition …

Broad Discourse Context for Language Modeling
M Torres Garcia – 2017 – research-collection.ethz.ch
… An- other example are dialogue systems, where discourse understanding is needed to produce valid utterances for a given conversation context. Currently, recur- rent neural network based language models hold the state-of-the-art. 1.1 Problem Statement and Motivation …

Synthesizing normalized faces from facial identity features
F Cole, D Belanger, D Krishnan, A Sarna… – IEEE Conference on …, 2017 – arxiv.org
… In this article, the author introduces a mathematical structure called MLP algebra on the set of all Multilayer Perceptron Neural Networks(MLP), which can serve as a guiding … arXiv:1701.05011 [pdf, ps, other] Title: Assessing User Expertise in Spoken Dialog System Interactions …

Improving scalability of inductive logic programming via pruning and best-effort optimisation
M Kazmi, P Schüller, Y Sayg?n – Expert Systems with Applications, 2017 – Elsevier

Explanation and justification in machine learning: A survey
O Biran, C Cotton – IJCAI-17 Workshop on Explainable AI (XAI), 2017 – intelligentrobots.org
… for tasks such as picking the next course in a college curriculum;[Dodson et al., 2011] propose a dialog system, instead of … Such proposals were made for Bayesian networks [Suermondt, 1992], multi- layer Perceptrons [Feraud and Clerot, 2002], RBF networks [Robnik-Šikonja et …

Dimensional Affect Recognition from HRV: an Approach Based on Supervised SOM and ELM
LA Bugnon, RA Calvo… – IEEE Transactions on …, 2017 – ieeexplore.ieee.org
… They have shown to be faster and more accurate than traditional multi-layer perceptrons and support vector machines (SVM) in several benchmarks [38] … Haag et al. [50] proposed an assessment of IAPS ratings using a multi-layer perceptron as regressor with multimodal inputs …

Patient subtyping via time-aware LSTM networks
IM Baytas, C Xiao, X Zhang, F Wang, AK Jain… – Proceedings of the 23rd …, 2017 – dl.acm.org
… but also to provide interpretability for physicians. While the authors did not use RNN, they used a multi-layer perceptron to generate a visit representation for each visit vector. Auto-Encoder Networks. e purpose of our study is …

K Lin, D Li, X He, Z Zhang, MT Sun – Advances in Neural Information …, 2017 – papers.nips.cc
… processing, which is essential to many applications such as machine translation [1], image captioning [6], and dialogue systems [26] … In conventional GANs [8], the discriminator with multilayer perceptrons outputs a binary probability distribution to suggest whether the unknown …

On Inductive Abilities of Latent Factor Models for Relational Learning
T Trouillon, É Gaussier, CR Dance… – arXiv preprint arXiv …, 2017 – arxiv.org
… Not all latent models are actually factorization models. Among these are a variety of neural-network models, including the neural tensor networks (Socher et al., 2013), or the multi-layer perceptron used in Dong et al. (2014) …

Automatic assessment of depression based on visual cues: A systematic review
A Pampouchidou, P Simos, K Marias… – IEEE Transactions …, 2017 – ieeexplore.ieee.org
Page 1. 1949-3045 (c) 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org …

Neural machine translation and sequence-to-sequence models: A tutorial
G Neubig – arXiv preprint arXiv:1703.01619, 2017 – arxiv.org
Page 1. Neural Machine Translation and Sequence-to-sequence Models: A Tutorial Graham Neubig Language Technologies Institute, Carnegie Mellon University 1 Introduction This tutorial introduces a new and powerful set …

Sequential modeling, generative recurrent neural networks, and their applications to audio
S Mehri – 2017 – papyrus.bib.umontreal.ca
… Step function. This was originally used in Perceptron models that exactly simulated the threshold of a cell. Step(z) = ?? ? 1 z ? 0 … These chain structures are extensively used in this field. Feed-forward neural networks, also called multilayer perceptrons (MLPs; see Fig …

Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform
C Baskin, N Liss, A Mendelson… – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform Chaim Baskin Natan Liss Avi Mendelson Evgenii Zheltonozhskii Technion – Israel Institute of Technology {chaimbaskin …

Computational Linguistic Creativity: Poetry generation given visual input
M Loller-Andersen – 2017 – brage.bibsys.no
… The most basic form of the perceptron … The first deep systems emerged in the 1960s: Ivakhnenko and Lapa (1966) published the first general, working learning algorithm for supervised deep feed forward multilayer perceptrons., while Ivakhnenko (1971) already de- scribed a …

B Pierpaolo, N Malvina, S Rachele… – ITALIAN JOURNAL OF …, 2017 – iris.unito.it
Page 1. Volume 3, Number 1 june 2017 Emerging Topics at the Third Italian Conference on Computational Linguistics and EVALITA 2016 IJCoL Italian Journal Rivista Italiana of Computational Linguistics di Linguistica Computazionale ccademia university press aA Page …

Voice activity detection and garbage modelling for a mobile automatic speech recognition application
M Ishaq – 2017 – aaltodoc.aalto.fi
… LM Language Model MFCC Mel Frequency Cepstral Coefficient MLE Maximum Likelihood Estimation MLP Multi Layer Perceptron MS WAV … to-speech synthesis system with the very large vocabulary system happened, which enabled the spoken dialog systems with multiple …

Incremental generative models for syntactic and semantic natural language processing
JM Buys – 2017 – ora.ox.ac.uk
… cations. Examples include automatic speech recognition, machine translation, text pre- diction on mobile keyboards, automatic e-mail reply suggestions and dialogue systems. Further language generation tasks that recently drew attention include image caption gen …

Deep Learning for Distant Speech Recognition
M Ravanelli – arXiv preprint arXiv:1712.06086, 2017 – arxiv.org
… video classification), machine translation, as well as in natural language processing (for dialogue systems, question answering, image captioning … for instance, the development of real-time speech recognizers or low- latency dialogue systems …

Data-Driven HRI: Reproducing interactive social behaviors with a conversational robot
CC Liu – 2017 – ir.library.osaka-u.ac.jp
Page 1. Title Data-Driven HRI : Reproducing interactive social behaviors with a conversational robot Author(s) Liu, Chun Chia Citation Issue Date Text Version ETD URL https://doi.org/ 10.18910/61827 DOI 10.18910/61827 rights Page 2. Data-Driven HRI …

Learning Logic Rules From Text Using Statistical Methods For Natural Language Processing
M KAZMI – 2017 – peterschueller.com
Page 1. LEARNING LOGIC RULES FROM TEXT USING STATISTICAL METHODS FOR NATURAL LANGUAGE PROCESSING by MISHAL KAZMI Submitted to the Graduate School of Engineering and Natural Sciences in Partial Fulfillment of the Requirements for the Degree of …

Finite state models for recognition and validation of read prompts
A Rouhe – 2017 – aaltodoc.aalto.fi
Page 1. Finite state models for recognition and validation of read prompts Aku Rouhe School of Electrical Engineering Thesis submitted for examination for the degree of Master of Science in Technology. Espoo 31.7.2017 Thesis supervisor: Prof. Mikko Kurimo Thesis advisor …

Processing of speech signals for robust recognition in practical environments
V Pannala – CSI transactions on ICT, 2017 – Springer
… In these methods, the models are pre-trained with large amount of data. Training methods in supervised techniques include Gaussian mixture models (GMM)[30], hidden Markov models (HMM) [36] and multi-layer perceptrons (MLP) [30] …

Leveraging Legal Stringency on Artificial Intelligence Applications-A’Copyright Law on Artificial Intelligence’Debate
P Bhattacharya – 2017 – papers.ssrn.com
… Image and voice recognition are one of the examples of deep learning. 42 An example of an automated online assistant having a text based dialog system, available in CC0 1.0 Universal (CC0 1.0) Public Domain Dedication …

Natural Language Processing for Social Media
A Farzindar, D Inkpen – Synthesis Lectures on Human …, 2017 – morganclaypool.com
… Semantic Role Labeling Martha Palmer, Daniel Gildea, and Nianwen Xue 2010 Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 Introduction to Chinese Natural Language Processing Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang 2009 …

Learning from Temporally-Structured Human Activities Data
ZC Lipton – 2017 – search.proquest.com
… 131. 8.1 Introduction . . . . . 131. 8.2 Task-completion dialogue systems . . . . . 133. viii. 8.2.1 Dialog-acts … (black). . . . 128. Figure 8.1: Components of a dialogue system . . . . . 134 …

Emotion Recognition from Speech
A Wendemuth, B Vlasenko, I Siegert, R Böck… – Companion …, 2017 – Springer
… Regarding static modeling, the list of possible classification techniques seems endless: multi-layer perceptrons or other types of neural networks, Bayes classifiers, Bayesian decision networks, random forests, Gaussian mixture models (GMMs), decision trees, k-nearest …

Speech recognition using articulatory and excitation source features
KS Rao, KE Manjunath – 2017 – books.google.com
… Some of the topics covered in this series include the presentation of real life commercial deployment of spoken dialog systems, contemporary methods of speech parameterization, developments in information … [9] proposed hybrid HMM/multilayer perceptron (MLPs) approach …

4 Driver mirror-checking action detection
N Li, C Busso – Vehicle Systems and Driver Modelling: DSP …, 2017 – books.google.com
Page 93. Nanxiang Li and Carlos Busso 4 Driver mirror-checking action detection Using multi-modal signals Nanxiang Li, Carlos Busso: The University of Texas at Dallas, Richardson, TX 75080, USA. e-mail:{nxl056000, busso}@ utdallas …

Continuous robust sound event classification using time-frequency features and deep learning
I McLoughlin, H Zhang, Z Xie, Y Song, W Xiao, H Phan – PloS one, 2017 – journals.plos.org
… As a human-computer interfacing aid, machine hearing allows a speech-based dialogue system to react to auditory events in a similar way to humans … As with multi-layer perceptrons (MLPs), CNNs can be trained by gradient descent using back-propagation …

Deep Energy-Based Models for Structured Prediction
D Belanger – 2017 – scholarworks.umass.edu
… system used as the interface between a computer and a user. For example, when a dialogue system responds to a user query, it may produce its response as a sentence containing multiple words, and this sentence may be further converted into an audio …

Integrating Multiple Modalities into Deep Learning Networks
PN McNeil – 2017 – search.proquest.com
… MP-units as a Perceptron. Expanding on the Perceptron, Fukushima (1980) created a. hierarchical network out of multiple Perceptron networks. He called the hierarchical … neural network (and also the Perceptron described by Rosenblatt (1962)). The input layer …

Automated Feature Engineering for Deep Neural Networks with Genetic Programming
J Heaton – 2017 – search.proquest.com
… returns the value 1 if the neurons weighted inputs reach a value above a specified threshold; otherwise, it returns the value 0. Minsky and Papert (1969) described severe limitations in the perceptron in their monograph. They demonstrated that perceptrons were incapable of …

Can We Speculate Running Application With Server Power Consumption Trace?
Y Li, H Hu, Y Wen, J Zhang – IEEE transactions on cybernetics, 2017 – ieeexplore.ieee.org
Page 1. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON CYBERNETICS 1 Can We Speculate Running Application With Server Power Consumption Trace …

Movement Data
S Hoogervorst – pure.tue.nl
Page 1. Eindhoven University of Technology MASTER Predicting website visitor gender and age with mouse movement data Hoogervorst, SJ Award date: 2016 Disclaimer This document contains a student thesis (bachelor’s …

Neural Logic Framework for Digital Assistants
N Cingillioglu, A Russo, K Broda – 2017 – imperial.ac.uk
Page 1. MEng Individual Project Imperial College London Department of Computing Neural Logic Framework for Digital Assistants Author: Nuri Cingillioglu Supervisor: Prof. Alessandra Russo Second Marker: Dr. Krysia Broda June 16, 2017 Page 2. Abstract …

Learning Generative End-to-end Dialog Systems with Knowledge
T Zhao – 2017 – cs.cmu.edu
… Page 2. November 21, 2017 DRAFT Keywords: dialog systems, end-to-end models, deep learning, reinforcement learn- ing, generative models, transfer learning, zero-shot learning Page 3 … Page 17. November 21, 2017 DRAFT Chapter 2 Related Work 2.1 Dialog Systems …

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