LVCSR & Artificial Intelligence 2018


Notes:

Large-vocabulary continuous speech recognition (LVCSR, more commonly known as speech-to-text, full transcription or ASR – automatic speech recognition) uses a set of words (bi-grams, tri-grams etc.) as the basic unit.

Resources:

Wikipedia:

See also:

100 Best CMUSphinx VideosHTK (Hidden Markov Model Toolkit) & Dialog Systems | Kaldi ASR


Attention-based audio-visual fusion for robust automatic speech recognition
G Sterpu, C Saam, N Harte – Proceedings of the 2018 on International …, 2018 – dl.acm.org
… One reason is the inconclusive research on what are good visual features for Large Vocabulary Continuous Speech Recognition (LVCSR) [14] that match the well established Mel-frequency cepstral coefficients for acoustic … In Thirtieth AAAI Conference on Artificial Intelligence …

Semi-orthogonal low-rank matrix factorization for deep neural networks
D Povey, G Cheng, Y Wang, K Li… – Proceedings of …, 2018 – pdfs.semanticscholar.org
… We present experiments 2000 hours Fisher + Switchboard large vocabulary continuous speech recognition (LVCSR) task and 300 hours Switchboard … feedforward neural networks,” in Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics …

A critical review and analysis on techniques of speech recognition: The road ahead
AV Haridas, R Marimuthu… – International Journal of …, 2018 – content.iospress.com
… The Artificial Intelligence approach [77] is a hybrid of the acoustic-phonetic technique and pattern recognition method … it was exposed that ANNs perform a key role in significant speech applications, such as large vocabulary continuous speech recognition (LVCSR) and …

Research on Interactive English Speech Recognition Algorithm in Multimedia Cooperative Teaching
S Peng – … Conference on Intelligent Transportation, Big Data & …, 2018 – ieeexplore.ieee.org
… Journal of Chongqing University of Posts & Telecommunications, 2008, 26(26):1491Y1507 [2] SHAN YuXiang, DENG Yan, LIU Jia. A Novel Large Vocabulary Continuous Speech Recognition Algorithm Combined with Language Recognition …

On the application of reservoir computing networks for noisy image recognition
A Jalalvand, K Demuynck, W De Neve, JP Martens – Neurocomputing, 2018 – Elsevier
Skip to main content …

Semi-supervised Adaptation of Assistant Based Speech Recognition Models for different Approach Areas
M Kleinert, H Helmke, G Siol, H Ehr… – 2018 IEEE/AIAA 37th …, 2018 – ieeexplore.ieee.org
… A. Speech Recognition Applications in ATM Artificial intelligence (AI) and in particular machine learn- ing applications have made a significant progress in the last few years, enabling computers to make a series of major break- throughs that were previously impossible …

Sequence-to-sequence asr optimization via reinforcement learning
A Tjandra, S Sakti, S Nakamura – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… Dec. 2011, IEEE Signal Processing Society, IEEE Catalog No.: CFP11SRW-USB. [17] Awni Y Hannun, Andrew L Maas, Daniel Jurafsky, and An- drew Y Ng, “First-pass large vocabulary continuous speech recognition using bi-directional recurrent DNNs,” arXiv …

Improvements in Serbian speech recognition using sequence-trained deep neural networks
E Pakoci, B Popovi?, D Pekar – SPIIRAS Proceedings, 2018 – researchgate.net
… More specifically, several variants of the new large vocabulary continuous speech recognition (LVCSR) system are described, all based on the … ARTIFICIAL INTELLIGENCE, KNOWEDGE AND DATA ENGINEERING …

Construction of large scale isolated word speech corpus in Bangla
MF Khan, MA Sobhan – Global Journal of Computer Science …, 2018 – computerresearch.org
… techniques makes this research effort as popular field of natural language processing as well as artificial intelligence … DavidPye, Jonathan Foote and Steve Renals, “WSJCAM0: A British English Speech Corpus For Large Vocabulary Continuous Speech Recognition”, In Proc …

HMM-Based Lightweight Speech Recognition System for Gujarati Language
JH Tailor, DB Shah – Information and Communication Technology for …, 2018 – Springer
… 1.2 HMM. HMM is a rich mathematical structure that is used for modeling data in multiple applications like speech recognition, artificial intelligence, data compression, and pattern recognition … A large-vocabulary continuous speech recognition system for Hindi …

Text classification based on deep belief network and softmax regression
M Jiang, Y Liang, X Feng, X Fan, Z Pei, Y Xue… – Neural Computing and …, 2018 – Springer
… Feng; Xiaojing Fan; Zhili Pei; Yu Xue; Renchu Guan Email author. Recent advances in Pattern Recognition and Artificial Intelligence … ICASSP.2010.5495072 Google Scholar. 5. Dahl G, Yu D, Deng L, Acero A (2011) Large vocabulary continuous speech recognition with context …

Speech recognition in a dialog system: from conventional to deep processing
A Becerra, JI de la Rosa, E González – Multimedia Tools and Applications, 2018 – Springer
… Speech recognition could be seen as an artificial intelligence area whose objective is to convert a speech signal … data, long-distance information, and model generalization, which constrain the prediction capabilities for LVCSR (large-vocabulary continuous speech recognition) …

A fixed-point neural network architecture for speech applications on resource constrained hardware
M Shah, S Arunachalam, J Wang, D Blaauw… – Journal of Signal …, 2018 – Springer
… In Proceedings of the national conference on artificial intelligence, (Vol. 20 pp. 1118–1123).Google Scholar. 11. Dahl, GE, Yu, D., Deng, L., & Acero, A. (2011). Large vocabulary continuous speech recognition with context-dependent DBN-HMMs …

Automatic dnn node pruning using mixture distribution-based group regularization
T Yoshida, T Moriya, K Watanabe… – Proc. of …, 2018 – isca-speech.org
… In recent years, the Deep Neural Network (DNN) has attracted attention as an artificial intelligence technology because of its … Efficient WFST- based one-pass decoding with on-the-fly hypothesis rescoring in extremely large vocabulary continuous speech recognition,” IEEE Trans …

Training deep neural networks with non-uniform frame-level cost function for automatic speech recognition
A Becerra, JI de la Rosa, E González… – Multimedia Tools and …, 2018 – Springer
… [24]. They propose two approaches for improving the loss function for DNN frame-level training in large vocabulary continuous speech recognition (LVCSR), which is often constructed with an output layer with softmax Page 4. 27234 Multimed Tools Appl (2018) 77:27231–27267 …

Whispered Speech Recognition using Hidden Markov Models and Support Vector Machines
J Gali?, B Popovi?, DŠ Pavlovi? – Acta Politechnica Hungarica, 2018 – uni-obuda.hu
Page 1. Acta Polytechnica Hungarica Vol. 15, No. 5, 2018 – 11 – Whispered Speech Recognition using Hidden Markov Models and Support Vector Machines Jovan Gali?1,2, Branislav Popovi?3, Dragana Šumarac Pavlovi?1 …

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System
F Zamora-Martinez, MJ Castro-Bleda – International journal of neural …, 2018 – World Scientific
Page 1. 2 April 6, 2018 18:19 1850007 International Journal of Neural Systems, Vol. 28, No. 0 (2018) 1850007 (15 pages) c© World Scientific Publishing Company DOI: 10.1142/S0129065718500077 Efficient Embedded Decoding …

Automatic speech recognition system for Tunisian dialect
A Masmoudi, F Bougares, M Ellouze, Y Estève… – Language Resources …, 2018 – Springer
Although Modern Standard Arabic is taught in schools and used in written communication and TV/radio broadcasts, all informal communication is typically carried out in dialectal Arabic. In this work,…

BRI: Mining business big data qualities
J Hamilton, S Tee – 22nd International Conference on ISO & TQM, 2018 – hk5sa.com
… China has embraced this vision, and is aiming to be the global leader in artificial intelligence (AI) by 2030 … These transcript or large vocabulary continuous speech recognition approaches first transcribe the audio speech content, then engage text- based analytics to find each …

Unsupervised spatial lexical acquisition by updating a language model with place clues
A Taniguchi, T Taniguchi, T Inamura – Robotics and Autonomous Systems, 2018 – Elsevier
Skip to main content …

Offline Speech Recognition Development
L Debatin, AH Filho, RLS Dazzi – 2018 – scitepress.org
… According to Coppin (2010), Artificial Intelligence involves the use of methods based on the intelligent behavior of humans to solve complex problems … A Bottom-Up Modular Search Approach to Large Vocabulary Continuous Speech Recognition …

Automatic Speech Recognition Techniques: A Review
AAA Alasadi, RR Deshmukh – researchgate.net
… were used to improve speech recognition performance in acoustic modelling for large vocabulary continuous speech recognition (LVCSR) [40] [38] 6. CLASSIFICATION TECHNIQUES STAGE … 6.3 Artificial Neural Network The artificial intelligence approach ([47], Lesser et al …

Speech communication integrated with other modalities
A Karpov, I Mporas – 2018 – Springer
… by Springer in the book series Lecture Notes in Computer Science, sub-series Lecture Notes in Artificial Intelligence … In the fourth article “Experimenting with lipreading for large vocabulary continuous speech recognition” by Karel Pale?ek [6], an audio-visual approach for …

Large Vocabulary Continuous Audio-Visual Speech Recognition
G Sterpu – Proceedings of the 2018 on International Conference …, 2018 – dl.acm.org
… Recent developments in the Machine Learning area, together with the release of suitable audio-visual datasets aimed at large vocabulary continuous speech recognition, have led to a renewal of the lip-reading topic, and al- low us … In AAAI Conference on Artificial Intelligence …

Arabic Continuous Speech Recognition Based on Hybrid SVM/HMM Model
E Zarrouk, YB Ayed, F Gargouri – Communication and Signal …, 2018 – books.google.com
… The development of a robust large vocabulary continuous speech recognition system needs a large vocabulary speech corpus for the Arabic language … Currently, he focuses his research on pattern recognition, artificial intelligence and speech recognition in MIRACL, Multimedia …

Speech Recognition Application for the Speech Impaired using the Android-based Google Cloud Speech API.
N Anggraini, A Kurniawan, LK Wardhani, N Hakiem – Telkomnika, 2018 – researchgate.net
… Machine (DBN) with a pre-trained Artificial Neural Network/Hidden Markov Model (ANN/HMM) model for large vocabulary continuous speech recognition on two … 3.1.2. Speech recognition In a book describing artificial intelligence [2], it is mentioned that speech recognition is the …

Manner of articulation based Bengali phoneme classification
T Bhowmik, SKD Mandal – International Journal of Speech Technology, 2018 – Springer
… Siniscalchi et al. developed an MLP-based, bottom-up stepwise knowledge integration technique in large vocabulary continuous speech recognition (LVCSR) (Siniscalchi et al. 2011) and replaced the MLP method with DNN (Siniscalchi et al …

Discriminatively trained continuous Hindi speech recognition system using interpolated recurrent neural network language modeling
M Dua, RK Aggarwal, M Biswas – Neural Computing and Applications, 2018 – Springer
… But MLE does not work well for large vocabulary continuous speech recognition (LVCSR) because it assumes that language model is prior known, training data are unlimited, and observations come from the known family of distribution (Gaussian) that are not possible in the …

Unsupervised Speech Denoising Method Based on Deep Neural Network
X Chen – 2018 11th International Symposium on Computational …, 2018 – ieeexplore.ieee.org
… At present, the research on large vocabulary continuous speech recognition system in China has approached the highest level in foreign countries … With the development of artificial intelligence and machine learning, speech recognition technology has been further developed …

Convolutional Neural Network and Feature Transformation for Distant Speech Recognition
HF Pardede, AR Yuliani… – International Journal of …, 2018 – search.proquest.com
… [19] R. Haeb-Umbach and H. Ney, “Linear discriminant analysis for improved large vocabulary continuous speech recognition,” in 1992 … His research interests include are speech recognition, pattern recognition, signal processing, machine learning and artificial intelligence …

Exploring the Effect of Tones for Myanmar Language Speech Recognition Using Convolutional Neural Network (CNN)
M Yangon – … Linguistics: 15th International Conference of the …, 2018 – books.google.com
… mm 2 Artificial Intelligence Laboratory, Okayama Prefectural University, Okayama, Japan ye@ c. oka-pu … in ASR tasks [1, 2]. CNN has gained higher performance than Deep Neural Network (DNN) across different large vocabulary continuous speech recognition (LVCSR) tasks …

Isolated Automatic Speech Recognition of Quechua Numbers using MFCC, DTW and KNN
HFC Chuctaya, RNM Mercado, JJG Gaona – pdfs.semanticscholar.org
… ASR is the area of artificial intelligence that transform the audio signals spoken by a person into a sequence of words that can be understood for a computer [6]. It has been … [18] M. Kumar, N. Rajput, and A. Verma, “A large-vocabulary continuous speech recognition system for …

Exploring RNN-Transducer for Chinese Speech Recognition
S Wang, P Zhou, W Chen, J Jia, L Xie – arXiv preprint arXiv:1811.05097, 2018 – arxiv.org
… In this paper, we explore RNN-T for a Chinese large vocabulary continuous speech recognition (LVCSR) task and aim to simplify the training … hierarchical re- current neural networks,” in Proceedings of the 20th Interna- tional Joint Conference on Artificial Intelligence, IJCAI 2007 …

Phase-Based Feature Representations for Improving Recognition of Dysarthric Speech
S Sehgal, S Cunningham… – 2018 IEEE Spoken …, 2018 – ieeexplore.ieee.org
… [15] C. Espaa-Bonet and JAR Fonollosa, “Automatic speech recognition with deep neural networks for im- paired speech,” Lecture Notes in Computer Science (in- cluding subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10077 LNAI, pp …

Adversarial Learning of Raw Speech Features for Domain Invariant Speech Recognition
A Tripathi, A Mohan, S Anand… – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… While the first author was at IIIT-Delhi, this work was partially sup- ported by the Infosys Center for Artificial Intelligence, IIIT-Delhi. 5962 … 216– 221. [10] Puming Zhan and Alex Waibel, “Vocal tract length normal- ization for large vocabulary continuous speech recognition,” Tech …

Development of Alexa Voice Services Software Development Kit For Speech Recognition Engine For Internet of Things
N Sharma – 2018 – tudr.thapar.edu
… into text format. In future, advancement and expansion of Speech Recognition techniques and Artificial Intelligence, Nueral Networks, Echo Cancellation, Beam Forming and Noise Reduction techniques will enhance the quality and efficiency of Speech Recognition Engines …

Lstm And Simple Rnn Comparison In The Problem Of Sequence To Sequence On Conversation Data Using Bahasa Indonesia
YD Prabowo, HLHS Warnars… – 2018 Indonesian …, 2018 – ieeexplore.ieee.org
… how to design a machine that can understand and respond to human language is part of artificial intelligence, specifically an … 6] D. Ellis and N. Morgan, “Size matters: An empirical study of neural network training for large vocabulary continuous speech recognition,” in ICASSP …

Deep Bayesian Learning and Understanding
JT Chien – Proceedings of the 27th International Conference on …, 2018 – aclweb.org
… George Saon and Jen-Tzung Chien. 2012. Large-vocabulary continuous speech recognition systems: A look at some recent advances. IEEE Signal Processing Magazine, 29(6):18–33, Nov … In Proc. of AAAI Conference on Artificial Intelligence, pages 3295–3301 …

Reform of College Students’ Foreign Language Vocabulary Teaching and Effectiveness Analysis of Students’ Vocabulary Competence Based on Corpus …
S Wang, D Wang – Kuram ve Uygulamada Egitim Bilimleri, 2018 – estp.com.tr
… International Journal on Artificial Intelligence Tools, 20(03), 401-424. http://dx.doi … (1999). Japanese large- vocabulary continuous-speech recognition using a newspaper corpus and broadcast news. Speech Communication, 28(2), 155-166. http://dx.doi …

Development Of Algorithm For Combination Of Cloud Services For Speech Control Of Cyber-Physical Systems
A Škraba, V Stanovov, E Semenkin… – International Journal on …, 2018 – ijits-bg.com
… [4] Wessel F., Schlüter R., Macherey K., Ney H., Confidence Measures for Large Vocabulary Continuous Speech Recognition. IEEE Transactions on Speech and Audio Processing, Vol. 9, No … Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI’14) …

FIND IT An Android application to find misplaced phone of user in the vicinity
B Tekwani, V Bhandiwad… – … on I-SMAC (IoT in Social …, 2018 – ieeexplore.ieee.org
… It is a popular open source large vocabulary continuous speech recognition (LVCSR) system [2] … The application can also provide voice recognition feature using Artificial Intelligence. The application will be user- friendly for specially abled people …

Building MEDISCO: Indonesian Speech Corpus for Medical Domain
MR Qorib, M Adriani – 2018 International Conference on Asian …, 2018 – ieeexplore.ieee.org
… “First-pass large vocabulary continuous speech recognition using bi … D. Suendermann- Oeft, M. Miller, ” Crowdsourced Continuous Improvement of Medical Speech Recognition,” The AAAI-17 Workshop on Crowdsourcing, Deep Learning, and Artificial Intelligence Agents, San …

Disordered Speech Assessment Using Kullback-Leibler Divergence Features with Multi-Task Acoustic Modeling
Y Liu, Y Qin, S Feng, T Lee… – 2018 11th International …, 2018 – ieeexplore.ieee.org
… It is based on recent works demonstrating that through network combination, TDNN-BLSTM outperforms TDNN and TDNN-LSTM in large vocabulary continuous speech recognition (LVCSR) tasks, in both monolingual [15] and multilingual [16] scenarios …

Acoustic modeling in Automatic Speech Recognition-A Survey
A Waris, RK Aggarwal – 2018 Second International Conference …, 2018 – ieeexplore.ieee.org
… 1990- first speech recognition product for consumers ie Dragon Dictate • 1993 – The first large-vocabulary continuous speech recognition system Sphinx-II … using tiled convolutional neural networks.” In Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp …

L2 Mispronunciation Verification Based on Acoustic Phone Embedding and Siamese Networks
Z Wang, J Zhang, Y Xie – 2018 11th International Symposium …, 2018 – ieeexplore.ieee.org
… Speech corpora Chinese National Hi-Tech Project 863 [19] for Mandarin large vocabulary continuous speech recognition (LVCSR) system development was … using a “siamese” time delay neural network,” International Journal of Pattern Recognition and Artificial Intelligence, vol …

Game for Mayan Speaking Children with Speech Recognition Provided by an English Speech Corpus
CAM PALMA, VMCHI PECH, SAG SEGURA – 2018 – redi.uady.mx
… maya [5] T. Robinson, J. Fransen, D. Pye, J. Foote, S. Renals, “WSJCAMO: a British English speech corpus for large vocabulary continuous speech recognition”, International Conference … His researcher lines: Voice recognition, Artificial Intelligence, Human Computer Interaction …

Beyond posteriorgram: Bottleneck features for keyword search
B Yusuf, B Gundogdu, M Saraclar – 2018 26th Signal …, 2018 – ieeexplore.ieee.org
Page 1. Beyond Posteriorgram: Bottleneck Features for Keyword Search Bolaji Yusuf Electrical and Electronics Eng. Dept. Bogazici University Istanbul, Turkey bolaji.yusuf@ boun.edu.tr Batuhan Gundogdu Electrical and Electronics Eng. Dept …

Estimation of MVDR Beamforming Weights Based on Deep Neural Network
MJ Jo, GW Lee, JM Moon, C Cho, HK Kim – Audio Engineering Society …, 2018 – aes.org
… and Computer Science , Gwangju Institute of Science and Technology ( GIST ) , Gwangju 61005 , Korea 2 Artificial Intelligence Research Center … J . Foote , and S . Renals , WSJCAM0 : a British English speech corpus for large vocabulary continuous speech recognition , in Proc …

Automatic detection technique for voice quality inter-disciplinary methodologies
T Al Smadi – Journal of Advanced Sciences and Engineering …, 2018 – jaset.isnra.org
Page 1. 1 ISSN: xxx-xxxx (Print) ; xxxx-xxxx (Online) Journal of Advanced Sciences and Engineering Technologies available online at: http://www.isnra.com/ojs/index.php/ JASET/ Takialddin Al Smadi 1 Department of Communications …

Mutitask Learning Based Muti-examples Keywords Spotting in Low Resource Condition
Y Jianbin, K Jian, Z Wei-Qiang… – 2018 14th IEEE …, 2018 – ieeexplore.ieee.org
… I. INTRODUCTION As an important artificial intelligence technology to process a huge amount of speech data, keywords spotting (KWS … After decades of researching, KWS based on large vocabulary continuous speech recognition (LVCSR) [1] [2], templets based KWS [3] [4] [5] [6 …

Automatic Detection of Shadda in Modern Standard Arabic Continuous Speech
A Al-Sabri, A Adam, F Rosdi – International Journal on Advanced …, 2018 – researchgate.net
… 1Center for Artificial Intelligence Technology 2 Centre for Software Technology & Management Faculty of Information Science and Technology … They improved the Cambridge Arabic Large Vocabulary Continuous Speech Recognition (LVCSR) Speech-to-Text (STT) system …

Learning Frame-Level Recurrent Neural Networks Representations for Query-by-Example Spoken Term Detection on Mobile Devices
Z Zhu, Z Wu, R Li, Y Ning, H Meng – … Conference on AI and Mobile Services, 2018 – Springer
… AIMS 2018: Artificial Intelligence and Mobile Services – AIMS 2018 pp 55-66 | Cite as … Unlike keyword search that is usually based on large vocabulary continuous speech recognition (LVCSR) [2, 3], end-to-end system is widely employed in QbyE-STD task …

The implementation of Voice Command in Smart Homes
F Norberg, Z Yildirim – 2018 – diva-portal.org
… 10 3.3 Voice recognition and Artificial Intelligence ….. 11 … information. Voice Command, Smart Homes, Artificial Intelligence and Automation were the main key words used in the research, in all three databases …

Handwriting recognition by using deep learning to extract meaningful features
J Pastor-Pellicer, MJ Castro-Bleda… – AI … – content.iospress.com
… From this point of view, the recognition of handwritten text lines images shares many characteristics with Large Vocabulary Continuous Speech Recognition (LVCSR): a joint segmentation and classification task is required in both cases for decoding since we cannot split …

Generative RNNs for OOV Keyword Search
B Gundogdu, B Yusuf, M Saraclar – IEEE Signal Processing …, 2018 – ieeexplore.ieee.org
… I. INTRODUCTION RETRIEVAL of spoken content is an important task not only for finding the parts of interest in spoken archives, but also for facilitating automated speech mining for better large vocabulary continuous speech recognition (LVCSR) …

A View of the State of the Art of Dialogue Systems
L Ozaeta, M Graña – … Conference on Hybrid Artificial Intelligence Systems, 2018 – Springer
… of dialogue systems it’s been a topic of remarkable interest since the very beginning of the Artificial Intelligence [18] … been shown to be effective for natural language processing [14] including the tremendous succeed for large vocabulary continuous speech recognition of Deep …

Role Play Dialogue Aware Language Models Based on Conditional Hierarchical Recurrent Encoder-Decoder
R Masumura, T Tanaka, A Ando, H Masataki… – Proc. Interspeech …, 2018 – isca-speech.org
… AAAI Conference on Artificial Intelligence (AAAI), pp … [32] T. Hori, C. Hori, Y. Minami, and A. Nakamura, “Efficient WFST- based one-pass decoding with on-the-fly hypothesis rescoring in extremely large vocabulary continuous speech recognition,” IEEE transactions on Audio …

Cyberphysical strategies to develop creative interaction between students and social robots
M Graña – The Proceedings of JSME annual Conference on …, 2018 – jstage.jst.go.jp
… of dialogue systems it’s been a topic of remarcable interest since the very begining of the Artificial Intelligence [19] … been shown to be effective for natural language processing [15] includ- ing the tremendous succed for large vocabulary continuous speech recognition of Deep …

Sign Language Converter
S Jagruti, MPM Kochar, MCM Bajpayee – ijecscse.org
… 3.2.2.5. The Artificial Intelligence Approach The artificial intelligence approach attempts to mechanize the recognition procedure according to the way a person applies its intelligence in visualizing, analyzing, and finally making a decision on the measured acoustic features …

Sign Language Converter
AS Manchalwar, JS Wankhade… – … and Soft Computing …, 2018 – search.proquest.com
… 3.2.2.5. The Artificial Intelligence Approach The artificial intelligence approach attempts to mechanize the recognition procedure according to the way a person applies its intelligence in visualizing, analyzing, and finally making a decision on the measured acoustic features …

End-to-End Mandarin Speech Recognition Using Bidirectional Long Short-Term Memory Network
Y Yao, R Chellali – … Conference on Mechatronics and Intelligent Robotics, 2018 – Springer
… In large vocabulary continuous speech recognition, the embedded training method is widely applied in the acoustic model training process, ie we need to use the HMM automatically align the … In: Proceedings of the 7th International Joint Conference on Artificial Intelligence, vol …

Efficient Voice Trigger Detection for Low Resource Hardware
S Sigtia, R Haynes, H Richards, E Marchi… – Proc. Interspeech …, 2018 – isca-speech.org
… Some older approaches to KWS adapted large vocabulary continuous speech recognition (LVSCR) systems for detecting keywords [3, 4], however … Feedforward Neural Networks,” in Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics …

Compact Feedforward Sequential Memory Networks for Small-footprint Keyword Spotting
M Chen, S Zhang, M Lei, Y Liu, H Yao… – Proc. Interspeech …, 2018 – isca-speech.org
… Large vocabulary continuous speech recognition (LVCSR) based method is a traditional solution for this task … Understanding the difficulty of training deep feedforward neural networks,” in Proceedings of the Thir- teenth International Conference on Artificial Intelligence and S …

Keyword Spotting Based on Hypothesis Boundary Realignment and State-Level Confidence Weighting
H Liu, Y Chen, R Ding, C Pang – … of the 2nd International Conference on …, 2018 – dl.acm.org
… retrieval; Multimedia and multimodal retrieval; Speech/audio search; • Computing methodologies ? Artificial intelligence; Natural language … One is the large vocabulary continuous speech recognition (LVCSR) based KWS, which commonly assumes offline processing of audio …

A Survey on Hand Gesture Using Imageprocessing
BR Sunny – 2018 – ijsrst.com
… an isolated word digit recognition task. This work is a preliminary investigation of large scale modeling techniques to be applied to large vocabulary continuous speech recognition. Increases in computational power, storage …

A multimodal analytics platform for journalists analysing large-scale, heterogeneous multilingual and multimedia content
S Vrochidis, A Moumtzidou, I Gialampoukidis… – Frontiers in Robotics …, 2018 – frontiersin.org
Analysts and journalists face the problem of having to deal with very large, heterogeneous and multilingual data volumes that need to be analyzed, understood and aggregated. Huge savings could be made in terms of time, labor and costs by automating and simplifying their editorial …

Reducing Number of Parameters for Identifying Breast Cancer
R Bachate, S Dumbare, G Ladhe, S Binawade… – INTERNATIONAL …, 2018 – ijasret.com
… 2.2 Machine Leaning Machine learning is a type of artificial intelligence that allow systems to learn automatically and improve from experience … [6]. R. Haeb-Umbach and H. Ney, Linear discriminant analysis for improved large vocabulary continuous speech recognition, in: IEEE …

pplying hybrid “CD-CNN-HMM” model for keywords spotting in continuous speech
H DRIDI, O Kais – … on Electrical Sciences and Technologies in …, 2018 – ieeexplore.ieee.org
… II. AN OVERVIEW OF CONVOLUTIONAL NEURAL NETWORKS Recently, with the tremendous success of artificial intelligence techniques and by introducing the Deep Neural Networks (DNNs), it has been crucial improvements in many automatic speech recognition tasks …

End-to-End Speech Command Recognition with Capsule Network
J Bae, DS Kim – Proc. Interspeech 2018, 2018 – isca-speech.org
… Z. Ma, Y. He, J. Wei, P. Wu, W. Situ, S. Li, and Y. Zhang, “Deep lstm for large vocabulary continuous speech recognition,” arXiv preprint … of train- ing deep feedforward neural networks,” in Proceedings of the thirteenth international conference on artificial intelligence and statistics …

Building Blocks of Assistant Based Speech Recognition for Air Traffic Management Applications
M Kleinert, H Helmke, H Ehr, C Kern, D Klakow… – 2018 – publications.idiap.ch
… A. Speech Recognition Applications in ATM Artificial intelligence (AI) and in particular machine learn- ing (ML) applications have made a significant progress in the last few years, enabling computers to make a series of major breakthroughs that were previously impossible [8 …

Investigation of Optimal Number of Gaussian Mixtures for Hindi Language ASR
P Tripathi – 2018 – 14.139.60.7
… Linear Prediction Coefficient/Linear Predictive Coding Linear Predictive Cepstral Coefficient Localized Spectro-Temporal Feature Large Vocabulary Continuous Speech Recognition Multi Band Minimum Classification Error Mel Filter Bank Mel Frequency Cepstral Coefficient …

A Real-Time Convolutional Approach To Speech Emotion Recognition
J Engelbart – 2018 – pdfs.semanticscholar.org
Page 1. MSc Artificial Intelligence Master Thesis A Real-Time Convolutional Approach To Speech Emotion Recognition by Jorn Engelbart 11331712 … for audio analyses. 2.2.1 Pipeline Multiple studies in the field of Artificial Intelligence have investigated the subject of SER …

Offline to online speaker adaptation for real-time deep neural network based LVCSR systems
Y Long, Y Li, B Zhang – Multimedia Tools and Applications, 2018 – Springer
… stable offline iVec- tor. Furthermore, different iVector estimation techniques are also reviewed and investigated for speaker adaptation in large vocabulary continuous speech recognition (LVCSR) tasks. Experimental results on …

Mixed-Bandwidth Cross-Channel Speech Recognition via Joint Optimization of DNN-Based Bandwidth Expansion and Acoustic Modeling
J Gao, J Du, E Chen – IEEE/ACM Transactions on Audio …, 2018 – ieeexplore.ieee.org
Page 1. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 27, NO. 3, MARCH 2019 559 Mixed-Bandwidth Cross-Channel Speech Recognition via Joint Optimization of DNN-Based Bandwidth Expansion and Acoustic Modeling …

Neuronale Netze in der automatischen Spracherkennung-ein Paradigmenwechsel?
R Schlüter, P Doetsch, P Golik, M Kitza, T Menne, K Irie… – www-i6.informatik.rwth-aachen.de
Page 1. Neuronale Netze in der automatischen Spracherkennung – ein Paradigmenwechsel? Neural Networks in Automatic Speech Recognition – a Paradigm Change? R. Schlüter, P. Doetsch, P. Golik, M. Kitza, T. Menne, K. Irie, Z. Tüske, A. Zeyer …

Speech, Prosody, and Machines: Nine Challenges for Prosody Research
A Rosenberg – Proceedings of the International Conference on …, 2018 – isca-speech.org
Page 1. Speech, Prosody, and Machines: Nine Challenges for Prosody Research Andrew Rosenberg IBM Research Yorktown Heights, NY, USA amrosenb@us.ibm. com Abstract Speech technology is becoming commonplace …

Introducing a virtual assistant to the lab: A voice user Interface for the intuitive control of laboratory instruments
J Austerjost, M Porr, N Riedel, D Geier… – SLAS …, 2018 – journals.sagepub.com
The introduction of smart virtual assistants (VAs) and corresponding smart devices brought a new degree of freedom to our everyday lives. Voice-controlled and I…

Unsupervised Feature Learning in Time Series Prediction Using Continuous Deep Belief Network
Q Chen, G Pan, M Yu, J Wang – 2018 – preprints.org
Page 1. Article 1 Unsupervised Feature Learning in Time Series 2 Prediction Using Continuous Deep Belief Network 3 Qili Chen 1*, Guangyuan PAN2*, Ming Yu3, Jiuhe Wang 1 4 1 Automation college at Beijing information …

Overview of Phoneme-based Video Indexing for Audio Transcript Reconstruction
C Leon-Barth, M Elvir, RF DeMara, A Gonzalez – cal.ucf.edu
… ASR speech recognition systems mostly depend on the trained corpus, scenario and the environment. The best systems use Large Vocabulary Continuous Speech Recognition (LVCSR) … In Artificial Intelligence for Applications, 1993. Proceedings., Ninth Conference on (pp …

An Improved Deep Belief Network Model for Road Safety Analyses
G Pan, L Fu, L Thakali, M Muresan, M Yu – arXiv preprint arXiv:1812.07410, 2018 – arxiv.org
Page 1. An Improved Deep Belief Network Model for Road Safety Analyses Guangyuan Pan1, Liping Fu*12, Lalita Thakali1, Matthew Muresan1, Ming Yu3 1 Department of Civil & Environmental Engineering, University of Waterloo …

Generalized Baum-Welch and Viterbi Algorithms Based on the Direct Dependency among Observations
VR Tabar, D Plewczynski, H Fathipour – JIRSS-JOURNAL OF THE …, 2018 – jirss.irstat.ir
Page 1. JIRSS (2018) Vol. 17, No. 02, pp 205-225 DOI: 10.29252/jirss.17.2.10 Generalized Baum-Welch and Viterbi Algorithms Based on the Direct Dependency among Observations Vahid Rezaei Tabar 1, Dariusz Plewczynski2,3 and Hosna Fathipour 4 …

Generalized Baum-Welch and Viterbi Algorithms Based on the Direct Dependency among Observations
V Rezaei Tabar, D Plewczynski… – Journal of The Iranian …, 2018 – jirss.irstat.ir
Page 1. JIRSS (2018) Vol. 17, No. 02, pp 205-225 DOI: 10.29252/jirss.17.2.10 Generalized Baum-Welch and Viterbi Algorithms Based on the Direct Dependency among Observations Vahid Rezaei Tabar 1, Dariusz Plewczynski2,3 and Hosna Fathipour 4 …

Deep belief networks and cortical algorithms: A comparative study for supervised classification
Y Rizk, N Hajj, N Mitri, M Awad – Applied Computing and Informatics, 2018 – Elsevier
… been previously possible. This has led to the inception of deep architectures that capitalize on recent advances in artificial intelligence and insights from cognitive neuroscience to provide better learning solutions. In this paper …

Recent advances in convolutional neural networks
J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai… – Pattern Recognition, 2018 – Elsevier

Extraction of Prosody for Automatic Speaker, Language, Emotion and Speech Recognition
L Mary – 2018 – books.google.com
Page 1. SPRINGER BRIEFS IN ELECTRICAL AND COMPUTER ENGINEERING SPEECH TECHNOLOGY Leena Mary Extraction of Prosody for Automatic Speaker, Language, Emotion and Speech Recognition Second Edition 123 Page 2 …

Applied Computing and Informatics
Y Rizk, N Hajj, N Mitri, M Awad – 2018 – researchgate.net
… been previously possible. This has led to the inception of deep architectures that capitalize on recent advances in artificial intelligence and insights from cognitive neuroscience to provide better learning solutions. In this paper …

Sequence to sequence learning and its speech applications
Y Zhang – 2018 – papyrus.bib.umontreal.ca
Page 1. Université de Montréal Sequence to Sequence Learning and Its Speech Applications par Ying Zhang Département d’informatique et de recherche opérationnelle Faculté des arts et des sciences Mémoire présenté `a …

Classification of rocks radionuclide data using machine learning techniques
AR Khan, AA Mir, S Saeed, M Rafique, KM Asim… – Acta Geophysica, 2018 – Springer
… 861–874CrossRefGoogle Scholar. Haeb-Umbach R, Ney H (1992) Linear discriminant analysis for improved large vocabulary continuous speech recognition … CrossRefGoogle Scholar. Michalski RS, Carbonell JG et al (2013) Machine learning: an artificial intelligence approach …

Smart remote-controller designed with combining speech-recognition microprocessor and wireless sensor networks
JY Bian, CL Hsu – Microsystem Technologies, 2018 – Springer
… functionality by designing terminology discovery strategies that could allow the discovery of extra-vocabu- lary (OOV) terms in large vocabulary continuous speech recognition (LVCSR) systems … Nowadays, technology has developed toward the stage of AI (artificial intelligence) …

A Study on Landmark Verification of Mandarin Alveolar-palatal Consonants
Z Wang, Q Zhang, J Zhang, Y Xie – 2018 11th International …, 2018 – ieeexplore.ieee.org
… Data preparation Chinese National Hi-Tech project 863[18] for Mandarin large vocabulary continuous speech recognition (LVCSR) system is adopted for … of detecting English fricative based on energy spectrum entropy [J]. Pattern recognition and artificial intelligence, 2014, 27(6 …

Re-ranking spoken term detection with acoustic exemplars of keywords
H Xu, X Xiao, NF Chen, ES Chng, H Li – Speech Communication, 2018 – Elsevier
… In the case of large vocabulary continuous speech recognition (LVCSR), most of the target keywords are likely covered by the system’s vocabulary and eventual out-of-vocabulary (OOV) keywords can be dealt with using a subword based system …

Improved acoustic modelling for automatic literacy assessment of children
M Nicolao, M Sanders, T Hain – Proceedings of Interspeech …, 2018 – eprints.whiterose.ac.uk
… 1–8. [20] PC Woodland, JJ Odell, V. Valtchev, and SJ Young, “Large vocabulary continuous speech recognition using HTK,” in ICASSP … transducer speech decoder,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture …

Discriminant Projection Representation-based Classification for Vision Recognition
Q Feng, Y Zhou – … -Second AAAI Conference on Artificial Intelligence, 2018 – aaai.org
… are Copyright c 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. known … methods. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) 2208 Page 2. Notation …

RVR & JC COLLEGE OF ENGINEERING:: GUNTUR
M Tech – it.rvrjcce.ac.in
… 3. Deepak Khemani “Artificial Intelligence”, Tata McGraw Hill Education 2013 … Large Vocabulary Continuous Speech Recognition: Introduction, Subword Speech units, Subword Unit Models Based on HMMs, Training of Subword Units, Language Models for Large Vocabulary …

Implementation of a spoken language system
J Perez Guijarro – openaccess.uoc.edu
… Titulació: Grau d’Enginyeria Informàtica Àrea del Treball Final: Artificial Intelligence Idioma del treball: English … Continuous Speech Recognition Julius Engine Julius Engine is a large vocabulary continuous speech recognition (LVCSR) decoder software based on …

Combining Speech and Speaker Recognition-A Joint Modeling Approach
H Su – 2018 – escholarship.org
… Automatic speech recognition is an artificial intelligence task that requires trans- lation of spoken language into text automatically … gone from single speaker to speaker independent systems, and also from isolated word system to large vocabulary continuous speech recognition …

Noise Robust Automatic Speech Recognition Based on Spectro-Temporal Techniques
G Kovács – 2018 – doktori.bibl.u-szeged.hu
… In 2015, I was in the audience of a roundtable discussion on Artificial Intelligence in Leuven … FFNN Feature Finding Neural Net HAS-RGAI Hungarian Academy of Sciences Research Group on Artificial Intelligence HMM Hidden Markov Model HSR Human Speech Recognition …

Touch-Supported Voice Recording to Facilitate Forced Alignment of Text and Speech in an E-Reading Interface
B Axtell, C Munteanu, C Demmans Epp, Y Aly… – … on Intelligent User …, 2018 – dl.acm.org
… improve upon them. Zhang et al [44] found that their system for scoring reading quality avoided known disadvantages of forced alignment by switching to large vocabulary continuous speech recognition (LVCSR). LVCSR was …

The Role of Informational and Human Resource Capabilities for Enabling Diffusion of Big Data and Predictive Analytics and Ensuing Performance
D Mishra, Z Luo, BT Hazen – Innovation and Supply Chain Management …, 2018 – Springer
… can be made in the fields of medicine, commerce and national security by utilizing artificial intelligence tools to … The transcript-based approach, also known as large vocabulary continuous speech recognition (LVCSR), and the phonetic-based approach are the commonly used …

Flat-start single-stage discriminatively trained HMM-based models for ASR
H Hadian, H Sameti, D Povey… – IEEE/ACM Transactions …, 2018 – ieeexplore.ieee.org
… CI models have a significantly smaller number of states and can simply be used without state tying. However, for large vocabulary continuous speech recognition, CD models have proved to outperform CI models remarkably …

Improved initialization for the multi layer perceptron
AV Mainkar – 2018 – rc.library.uta.edu
… ie, progressively improve performance on a specific task) with data, without being explicitly programmed [1]. Machine learning is a subfield of artificial intelligence (AI). The goal of machine learning generally is to understand …

Safety First: Conversational Agents for Health Care
T Bickmore, H Trinh, R Asadi, S Olafsson – Studies in Conversational UX …, 2018 – Springer
Automated dialogue systems represent a promising approach for health care promotion, thanks to their ability to emulate the experience of face-to-face interactions between health providers and…

New transformed features generated by deep bottleneck extractor and a GMM–UBM classifier for speaker age and gender classification
AA Mallouh, Z Qawaqneh, BD Barkana – Neural Computing and …, 2018 – Springer
… object recognition [32, 33]. The artificial neural network (ANN) is a subfield of artificial intelligence, and it is used as a classifier. The structure of an NN is composed of input layer, one hidden layer, and output layer. On the other …

A Call Center Agent Productivity Modeling Using Discriminative Approaches
A Ahmed, Y Hifny, S Toral, K Shaalan – Intelligent Natural Language …, 2018 – Springer
In this article, we present a novel framework for measuring productivity of customer service representative (CSR) in real estate call centers. The framework proposes a binary classification task for…

Analyses of example sentences collected by conversation for example-based non-task-oriented dialog system
Y Kageyama, Y Chiba, T Nose, A Ito – IAENG International Journal of …, 2018 – iaeng.org
Page 1. Analyses of Example Sentences Collected by Conversation for Example-Based Non-Task-Oriented Dialog System Yukiko Kageyama, Yuya Chiba, Takashi Nose, and Akinori Ito, Member, IAENG Abstract—Designing …

Automatic quality estimation for speech translation using joint ASR and MT features
NT Le, B Lecouteux, L Besacier – Machine Translation, 2018 – Springer
This paper addresses the automatic quality estimation of spoken language translation (SLT). This relatively new task is defined and formalized as a sequence-labeling problem where each word in the…

A Dynamic Neural Network Architecture with Immunology Inspired Optimization for Weather Data Forecasting
AJ Hussain, P Liatsis, M Khalaf, H Tawfik, H Al-Asker – Big data research, 2018 – Elsevier
… the area of weather forecasting. Expert systems and various Artificial Intelligence (AI) techniques have been used and developed to improve decision support tools, eg, in flood management [40]. Machine Learning models (ML …

Speaker-adapted confidence measures for ASR using deep bidirectional recurrent neural networks
MA Del-Agua, A Gimenez, A Sanchis… – … on Audio, Speech …, 2018 – ieeexplore.ieee.org
Page 1. 1198 IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 26, NO. 7, JULY 2018 Speaker-Adapted Confidence Measures for ASR Using Deep Bidirectional Recurrent Neural Networks …

Institute of Communications Engineering Staff
M Bossert, R Fischer, W Minker, UC Fiebig… – Journal on Multimodal …, 2018 – uni-ulm.de
… A. Pugachev, O. Akhtiamov, A. Karpov and W. Minker Deep Learning for Acoustic Addressee Detection in Spoken Dialogue Systems Proceedings of the Conference on Artificial Intelligence and Natural Language (AINL 2017), Springer, Saint Petersburg, Russia, 2017 Bibtex …

Design of an enhanced speech authentication system over mobile devices
MU Anwar – 2018 – lib.buet.ac.bd
… LM: Language Model LSTM: Long Short-Term-Memory (recurrent neural network) LVCSR: Large Vocabulary Continuous Speech Recognition LVSR: Large Vocabulary Speech Recognition Mah: Mahalanobis MDP: Markov Decision Process …

Social networking data analysis tools & challenges
A Sapountzi, KE Psannis – Future Generation Computer Systems, 2018 – Elsevier
… Social network analytics and content mining approaches follow the interdisciplinary principles of Artificial Intelligence (AI), Statistics … Audio or speech analysis follow the Large-Vocabulary Continuous Speech Recognition or the phonetic-based approach to extract information …

On the derivational entropy of left-to-right probabilistic finite-state automata and hidden markov models
JA Sánchez, MA Rocha, V Romero… – Computational …, 2018 – MIT Press
Create a new account. Email. Returning user. Can’t sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …

Generalized Extraction and Classification of Span-Level Clinical Phrases
T Baldwin, Y Guo, VV Mukherjee… – AMIA Annual …, 2018 – ncbi.nlm.nih.gov
… AAAI Conference on Artificial Intelligence [Internet]; 2017. Available from: https://aaai.org/ ocs/index.php/AAAI/AAAI17/paper/view/14794. 38. Zweig G, Nguyen P. 2009. A segmental CRF approach to large vocabulary continuous speech recognition …

Backpropagation with Photonics
P Antonik – Application of FPGA to Real?Time Machine Learning, 2018 – Springer
This chapter presents an experiment that was not originally planned as part of my thesis. The project was set up when Michiel Hermans joined our team in 2015 with an idea of implementing the…

Exploiting temporal context in speech technologies using LSTM recurrent neural networks
R Zazo Candil – 2018 – repositorio.uam.es
… Inspired by the human brain and following the previous definition of Artificial Intelligence, the research community … Nowadays, large vocabulary continuous speech recognition (LVCSR) systems are becoming increasingly relevant for industry, leading the technological trend …

Developing a voice-controlled home-assisting system for KTH Live-in Labs
S Maloo – 2018 – diva-portal.org
… 11 Page 12. 1.1. OUTLINE CHAPTER1. INTRODUCTION cepts and research fields, like Big Data, IoT, Artificial Intelligence and others. Further, automation is evolving to new application domains like smart cities, transport, agriculture, and intelligent health …

Localising and Reconstructing Drill Holes in 3D Objects using Machine Learning
V Ståhl – 2018 – diva-portal.org
… LVCSR large vocabulary continuous speech recognition … Leading the new artificial intelligence wave are various deep neural network (DNN) algorithms, as DNNs are proven to be a powerful approach when classifying abstract properties of both sounds and images [23] …

Auditory Classification of Carsby Deep Neural Networks
J Karlsson – 2018 – diva-portal.org
… LVCSR large vocabulary continuous speech recognition … Leading the new artificial intelligence wave are various deep neural network (DNN) algorithms, as DNNs are proven to be a powerful approach when classifying abstract properties of both sounds and images [23] …

Accessible Human-Error Interactions in AI Applications for the Blind
J Hong – Proceedings of the 2018 ACM International Joint …, 2018 – cs.umd.edu
… In Proceedings of the 2017 International Conference on Artificial Intelligence, Automation and Control Technologies (AIACT ’17). ACM, New York, NY, USA, Article 22, 6 pages … 1999. Patterns of entry and correction in large vocabulary continuous speech recognition systems …

Deep Domain Adaptation to Predict Freezing of Gait in Patients with Parkinson’s Disease
VG Torvi, A Bhattacharya… – 2018 17th IEEE …, 2018 – ieeexplore.ieee.org
… Deep, convolutional, and recurrent models for human activity recognition using wearables,” in International Joint Conference on Artificial Intelligence, 2016 … Y. He, J. Wei, P. Wu, W. Situ, S. Li, and Y. Zhang, “Deep lstm for large vocabulary continuous speech recognition,” in arXiv …

Conversational Speech Understanding in highly Naturalistic Audio Streams
L Kaushik – 2018 – utd-ir.tdl.org
… speech understanding in highly naturalistic audio environments, namely: (i) A novel deep learning based application for Large Vocabulary Continuous Speech Recognition (LVCSR), (ii) Convolutional Neural Networks (CNN) and Curriculum learning based novel long term …

Unifying Data, Model and Hybrid Parallelism in Deep Learning via Tensor Tiling
M Wang, C Huang, J Li – arXiv preprint arXiv:1805.04170, 2018 – arxiv.org
Page 1. Unifying Data, Model and Hybrid Parallelism in Deep Learning via Tensor Tiling Minjie Wang Chien-chin Huang Jinyang Li New York University Abstract Deep learning systems have become vital tools across many …

Joint Estimation of Reverberation Time and Early-To-Late Reverberation Ratio From Single-Channel Speech Signals
F Xiong, S Goetze, B Kollmeier… – IEEE/ACM Transactions …, 2018 – ieeexplore.ieee.org
Page 1. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 27, NO. 2, FEBRUARY 2019 255 Joint Estimation of Reverberation Time and Early-To-Late Reverberation Ratio From Single-Channel Speech Signals …

Deep learning with particle filter for person re-identification
G Choe, C Choe, T Wang, H So, C Nam… – Multimedia Tools and …, 2018 – Springer
Page 1. Multimed Tools Appl https://doi.org/10.1007/s11042-018-6415-5 Deep learning with particle filter for person re-identification Gwangmin Choe1 ·Chunhwa Choe1 ·Tianjiang Wang2 · Hyoson So1 ·Cholman Nam3 ·Caihong Yuan2 …

Calibrated Prediction Intervals for Neural Network Regressors
G Keren, N Cummins, B Schuller – IEEE Access, 2018 – ieeexplore.ieee.org
Page 1. 2169-3536 (c) 2018 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 …

Data-Driven Fault Detection of Electrical Machine
Z Xu, J Hu, C Hu, S Nadarajan, C Goh… – … Conference on Control …, 2018 – ieeexplore.ieee.org
… [12] A. Siddique, G. Yadava, and B. Singh, Applications of artificial intelligence techniques for induction machine stator fault diagnostics … [14] G. Zweig and M. Picheny, Advances in large vocabulary continuous speech recognition, Advances in Computers, 60, 2004, 249-291 …

Literature Survey and Datasets
S Poria, A Hussain, E Cambria – Multimodal Sentiment Analysis, 2018 – Springer
In this chapter we present the literature on unimodal and multimodal approaches to sentiment analysis and emotion recognition. As discussed in the Sect. 2.1, both of these topics can be brought…

AlignTool: The automatic temporal alignment of spoken utterances in German, Dutch, and British English for psycholinguistic purposes
L Schillingmann, J Ernst, V Keite, B Wrede… – Behavior research …, 2018 – Springer
In language production research, the latency with which speakers produce a spoken response to a stimulus and the onset and offset times of words in longer utterances are key dependent variables….

Multilingual phrase sampling for text entry evaluations
M Franco-Salvador, LA Leiva – International Journal of Human-Computer …, 2018 – Elsevier
Skip to main content …

Phase and reverberation aware DNN for distant-talking speech enhancement
Z Oo, L Wang, K Phapatanaburi, M Iwahashi… – Multimedia Tools and …, 2018 – Springer
Page 1. Phase and reverberation aware DNN for distant-talking speech enhancement Zeyan Oo1 & Longbiao Wang2 & Khomdet Phapatanaburi1 & Masahiro Iwahashi1 & Seiichi Nakagawa3 & Jianwu Dang2,4 Received: 23 …

Transcribing Real-Valued Sequences With Deep Neural Networks
A Hannun – 2018 – stacks.stanford.edu
… 1Classifying problems which can be solved by deep learning in this way is due to Andrew Ng in eg https://hbr.org/2016/11/what-artificial-intelligence-can-and-cant-do-right-now. Page 19 … form first-pass large vocabulary continuous speech recognition using only a neu …

Automating the anonymisation of textual corpora
L García Sardiña – 2018 – addi.ehu.eus
… Final Thesis September 2018 Departments: Computer Systems and Languages, Computational Architectures and Technologies, Computational Science and Artificial Intelligence, Basque Language and Communication, Communications Engineer. Page 2 …

MindID: Person identification from brain waves through attention-based recurrent neural network
X Zhang, L Yao, SS Kanhere, Y Liu, T Gu… – Proceedings of the ACM …, 2018 – dl.acm.org
… [2] attempt to build a Large Vocabulary Continuous Speech Recognition (LVCSR) Systems using attention-based RNN and demonstrate that their approach, compared with traditional methods, requires fewer training stages, less auxiliary data, and less domain expertise …

Sentence Classification for Morphologically Rich Languages
T Madhuri – 2018 – web2py.iiit.ac.in
Page 1. Sentence Classification for Morphologically Rich Languages Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computational Linguistics by Research by Tummalapalli Madhuri 201325191 …

??-Norm Heteroscedastic Discriminant Analysis Under Mixture of Gaussian Distributions
W Zheng, C Lu, Z Lin, T Zhang, Z Cui… – IEEE transactions on …, 2018 – 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 NEURAL NETWORKS AND LEARNING SYSTEMS 1 1-Norm Heteroscedastic Discriminant Analysis …

Development of Voice User Interfaces and their Impact on the User Experience of Mobile Applications
KA Münch – stl.htwsaar.de
… In combination with recent achievements in technology and especially in the field of artificial intelligence, VUIs have become more usable … Especially through the progress in the research regarding artificial intelligence the quality of NLU was highly increased …

Tutoring System for Smartphone Text Input for Older Adults using Statistical Stumble Detection
T Hagiya – 2018 – repository.kulib.kyoto-u.ac.jp
Page 1. Title Tutoring System for Smartphone Text Input for Older Adults using Statistical Stumble Detection( Dissertation_?? ) Author(s) Hagiya, Toshiyuki Citation Kyoto University (????) Issue Date 2018-03-26 URL https://doi.org/10.14989/doctor.k21207 Right …

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