Lemmatization & Dialog Systems

Notes:

Lemmatization is a process in natural language processing (NLP) that involves reducing a word to its base form, or lemma. This is typically done by removing inflections (such as tense and number) from the word, so that it can be more easily analyzed and compared to other words.

For example, the lemma of the word “running” is “run,” and the lemma of the word “jumps” is “jump.” By lemmatizing these words, it is possible to group them together and treat them as a single item, even though they have different inflections.

Lemmatization is often used in NLP tasks such as text classification, language translation, and information retrieval, as it can help to standardize the representation of words and make it easier to compare them to one another. It is also sometimes used in spelling correction, as it can help to identify the correct base form of a word even if it is spelled incorrectly. Overall, lemmatization is a useful tool for simplifying and standardizing the representation of language data in NLP tasks.

There are several ways in which lemmatizers can be used in dialog systems:

Text classification: Lemmatizers can be used to pre-process text data in order to improve the accuracy of text classification models. By reducing words to their base form, it is possible to more accurately identify the overall content and meaning of a text, which can help the model make more accurate predictions.
Language translation: Lemmatizers can be used to standardize the representation of language data in order to improve the accuracy of translation systems. By reducing words to their base form, it is easier to identify the correct translation for a given word, even if it is inflected differently in the source and target languages.
Information retrieval: Lemmatizers can be used to improve the effectiveness of search engines and other information retrieval systems by standardizing the representation of language data. By reducing words to their base form, it is easier to identify relevant documents and results based on the user’s query.

Lemmatisation: The process of reducing a word to its base form, or lemma, by removing inflections such as tense and number. This is typically done in order to more easily analyze and compare words.

Lemmatize: To reduce a word to its base form through the process of lemmatization.

Lemmatized: The past tense of “lemmatize,” used to describe a word that has been reduced to its base form through the process of lemmatization.

Lemmatizer: A software tool or algorithm that is used to perform the process of lemmatization.

Lemmatizing: The present participle of “lemmatize,” used to describe the act of reducing a word to its base form through the process of lemmatization.

Wikipedia:

Intent Detection System Based on Word Embeddings
K Balodis, D Deksne – International Conference on Artificial Intelligence …, 2018 – Springer
… In this way only for 236 utterances were classified, because others were not in the domain of the dialog system … The words in utterances are either lemmatized or not … The setting we use is the original sentence without lemmatization or stopword removal …

Improving dialogue act classification for spontaneous arabic speech and instant messages at utterance level
AR Elmadany, S Abdou, M Gheith – arXiv preprint arXiv:1806.00522, 2018 – arxiv.org
… Therefore, Dialogue act recognition is considered an important component of most spoken dialogue systems … Conditional Random Fields (CRF) – lexical normalization – Morphological analysis and lemmatization – Annotate word by word F-Measure 0.8652 …

Lemmatization for Ancient Languages: Rules or Neural Networks?
O Dereza – Conference on Artificial Intelligence and Natural …, 2018 – Springer
… that represent lexical context was successfully implemented by [25] to lemmatise Middle Dutch data … Shavrina, T., Sorokin, A.: Modeling advanced lemmatization for Russian language using TnT-Russian … Souvay, G., Pierrel, JM: Lemmatisation des mots en Moyen Français …

Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification
T Mairittha, T Okita, S Inoue – Proceedings of the 2018 ACM International …, 2018 – dl.acm.org
… This paper focuses on a different aspect of intent. When the Yes/No type of question arises, the dialogue systems need to transit either to Yes or No states to progress the conver- sation … Then use both stemming and lemmatization to re- duce inflectional forms …

The CSU-K Rule-Based System for the 2nd Edition Spoken CALL Shared Task
D Jülg, M Kunstek, C Freimoser, K Berkling… – Proc. Interspeech …, 2018 – researchgate.net
… 3.5.2. Lemmatization … Lemmatizing is used to help fo- cus on the semantics of the word by mapping a large series of related words into the same token representation given by the stem … Again the lemmatized version of the word is used for the above mentioned reasons …

Review on Chatbot Design Techniques in Speech Conversation Systems
R Sharma, M Patel – iarjset.com
… earlier work is done through the NLTK library which performs the lemmatization, character tokenization … works by taking strings as input, removing the noise, stemming and lemmatizing for obtaining … or the emotions or expressions behind it by building a dialogue system just like …

A Review on Artificial Intelligence Decision Making Support System
SS Harnish Shah – j-asc.com
… Moreover, QA can be used to develop dialogue systems and chatbots … In NLP, we call finding this process lemmatization — figuring out the most basic form or lemma of each word in the sentence … We can also lemmatize verbs by finding their root, unconjugated form …

Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation
N Ruiz, S Bangalore, J Chen – arXiv preprint arXiv:1805.04453, 2018 – arxiv.org
… the efficacy of bootstrapping a Span- ish intent classifier using the data and underlying models from an English spoken language dialog system … Of these types of errors, the most detrimental are substitutions of named entities, verbs, and nouns that are not lemmatization errors …

A Study on Dialog Act Recognition using Character-Level Tokenization
E Ribeiro, R Ribeiro, DM de Matos – arXiv preprint arXiv:1805.07231, 2018 – arxiv.org
… Dialog act recognition is important in the context of a dialog system, since it re- veals the intention behind the words uttered by … 9425 .0015 Punctuated .7685 .0021 .7317 .0032 .9371 .0007 Capitalized + Punctuated .7673 .0025 .7314 .0040 .9548 .0004 Lemmatized .7521 .0027 …

An Ontology-Based Dialogue Management System for Banking and Finance Dialogue Systems
D Altinok – arXiv preprint arXiv:1804.04838, 2018 – arxiv.org
… Throughout our work, all 1 lemmatizing and morphological analysis tasks are done by DEMorphy. 2. Introduction Keeping dialogue state in conversational interfaces is a notoriously difficult task. Dialogue systems, also known as chatbots, virtual assistants and conversational …

Dialogue Act Classification in Reference Interview Using Convolutional Neural Network with Byte Pair Encoding
S Kawano, K Yoshino, Y Suzuki, S Nakamura – colips.org
… In dialog systems, it is impractical to define comprehensive behaviors of the system by rules … In addition, it is necessary to investigate the effectiveness of our method in other dia- logue domains, and compare the other approaches like lemmatization or word-CNN with pre-trained …

Supervised question answering system for technical support
S Shim, G Chodwadia, K Jain, C Patel… – … (CCWC), 2018 IEEE …, 2018 – ieeexplore.ieee.org
… This makes corpus a good resource for research into building dialogue System based on neural language that can make use of large amounts of unlabeled data … 4. Lemmatization – English language has different words for a verb as per the tense and plurality …

Alana v2: Entertaining and Informative Open-domain Social Dialogue using Ontologies and Entity Linking
AC Curry, I Papaioannou, A Suglia, S Agarwal… – dex-microsites-prod.s3.amazonaws …
… We rely on this intuition in order to develop a core module of our dialogue system called the Contextualised Linked Concept Generator … all noun phrases that appear in the user query, c) all 1,2,3-ngrams of the user utterance after removing stop words and applying lemmatisation …

A Dialogue Annotation Scheme for Weight Management Chat using the Trans-Theoretical Model of Health Behavior Change
R Manuvinakurike, S Bharadwaj, K Georgila – arXiv preprint arXiv …, 2018 – arxiv.org
… The POC annotations are designed to serve two purposes: (i) to equip future dialogue systems with the capability of providing suggestions based on the seeker’s current SOC; and (ii) to … We used the NLTK toolkit for lemmatization (Loper and Bird, 2002) and removed stop words …

Concorde: Morphological Agreement in Conversational Models
D Polykovskiy, D Soloviev… – Asian Conference on …, 2018 – proceedings.mlr.press
… Another technique to reduce the vocabulary size is to lemmatize all words … A conversational model on a lemmatized vocabulary with subsequent morphological agreement provide a … simple dictionary lookup, and modern context-sensitive approaches to lemmatization based on …

Fantom: A Crowdsourced Social Chatbot using an Evolving Dialog Graph
P Jonell, M Bystedt, FI Dogan, P Fallgren, J Ivarsson… – dex-microsites-prod.s3.amazonaws …
… therefore required a dialog manage- ment method capable of incorporating contributions from many authors, most of them without any knowledge about dialog systems or computer … Lemmatization, Tokenization and Part-of-speech SpaCy is used in order to extract these features …

Affective Neural Response Generation
N Asghar, P Poupart, J Hoey, X Jiang, L Mou – European Conference on …, 2018 – Springer
… 2 The dictionary we use consists of 13,915 lemmatized English words, each of which is rated on three traditionally accepted continuous … To the best of our knowledge, we are the first to introduce VAD to dialogue systems … end{aligned}$$. (2). where l(w) is the lemmatization of the …

A Bird’s-eye View of Language Processing Projects at the Romanian Academy
D Tufi?, C Dan – Proceedings of the Eleventh International Conference …, 2018 – aclweb.org
… contemporary language reference corpus, speech corpus, natural language dialogue systems, intelligent character … sentences, with almost 10 million tokens, MSD tagged, lemmatized, NERC marked … collection of pre-processing tools (tokenizer, tagger, lemmatizer, NER) trained …

Investigating linguistic pattern ordering in hierarchical natural language generation
SY Su, YN Chen – arXiv preprint arXiv:1809.07629, 2018 – arxiv.org
… is then fed into a natural language generation (NLG) module to construct a response utterance to the user [8, 9]. As a key component to a dialogue system, the goal … The data preprocessing includes trimming punctuation marks, lemmatization, and turning all words into lowercase …

Alquist: The Alexa Prize Socialbot
J Pichl, P Marek, J Konrád, M Matulík… – arXiv preprint arXiv …, 2018 – arxiv.org
… Several methods of implementation of the open domain dialogue system have been proposed … Currently, we use annotators for sentence splitting, tokenization, part of speech tagging, dependency parsing, lemmatisation, sentiment analysis and named entity recognition (NER) …

Towards Building a Virtual Assistant Health Coach
I Gupta, B Di Eugenio, B Ziebart, B Liu… – 2018 IEEE …, 2018 – ieeexplore.ieee.org
… classifier: sender of the message, message length, Part-Of-Speech tags, time difference between two messages, message contribution, and unigrams after lemmatization. IV … A reusable framework for health counseling dialogue systems based on a behavioral medicine ontology …

Artificial Intelligence and Natural Language
D Ustalov, A Filchenkov, L Pivovarova, J Žižka – Springer
… Its aim was to (a) bring together experts in the areas of natural language processing, speech technologies, dialogue systems, information retrieval, machine learning … 23 Yulia Badryzlova and Polina Panicheva Lemmatization for Ancient Languages: Rules or Neural Networks …

Next Utterance Ranking Based On Context Response Similarity
BEA Boussaha, N Hernandez, C Jacquin, E Morin – basma-b.github.io
… This category of dialogue systems is in the center of our interest in this work … The only preprocessing performed on the dataset is tokenization, lemmatization and stemming available as options when downloading the corpus …

Testing a Knowledge Inquiry System on Question Answering Tasks1
D Kyriaki, L ECKMAN… – Emerging Topics in …, 2018 – books.google.com
… An intelligent dialog system could respond to the question about Craig Adams with a clarification request about which sport, or by giving a possible … The verb is then lemmatized and, by utilizing Word- Net’s synsets, the most probable morphological variant of the verb as a noun …

Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations
E Ribeiro, R Ribeiro, DM de Matos – arXiv preprint arXiv:1807.08587, 2018 – arxiv.org
… By combining the best approaches for each aspect, we achieve results that surpass the previous state-of-the-art in a dialog system context and similar to human-level in an annotation context on the Switchboard Dialog Act Corpus, which is the most explored corpus for the task …

Testing a Knowledge Inquiry System on Question Answering Tasks
KD Zafeiroudi, L Eckman… – Joint Proceedings of …, 2018 – personal.psu.edu
… other work proposes interaction with the user to help users reformulate or clarify the question [1,9]. An intelligent dialog system could respond to the … The verb is then lemmatized and, by utilizing WordNet’s synsets, the most probable morphological variant of the verb as a noun is …

Using Lexical Alignment and Referring Ability to Address Data Sparsity in Situated Dialog Reference Resolution
T Shore, G Skantze – Proceedings of the 2018 Conference on Empirical …, 2018 – aclweb.org
… the training example for r is weighted by its com- plement set size, |R \ r| = 19. Initial experiments showed that lemmatization did not affect the performance on our dataset. Thus, each inflected lexical form is considered a unique word (ie, vocabulary item) …

Towards a music-language mapping
M Berlingerio, F Bonin – … of the Eleventh International Conference on …, 2018 – aclweb.org
… it presents several advantages: i) it is universal among dif- ferent languages; ii) it would facilitate the communication with dialogue system for persons with … As our aim was to map the entire language, we did not perform any filtering of stop words, nor applied lemmatization …

Neural Metaphor Detecting with CNN-LSTM Model
C Wu, F Wu, Y Chen, S Wu, Z Yuan… – Proceedings of the …, 2018 – aclweb.org
… (2016) to use the lemmatizing strategy. The first module in our model is a lemmatizer. This module is used to lemmatize the verbs in texts via a dictionary. The input is a text with a sequence of word, and output is the text with lemmatized words …

THU NGN at NAACL-2018 Metaphor Shared Task: Neural Metaphor Detecting with CNN-LSTM Model
C Wu, F Wu, Y Chen, S Wu, Z Yuan, Y Huang – researchgate.net
… sentiment information bet- ter, which is beneficial to many applications such as machine translation, dialog systems and senti … This layer is used to lemmatizing the verbs in texts. Since verbs with different forms can share the same lemmas, using the lemmatized verbs in texts can …

Semi-automatic Korean FrameNet Annotation over KAIST Treebank
Y Hahm, J Kim, S Kwon, KS Choi – Proceedings of the Eleventh …, 2018 – aclweb.org
… answering systems (Shen and Lapata, 2007, Hahm et al., 2016), information extraction (Surdeanu et al., 2003), and dialog systems (Chen et al … and then pruned specific morphemes, such as endings, josa (Korean postpositions), and affixes, as part of a lemmatization task in …

Character-based recurrent neural networks for morphological relational reasoning
R AI – clasp.gu.se
… to create systems for more complex language generation tasks, such as machine translation, automatic summarization, and dialog systems … RNNs, have been successfully applied in several types of prediction problems in morphology, including lemmatization, inflection and …

Artificial Intelligence and Natural Language: 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, Proceedings
D Ustalov – 2018 – books.google.com
… Its aim was to (a) bring together experts in the areas of natural language processing, speech technologies, dialogue systems, information retrieval … Tatiana Malygina and Ivan Drokin 11 23 Yulia Badryzlova and Polina Panicheva Lemmatization for Ancient Languages: Rules or …

Slovensko?ceský NLP workshop (SloNLP 2018)
J Genci, KPI TUKE, A Horák, FI MUNI, M Lopatková… – researchgate.net
… the workshop include automatic speech recognition, automatic natural language analysis and generation (morphology, syntax, semantics, etc.), dialogue systems, machine transla … Open-Source Tools for Morphology, Lemmatization, POS Tagging and Named Entity Recognition …

Isa: Intuit Smart Agent, A Neural-Based Agent-Assist Chatbot
Z Xue, TY Ko, N Yuchen, MKD Wu, CC Hsieh – oak.cs.ucla.edu
… The posts are first converted to lowercase before we perform stemming, lemmatization and tokenizing … In [13], the author uses multiple RNNs to construct a dialogue system: the first RNN is used to capture the user’s intent and the second one serves as a belief tracker to maintain …

Metis: A Scalable Natural-Language-Based Intelligent Personal Assistant for Maritime Services
N Gkanatsios, K Mermikli, S Katsikas – International Conference on …, 2018 – Springer
… First of all, mistyping and misspelling errors are common in dialog systems [27, 28], especially when most users are maritime employees from … Preprocessing includes tokenization, removal of unnecessary words (stop words, numbers and codewords) and lemmatization …

KG^ 2: Learning to Reason Science Exam Questions with Contextual Knowledge Graph Embeddings
Y Zhang, H Dai, K Toraman, L Song – arXiv preprint arXiv:1805.12393, 2018 – arxiv.org
… Graph embedding has provided the representational flexibility for neural models in many NLP tasks, such as dialog system [He et al., 2017], question answering [Zhang et al., 2017], link prediction [Bordes et al., 2013] and triple … Words in each graph node are lemmatized …

From Emoji Usage to Categorical Emoji Prediction
G Guibon, M Ochs, P Bellot – … and Intelligent Text …, 2018 – hal-amu.archives-ouvertes.fr
… Then we applied lemmatization to the words using NLTK … The methodology and resources can be used to recommend the emotion cat- egories to express by an embodied conversational agent or in general dialog system, such as trending chatbots …

Detecting and Tracking Ongoing Topics in Psychotherapeutic Conversations
S Consoli, A Härmä, R Helaoui, DR Recupero – 2018 – people.unica.it
… eling the human-human dialogues may serve as a guide for the devel- opment of artificial human-machine dialogue systems[6]. Topic … The steps of stemming and lemmatization have being neglected because they modified the forms of words changing the common base body of …

COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks
P Molino, H Zheng, YC Wang – Proceedings of the 24th ACM SIGKDD …, 2018 – dl.acm.org
… We refer to this task as contact type identification (similar to intent de- tection in dialogue systems research) … Tokenization Lowercasing Stopword removal Lemmatization LSA TF-IDF … Then, each word is lemmatized to convert different inflected forms into the same base form …

LIS at SemEval-2018 Task 2: Mixing Word Embeddings and Bag of Features for Multilingual Emoji Prediction
G Guibon, M Ochs, P Bellot – … of The 12th International Workshop on …, 2018 – aclweb.org
… Cleaning. To prepare the data we first cleaned tweets by removing trailing three dots, user men- tions and urls. Then we used Spacy6 to apply lemmatization and part-of-speech tagging (PoS) … Neural emoji recommendation in dialogue systems. arXiv preprint arXiv:1612.04609 …

Learning Prototypical Goal Activities for Locations
T Jiang, E Riloff – Proceedings of the 56th Annual Meeting of the …, 2018 – aclweb.org
… Recognizing goals is also critical for conversational dialogue systems … Exact Match judges aj to be a correct answer for li if (1) it exactly matches (af- ter lemmatization) any activity in li’s gold set, or (2) aj’s verb and noun both appear in li’s gold set, though possibly in different …

Chatbot using TensorFlow for small Businesses
R Singh, M Paste, N Shinde, H Patel… – 2018 Second …, 2018 – ieeexplore.ieee.org
… every day and are used in various practical applications which include customer service, information acquisition and dialogue systems … place where various functions are applied in form of pipeline which includes [2] Sentences -> Tokenization -> Lemmatization -> POS-tagging …

Adaptation of speech recognition vocabularies for improved transcription of YouTube videos
D Jouvet, D Langlois, M Menacer… – Journal of the …, 2018 – hal.archives-ouvertes.fr
… a probabilistic model for guessing base forms [4] in English and Finish, and a morpho- logical guesser for lemmatization in Arabic [5 … M. Sun, Y.-N. Chen, and AI Rudnicky, “Learning oov through semantic relatedness in spoken dialog systems,” in “Sixteenth Annual Conference of …

Accelerating Information Retrieval using Natural Language Processing
V Venkatesh – ijcstjournal.org
… Most of the NLP problems relate to classification except dialog systems that use natural language interaction that are built using modern … This process involves normalizing, aggregating and generalize the data by converting the data by parsing, stemming and lemmatization …

Relation Extraction of Medical Concepts Using Categorization and Sentiment Analysis
A Mondal, E Cambria, D Das, A Hussain… – Cognitive …, 2018 – Springer
… the medical concepts from the contexts using nltk package10 based tokenization, stem- ming, and lemmatization method with … community detection [18], manufacturing and supply chain applications [77], human communication comprehension [80] and dialogue systems [79], etc …

A Comparison of Features for the Automatic Labeling of Student Answers to Open-ended Questions
JG Alvarado, HA Ghavidel, A Zouaq, J Jovanovic… – pdfs.semanticscholar.org
… Student SAQ responses and associated metadata were collected through a dialog system … 3.2 Overall Approach Our general approach can be described as follows: 1. Data pre-processing: in this step, we perform lemmatization and removal of punctuation marks and stop words …

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume …
M Walker, H Ji, A Stent – Proceedings of the 2018 Conference of the …, 2018 – aclweb.org
Page 1. NAACL HLT 2018 The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Proceedings of the Conference Volume 1 (Long Papers) June 1-June 6, 2018 New Orleans, Louisiana Page 2 …

Automated essay scoring in applied games: Reducing the teacher bandwidth problem in online training
W Westera, M Dascalu, H Kurvers, S Ruseti… – Computers & …, 2018 – Elsevier
… A breakthrough failed to occur, however, because of the underestimated complexity of creating intelligent dialogue systems … word detection, based on the E-Lex lexicon (formerly named TST-lexicon) (CGN Consortium, 2017), stop words elimination and lemmatization using lists …

Domain Knowledge Driven Key Term Extraction for IT Services
P Mohapatra, Y Deng, A Gupta, G Dasgupta… – … Conference on Service …, 2018 – Springer
… Chunking, lemmatization, and POS tagging are done using the Spacy toolkit 5 . Candidate contiguous words are concatenated together to form candidate phrases … 3. Spacy’s lemmatizer is used to lemmatize the extracted and assigned key terms …

A hybrid approach for automatic extraction of bilingual multiword expressions from parallel corpora
N Semmar – Proceedings of the Eleventh International Conference …, 2018 – aclweb.org
… dictionary, it is preferable to lemmatize the parallel corpus before extracting and aligning MWEs. However, as some surface forms are similar to lemmas in English and French languages, we experimented the two possibilities. The parallel corpus has been lemmatized using the …

Exploring Distinct Features for Automatic Short Answer Grading
LB Galhardi… – Anais do Encontro …, 2018 – portaldeconteudo.sbc.org.br
… The first one is the Beetle dataset, with data collected from the Beetle II tutorial dialogue system [Dzikovska et al … It consists of case normalization, non-alphanumeric character removal, spelling correction, lemmatization and stopword removal. 4.1. Text statistics …

Data Collection for Dialogue System: A Startup Perspective
Y Kang, Y Zhang, JK Kummerfeld, L Tang… – Proceedings of the 2018 …, 2018 – aclweb.org
… We then describe in detail two crowdsourc- ing methods we use to collect intent classifica- tion data for our deployed dialogue system … in the data: we lowercase the text, remove punctuation, replace each digit with a common symbol, expand contractions, and lemmatize (us- ing …

Multilayer Corpus Studies
A Zeldes – 2018 – taylorfrancis.com
… However, part of speech tagging and lemmatization are intricately inter- twined in important ways: they both apply to the exact same units (‘word forms’ or, more precisely, tokens, see Chapter 2 ); determining one often constrains the other ( bent as a noun has a different lemma …

Extraction of Typical Client Requests from Bank Chat Logs
E Pronoza, A Pronoza, E Yagunova – Mexican International Conference …, 2018 – Springer
… client dialogues) which can be used by chat bot developers to train chat bot systems, however, such data often need cleaning and special preparation before they could be used as input for a dialogue system … Firstly, chat logs are lemmatized using MyStem 1 and then cleaned …

School of Computing
EA Chukwudozie – 2018 – minerva.leeds.ac.uk
… 18 2.5.1.1 Stemming 18 2.5.1.2 Lemmatisation 18 2.5.1.3 Word Embeddings 18 2.5.1.4 Part of Speech Tagging 22 … Page 6. – 6 – 2.6 The Bible in Perspective 24 2.7 Essentials of the Christian Faith 24 Chapter 3: Literature Review and The Dialogue System 27 3.0 Introduction 27 …

Multimodal Affective Computing to Enhance the User Experience of Educational Software Applications
JM Garcia-Garcia, VMR Penichet, MD Lozano… – Mobile Information …, 2018 – hindawi.com
… This processing involves tasks of tokenization, parsing and part-of-speech tagging, lemmatization, and stemming, among others … André, and N. Bee, “EmoVoice—a framework for online recognition of emotions from voice,” in Perception in Multimodal Dialogue Systems, E. André …

Enhancing Text Using Emotion Detected from EEG Signals
A Gupta, H Sahu, N Nanecha, P Kumar, PP Roy… – Journal of Grid …, 2018 – Springer
Page 1. J Grid Computing https://doi.org/10.1007/s10723-018-9462-2 Enhancing Text Using Emotion Detected from EEG Signals Akash Gupta · Harsh Sahu · Nihal Nanecha · Pradeep Kumar · Partha Pratim Roy · Victor Chang …

Natural Language Data Management and Interfaces
Y Li, D Rafiei – Synthesis Lectures on Data Management, 2018 – morganclaypool.com
… Second, the success of IBM’s Watson [Ferrucci, 2012] at Jeopardy and the emergence of natural language dialog systems such as Apple’s Siri, Google’s Home, Ama- zon’s Alexa, and Microsoft’s Cortana has further ignited the interest in natural language data analysis and …

Text Deconvolution Saliency (TDS): a deep tool box for linguistic analysis
L Vanni, M Ducoffe, D Mayaffre… – … Annual Meeting of …, 2018 – hal.archives-ouvertes.fr
… Notice that we do not use lemmatisation, as in Collobert and Weston (2008), thus the linguistic material which is automatically detected does not rely on any prior assumptions about the part of speech … 2017. A network- based end-to-end trainable task-oriented dialogue system …

Textual Deconvolution Saliency (TDS): a deep tool box for linguistic analysis
L Vanni, M Ducoffe, C Aguilar, F Precioso… – Proceedings of the 56th …, 2018 – aclweb.org
… This embedding is also finetuned by the model to to increase the accuracy. Notice that we do not use lemmatisation, as in Collobert and Weston (2008), thus the linguistic material which is automatically detected does not rely on any prior assumptions about the part of speech …

A Trustworthy, Responsible and Interpretable System to Handle Chit-Chat in Conversational Bots
P Agrawal, A Suri, T Menon – arXiv preprint arXiv:1811.07600, 2018 – arxiv.org
… Non-task and non-information oriented dialogue systems have been well studied (Vinyals and Le 2015) … Setting this threshold to a high value helps handle spelling mistakes, synonyms and lemmatised representa- tions of words …

Explorations into Deep Neural Models for Emotion Recognition
F Stojanovska, M Toshevska, S Gievska – International Conference on …, 2018 – Springer
… Part-of-speech tagging and lemmatization ie, extracting the base form of words conclude the preparation of data for the next stage of … D., Siddique, FB, Wu, CS, Wan, Y., Chan, RHY, Fung, P.: Real-time speech emotion and sentiment recognition for interactive dialogue systems …

Article in Press IJIMAI journal
AM Sandoval, J Díaz, LC Llanos, T Redondo – researchgate.net
Page 1. Article in Press IJIMAI journal – 1 – I. Introduction TERMINOLOGY is a branch of Applied Linguistics whose main goal is the creation of specialized or technical language. Thematic domains are by themselves the realm …

Linguistic and Gestural Adaptation
Z Hu – 2018 – escholarship.org
… I am very fortunate to have him. Several members of the Natural Language and Dialog Systems Lab have contributed … “Entrainment in Pedestrian Direction Giving: How many kinds of entrainment?” Workshop on Spoken Dialog Systems (IWSDS 2014), Napa, CA, USA, Jan …

Using reinforcement learning to learn how to play text-based games
M Zelinka – arXiv preprint arXiv:1801.01999, 2018 – arxiv.org
… is defined by sentences in natural language would allow many interesting real-world applications such as automatic optimisation of dialogue systems … In order to simplify the problem, techniques that reduce the vocabulary size such as stemming or lemmatisation are commonly …

Anomaly detection for short texts: Identifying whether your chatbot should switch from goal-oriented conversation to chit-chatting
A Bakarov, V Yadrintsev, I Sochenkov – International Conference on Digital …, 2018 – Springer
… Conversational agents (also called dialog systems) are systems that are able to converse with a human on a natural language, imitating dialogue with a real human being [4 … In our experiments the data was lemmatized and cleared from stop-words using NLTK stopword lists [21 …

On Finding the Relevant User Reviews for Advancing Conversational Faceted Search
E Dimitrakis, K Sgontzos, P Papadakos, Y Marketakis… – users.ics.forth.gr
… To the best of our knowledge though, the only work that combines spoken dialogue systems with faceted search is the … 2) Apply tokenization, removal of stop-words and punctuations, as well as lemma- tization (using Stanford CoreNLP [8]) both to the input question q and each …

Automatic Syntactic Analysis Based on Selectional Preferences
A Gelbukh, H Calvo – 2018 – Springer
Page 1. Studies in Computational Intelligence 765 Alexander Gelbukh Hiram Calvo Automatic Syntactic Analysis Based on Selectional Preferences Page 2. Studies in Computational Intelligence Volume 765 Series editor Janusz …

Natural Language Processing with Java: Techniques for building machine learning and neural network models for NLP
RM Reese, AS Bhatia – 2018 – books.google.com
… 66 Stemming with LingPipe 67 Using lemmatization 68 Using the StanfordLemmatizer class 68 Using lemmatization in OpenNLP … You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and other …

Classical and modern Arabic corpora
E Atwell – Diachronic Corpora, Genre, and Language Change, 2018 – books.google.com
… This collection of web-corpora includes the 176-million-word Arabic Internet Corpus, which we subsequently lemmatized using the SALMA … 2016. Usefulness, localizability, humanness, and language- benefit: Additional evaluation criteria for natural language dialogue systems …

Building Chatbots with Python
S Raj – Springer
… 37 Stemming and Lemmatization ….. 42 Named-Entity Recognition ….. 44 … 121 Understanding More on Rasa Core and Dialog System ….. 122 …

Deep Semantic Learning for Conversational Agents
M Morisio, M Mensio – 2018 – researchgate.net
Page 1. POLITECNICO DI TORINO Master of Science in Computer Engineering Master’s Thesis Deep Semantic Learning for Conversational Agents Supervisor Prof. Maurizio Morisio Candidate Martino Mensio Tutor Istituto Superiore Mario Boella Dr. Giuseppe Rizzo April 2018 …

Dynamic Extension of ASR Lexicon Using Wikipedia Data
B Abdullah, I Illina, D Fohr – IEEE Workshop on Spoken and …, 2018 – hal.archives-ouvertes.fr
… For training the DNN models, words in the multipurpose text corpus are lemmatized. Moreover, PNs and non-PNs occurring less than 5 times are discarded … [4] Ming Sun, A., Chen, Y. “Learning OOV through semantic relatedness in spoken dialog systems,” Interspeech, pp …

Using natural language processing for question answering in closed and open domains
M Latifi – 2018 – upcommons.upc.edu
Page 1. Universitat Politècnica de Catalunya BarcelonaTECH Department of Computer Science Using Natural Language Processing for Question Answering in Closed and Open Domains A DISSERTATION SUBMITTED TO …

A Supervised Approach To The Interpretation Of Imperative To-Do Lists
P Landes, B Di Eugenio – arXiv preprint arXiv:1806.07999, 2018 – arxiv.org
… 1Argument extraction can be considered equiva- lent to slot filling as defined in many spoken dialogue systems … We used the lemmatized form of the token for word count and cosine similarity features. Let cwa “ Countpw,aq be the count of word Page 7. Id Classifier Features …

Mapping natural language sentences to semantic graphs
X Peng, D Gildea – 2018 – urresearch.rochester.edu
… as a deeper understanding of natural language is increasingly important for user appli- cations such as information extraction, question answering and dialogue systems … tions such as question answering, information extraction, machine comprehension, and dialogue systems …

Towards Multilingual Neural Question Answering
E Loginova, S Varanasi, G Neumann – European Conference on Advances …, 2018 – Springer
… We use the texts from the second version, as they are not lemmatised and as such are better suited for machine translation, but keep … It is quite likely that the lack of research in the area may hinder the usage of more advanced dialogue systems and machine-human interfaces, if …

Using Polarity Classification Model to Assess Customer Attitudes: the Case of Russian E-Commerce Companies on Twitter
T Alexander – 2018 – dspace.spbu.ru
Page 1. Saint Petersburg State University Graduate School of Management Master in Management Program USING POLARITY CLASSIFICATION MODEL TO ASSESS CUSTOMERS’ ATTITUDES: THE CASE OF RUSSIAN E-COMMERCE COMPANIES ON TWITTER …

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…

Neural natural language inference models enhanced with external knowledge
Q Chen, X Zhu, ZH Ling, D Inkpen, S Wei – … of the 56th Annual Meeting of …, 2018 – aclweb.org
… al., 2015; Liu et al., 2015; Wieting et al., 2015; Mrksic et al., 2017), machine trans- lation (Shi et al., 2016; Zhang et al., 2017b), lan- guage modeling (Ahn et al., 2016), and dialogue systems (Chen et … The words are lemmatized using Stanford CoreNLP 3.7.0 (Manning et al., 2014 …

Towards a new possibilistic query translation tool for cross-language information retrieval
B Elayeb, WB Romdhane, NBB Saoud – Multimedia Tools and …, 2018 – Springer
Approaches of query translation in Cross-Language Information Retrieval (CLIR) have frequently used dictionaries which suffer from translation ambiguity. Besides, a word-by-word query translation is n.

Short Answer Assessment in Context: The Role of Information Structure
R Ziai – core.ac.uk
Page 1. Short Answer Assessment in Context: The Role of Information Structure Dissertation zur Erlangung des akademischen Grades Doktor der Philosophie in der Philosophischen Fakultät der Eberhard Karls Universität T¨ubingen vorgelegt von Ramon Ziai aus Straßburg …

SUAR: Towards Building a Corpus for the Saudi Dialect
N Al-Twairesh, R Al-Matham, N Madi… – Procedia computer …, 2018 – Elsevier
… Most NLP applications such as machine translation, sentiment analysis, information extraction, and dialogue systems need enabling technologies … Like most morphological analyzers, MADAMIRA can be used for tokenization, lemmatization, and identification of morphological …

Applications of Sequence to Sequence Models for Technical Support Automation
G Aalipour, P Kumar, S Aditham… – … Conference on Big …, 2018 – ieeexplore.ieee.org
… A traditional generative model for dialog systems that empha- sizes on the importance of hierarchy within previous dialogs [12] … We started with simple popular techniques such as lowercasing, stemming and lemmatizing and stop word removals …

An Encoder-decoder Approach to Predicting Causal Relations in Stories
M Roemmele, A Gordon – Proceedings of the First Workshop on …, 2018 – aclweb.org
… For all experiments, we filtered grammati- cal words (ie all words except for adjectives, ad- verbs, nouns, and verbs) and lemmatized all seg- ments, consistent with Luo et al. (2016). COPA items intentionally do not contain proper nouns, so we excluded them as well …

LSTM Hypertagging
R Fu, M White – Proceedings of the 11th International Conference on …, 2018 – aclweb.org
… ues of the missing relations were set to the empty string. This kept the size of the input constant. • Lexical Features: Lemmatized words asso- ciated with elementary predication nodes • Node Attribute Features: Named entity cat- egory, determiner, mood, number, particle, tense …

Identifying Author Topic Stance in Online Discussion Forums
G Patterson – 2018 – escholarship.org
… both sides of an issue. It could also be used to learn the linguistic and rhetorical devices that make for successful persuasive arguments, or the expressions of disagreement, which could then be used in other dialog systems or chatbots. Furthermore, this methodology …

Tailored Sequence to Sequence Models to Different Conversation Scenarios
H Zhang, Y Lan, J Guo, J Xu, X Cheng – … of the 56th Annual Meeting of …, 2018 – aclweb.org
… While in other scenarios such as chatbot, users are interacting with the dialogue system for fun … For ex- ample, we use the official script to tokenize, stem and lemmatize, and the duplicates and sentences with length less than 5 or longer than 50 are re- moved …

Towards Building a Domain Independent Dialog System
P Jwalapuram – 2018 – web2py.iiit.ac.in
… They use a tokenizer, tagger, lemmatizer and a chunker, but discount the need for a grammar based syntactic parser … [4] describes an ontology based dialog system that simulates a health counselor, using an RDF- based ontology described in OWL …

To Read or To Do? That’s The Task
Z Alibadi, J Vidal – jmvidal.cse.sc.edu
… Therefore, we kept only alphabetical characters and the special char of question mark “?” and we didn’t stem or lemmatize the text … a wide range of natural language-related tasks such as parsing, part-of-speech (POS) tagging, machine translation, dialog systems, and sentiments …

Mixed-initiative active learning for generating linguistic insights in question classification
R Sevastjanova, M El-Assady… – Workshop on Data …, 2018 – researchgate.net
… A labeling interface can be designed through a dialog system, a visualization, or other interface design mediums … To reduce the chance that the models overfit, we apply a lemmatizer and extract only n-grams (unigrams, bigrams and trigrams) which occur more than three times in …

Detecting Machine-translated Subtitles in Large Parallel Corpora
P Lison, AS Dogruöz – 11th Workshop on Building and Using …, 2018 – lrec-conf.org
… Parallel corpora extracted from online repositories of movie and TV subtitles are employed in a wide range of NLP applications, from language modelling to machine translation and dialogue systems … Tokenizing, POS tag- ging, lemmatizing and parsing UD 2.0 with UDPipe …

Creating New Concept-Based Representations for Superior Text Analysis and Retrieval
W Shalaby – 2018 – search.proquest.com
Page 1. CREATING NEW CONCEPT-BASED REPRESENTATIONS FOR SUPERIOR TEXT ANALYSIS AND RETRIEVAL by Walid Shalaby A dissertation submitted to the faculty of The University of North Carolina at Charlotte …

R?ku kopa latviešu valodas semantikas anal?zei: publik?ciju kopa
P Paikens – 2018 – dspace.lu.lv
… The use-cases are ranging from controlled languages (eg dialogue systems and interfaces to formal languages) to domain-specific machine translation … In particular, we have implemented a set of functions that detail the lemma- tization and palatalization that occurs in Latvian …

Interpretable Multimodal Retrieval for Fashion Products
L Liao, X He, B Zhao, CW Ngo, TS Chua – 2018 ACM Multimedia …, 2018 – dl.acm.org
… 5.1.3 Training Setups. For product images, we trained a Multi- Box model [37] to detect and crop clothing items. For text descrip- tions of products, we pre-processed all the sentences with Word- Net’s lemmatizer [1] and removed stop words …

The META-NET strategic research agenda for language technology in Europe: An extended summary
G Rehm – Language technologies for a multilingual Europe, 2018 – oapen.org
… A top layer consists of language processing such as text filters, tokenisation, spell, grammar and style checking, hyphenation, lemmatising and parsing … Part of this layer are question answering and dialogue systems as well as email response applications …

Multimodal Sentiment Analysis
S Poria, A Hussain, E Cambria – 2018 – Springer
… Examples of the second domain will include, but not limited to: computational and psychological models of emotions, bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning …

Modeling Linguistic and Personality Adaptation for Natural Language Generation
Z Hu, JF Tree, M Walker – Proceedings of the 19th Annual SIGdial …, 2018 – aclweb.org
… Zhichao Hu1, Jean E. Fox Tree2 and Marilyn A. Walker1 Natural Language and Dialogue Systems Lab, Computer Science Department1 Spontaneous Communication … We lemmatize, POS tag and derive constituency structures using Stanford CoreNLP (Manning et al., 2014) …

Augmenting Neural Response Generation with Context-Aware Topical Attention
N Dziri, E Kamalloo, KW Mathewson… – arXiv preprint arXiv …, 2018 – arxiv.org
… A good dialogue system should be capable of sustaining a coherent conversation with a human by staying on topic and by following a train of thoughts (Venkatesh … Each utterance is rep- resented by lemmatized bag-of-words where stop words and punctuation marks are omitted …

Summarization of Maryland Shooting Collection
P Khawas, B Banerjee, S Zhao, Y Fan, Y Kim – 2018 – vtechworks.lib.vt.edu
… 1. Tokenizing & Lemmatizing – Breaking the collection into its individual words and lemmatizing using NLTK’s WordNet Lemmatizer. 2. Generating POS tags using NLTK’s pos tag method for the most frequent words found in Section 4.1. 4.3.2 Results …

A dynamic deep learning approach for intonation modeling
F Tombini – 2018 – publikationen.sulb.uni-saarland.de
… Nevertheless, intonation remains a rather pressing research topic, that Page 14. 2 is bound to become more critical in the coming years, especially as the demand for TTS applications such as dialog systems, virtual agents, and personal assistants increases …

Language-Based Bidirectional Human and Robot Interaction Learning for Mobile Service Robots
V Perera – 2018 – reports-archive.adm.cs.cmu.edu
Page 1. Language-Based Bidirectional Human and Robot Interaction Learning for Mobile Service Robots Vittorio Perera CMU-CS-18-108 August 22, 2018 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 …

Representation learning for natural language
O MOGREN – mogren.one
… humans (Turing 1950). This was published long before machines were anywhere near being able to succeed at this, while substantial progress has been made in recent years using dialog systems trained on large corpora. Most of …

Corpus Annotation and Inference with Episodic Logic Type Structure
G Kim – 2018 – cs.rochester.edu
… activity and requirement for understanding. We do not want a dialogue system or other NLU system to jump to unwarranted conclusions about the reality of ghosts or about rats that are bigger than elephants. In a sense, the omissions …

Distinguishing between facts and opinions for sentiment analysis: Survey and challenges
I Chaturvedi, E Cambria, RE Welsch, F Herrera – Information Fusion, 2018 – Elsevier
… leading to many exciting open challenges, as well as in the business world, due to the remarkable benefits to be had from financial [29] and political [30] forecasting, e-health [31] and e-tourism [32], human communication comprehension [33] and dialogue systems [34], etc …

The First Financial Narrative Processing Workshop (FNP 2018)
M El-Haj, P Rayson, A Moore – 2018 – lrec-conf.org
… Throughout our work, all 1 lemmatizing and morphological analysis tasks are done by DEMorphy. 2. Introduction Keeping dialogue state in conversational interfaces is a notoriously difficult task. Dialogue systems, also known as chatbots, virtual assistants and conversational …

Neural Networks for Narrative Continuation
M Roemmele – 2018 – roemmele.github.io
… of what became known as template-based generation. One historical example of the template-based approach was the dialogue system ELIZA (Weizenbaum, 1966). As one of the first ‘chatbots’, ELIZA was a program that acted as a psychother …

Affective analysis of text in tweets
AA Narwekar – 2018 – ideals.illinois.edu
… more articulate ways to convey the emotions in an email, etc. 2. Better Human Computer Interaction • One may construct dialogue systems that adapts its behaviour based on the emo- tional state of the user [102]. As an example, consider the benefits of performing …

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
E Riloff, D Chiang, H Julia, T Jun’ichi – Proceedings of the 2018 …, 2018 – aclweb.org
… She works on spoken language processing and NLP, studying text-to-speech synthesis, spoken dialogue systems, entrainment in conversation, detection of deceptive and emotional speech, hedging behavior, and linguistic code-switching (language mixing). xxii Page 23 …

A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
D Shekhar – 2018 – digitalcommons.du.edu
… tems or Conversational Agents – perhaps a desirable application of the future- have been growing rapidly. A Dialog System can communicate with human in text, speech or both and can be classified into – Task-oriented Systems and Chatbot Systems …

Word Rewarding for Adequate Neural Machine Translation
Y Takebayashi, C Chenhui, Y Arase… – … Workshop on Spoken …, 2018 – workshop2018.iwslt.org
… We used MeCab for Japanese and TreeTagger for English to lemmatize words … E17-2058 [27] T.-H. Wen, M. Gasic, N. Mrkšic, P.-H. Su, D. Vandyke, and S. Young,“Semantically conditioned lstm-based natural language generation for spoken dialogue systems,” in Proceedings …

A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version
IV Serban, R Lowe, P Henderson… – Dialogue & …, 2018 – dad.uni-bielefeld.de
… A Survey of Available Corpora for Building Data-Driven Dialogue Systems: The Journal Version Iulian Vlad Serban … In the area of dialogue systems, the trend is less obvious, and most practical systems are still built through significant engineering and expert knowledge …

From Compute to Data: Across-the-Stack System Design for Intelligent Applications
Y Kang – 2018 – deepblue.lib.umich.edu
… We have observed that the complexity of building dialogue system for a real-world use case is often substantially greater than those studied in the re … classification in a real-world intelligent dialogue system? 1.2 Across-the-Stack System Design for Intelligent Applica- tions …

Response Generation For An Open-Ended Conversational Agent
N Dziri – 2018 – era.library.ualberta.ca
… Over the past decade, dialogue systems have become omnipresent in our daily lives, assisting … models has shown promising results in solving problems such as scalability and language-independence that conventional dialogue system fail to cope with …

Automatic Image Captioning with Style
AP Mathews – 2018 – openresearch-repository.anu.edu.au
Page 1. Automatic Image Captioning with Style Alexander Mathews A thesis submitted for the degree of Doctor of Philosophy The Australian National University November 2018 Page 2. c Alexander Mathews 2018 Page 3. Except …

Extracting Linguistic Resources from the Web for Concept-to-Text Generation
G Lampouras, I Androutsopoulos – arXiv preprint arXiv:1810.13414, 2018 – arxiv.org
… we follow a procedure similar to the one we use to identify individuals or classes that should be anonymous (Section 3.1.1). For each <S, R, O> triple that involves the individual or class S being described, we examine the nl names of S and O. If all the (lemmatized) words of the …

Scalable and Efficient Probabilistic Topic Model Inference for Textual Data
M Magnusson – 2018 – books.google.com
Page 1. Linköping Studies in Arts and Sciences No. 743 Linköping Studies in Statistics No. 14 Scalable and Efficient Probabilistic Topic Model Inference for Textual Data Måns Magnusson Page 2. Faculty of Arts and Sciences Dissertations, No …

CRM and sentiment analysis, the supporting role of leading-edge technologies
M Chiarato – 2018 – tesi.cab.unipd.it
Page 1. UNIVERSITA’ DEGLI STUDI DI PADOVA DIPARTIMENTO DI SCIENZE ECONOMICHE ED AZIENDALI “MARCO FANNO” CORSO DI LAUREA MAGISTRALE IN BUSINESS ADMINISTRATION TESI DI LAUREA “CRM AND SENTIMENT ANALYSIS …

How to Do Corpus Pragmatics on Pragmatically Annotated Data: Speech Acts and Beyond
M Weisser – 2018 – books.google.com
Page 1. JOHN BENJAMINS PUBLISHING COMPANY on Pragmatically Annotated Data 84 Corpus Pragmatics Martin Weisser How to Do Page 2. How to Do Corpus Pragmatics on Pragmatically Annotated Data Page 3. Studies …