Academic literature on the topic 'Multilingual Modeling'
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Journal articles on the topic "Multilingual Modeling"
Haas, Alison, Scott E. Grapin, Lorena Llosa, and Okhee Lee. "Computational Modeling With Multilingual Learners." Science and Children 60, no. 7 (September 2023): 64–70. http://dx.doi.org/10.1080/00368148.2023.12315941.
Full textSanthosh Kumar, C., and V. P. Mohandas. "Robust features for multilingual acoustic modeling." International Journal of Speech Technology 14, no. 3 (May 11, 2011): 147–55. http://dx.doi.org/10.1007/s10772-011-9092-6.
Full textGrutman, Rainier. "The Missing Link: Modeling Readers of Multilingual Writing." Journal of Literary Multilingualism 1, no. 1 (May 2023): 15–36. http://dx.doi.org/10.1163/2667324x-20230103.
Full textPark, Hyunji Hayley, Katherine J. Zhang, Coleman Haley, Kenneth Steimel, Han Liu, and Lane Schwartz. "Morphology Matters: A Multilingual Language Modeling Analysis." Transactions of the Association for Computational Linguistics 9 (March 17, 2021): 261–76. http://dx.doi.org/10.1162/tacl_a_00365.
Full textLindén, Krister. "Multilingual modeling of cross-lingual spelling variants." Information Retrieval 9, no. 3 (June 2006): 295–310. http://dx.doi.org/10.1007/s10791-006-1541-5.
Full textHan, Yao Jun, and Xue Mei Luo. "Modeling and Analysis of Multilingual Information Parallel Downloads in Data Grid." Applied Mechanics and Materials 263-266 (December 2012): 1424–28. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1424.
Full textSong, Guizhe, Degen Huang, and Zhifeng Xiao. "A Study of Multilingual Toxic Text Detection Approaches under Imbalanced Sample Distribution." Information 12, no. 5 (May 12, 2021): 205. http://dx.doi.org/10.3390/info12050205.
Full textHao, Shudong, and Michael J. Paul. "An Empirical Study on Crosslingual Transfer in Probabilistic Topic Models." Computational Linguistics 46, no. 1 (March 2020): 95–134. http://dx.doi.org/10.1162/coli_a_00369.
Full textRahimi, Razieh, Azadeh Shakery, and Irwin King. "Multilingual information retrieval in the language modeling framework." Information Retrieval Journal 18, no. 3 (May 6, 2015): 246–81. http://dx.doi.org/10.1007/s10791-015-9255-1.
Full textMitchell, Joan S., Marcia Lei Zeng, and Maja Žumer. "Modeling Classification Systems in Multicultural and Multilingual Contexts." Cataloging & Classification Quarterly 52, no. 1 (December 18, 2013): 90–101. http://dx.doi.org/10.1080/01639374.2013.845620.
Full textDissertations / Theses on the topic "Multilingual Modeling"
Wicentowski, Richard. "Modeling and learning multilingual inflectional morphology in a minimally supervised framework." Available to US Hopkins community, 2002. http://wwwlib.umi.com/dissertations/dlnow/3068229.
Full textSchleider, Thomas. "Knowledge Modeling and Multilingual Information Extraction for the Understanding of the Cultural Heritage of Silk." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS280.
Full textModeling any type of human knowledge is a complex effort and needs to consider all specificities of its domain including niche vocabulary. This thesis focuses on such an endeavour for the knowledge about the European silk object production, which can be considered obscure and therefore endangered. However, the fact that such Cultural Heritage data is heterogenous, spread across many museums worldwide, sparse and multilingual poses particular challenges for which knowledge graphs have become more and more popular in recent years. Our main goal is not only into investigating knowledge representations, but also in which ways such an integration process can be accompanied through enrichments, such as information reconciliation through ontologies and vocabularies, as well as metadata predictions to fill gaps in the data. We will first propose a workflow for the management for the integration of data about silk artifacts and afterwards present different classification approaches, with a special focus on unsupervised and zero-shot methods. Finally, we study ways of making exploration of such metadata and images afterwards as easy as possible
Caon, Daniel Régis Sarmento. "Automatic speech recognition, with large vocabulary, robustness, independence of speaker and multilingual processing." Universidade Federal do Espírito Santo, 2010. http://repositorio.ufes.br/handle/10/6390.
Full textThis work aims to provide automatic cognitive assistance via speech interface, to the elderly who live alone, at risk situation. Distress expressions and voice commands are part of the target vocabulary for speech recognition. Throughout the work, the large vocabulary continuous speech recognition system Julius is used in conjunction with the Hidden Markov Model Toolkit(HTK). The system Julius has its main features described, including its modification. This modification is part of the contribution which is in this work, including the detection of distress expressions ( situations of speech which suggest emergency). Four different languages were provided as target for recognition: French, Dutch, Spanish and English. In this same sequence of languages (determined by data availability and the local of scenarios for the integration of systems) theoretical studies and experiments were conducted to solve the need of working with each new configuration. This work includes studies of the French and Dutch languages. Initial experiments (in French) were made with adaptation of hidden Markov models and were analyzed by cross validation. In order to perform a new demonstration in Dutch, acoustic and language models were built and the system was integrated with other auxiliary modules (such as voice activity detector and the dialogue system). Results of speech recognition after acoustic adaptation to a specific speaker (and the creation of language models for a specific scenario to demonstrate the system) showed 86.39 % accuracy rate of sentence for the Dutch acoustic models. The same data shows 94.44 % semantical accuracy rate of sentence
Este trabalho visa prover assistência cognitiva automática via interface de fala, à idosos que moram sozinhos, em situação de risco. Expressões de angústia e comandos vocais fazem parte do vocabulário alvo de reconhecimento de fala. Durante todo o trabalho, o sistema de reconhecimento de fala contínua de grande vocabulário Julius é utilizado em conjunto com o Hidden Markov Model Toolkit(HTK). O sistema Julius tem suas principais características descritas, tendo inclusive sido modificado. Tal modificação é parte da contribuição desse estudo, assim como a detecção de expressões de angústia (situações de fala que caracterizam emergência). Quatro diferentes linguas foram previstas como alvo de reconhecimento: Francês, Holandês, Espanhol e Inglês. Nessa mesma ordem de linguas (determinadas pela disponibilidade de dados e local de cenários de integração de sistemas) os estudos teóricos e experimentos foram conduzidos para suprir a necessidade de trabalhar com cada nova configuração. Este trabalho inclui estudos feitos com as linguas Francês e Holandês. Experimentos iniciais (em Francês) foram feitos com adaptação de modelos ocultos de Markov e analisados por validação cruzada. Para realizar uma nova demonstração em Holandês, modelos acústicos e de linguagem foram construídos e o sistema foi integrado a outros módulos auxiliares (como o detector de atividades vocais e sistema de diálogo). Resultados de reconhecimento de fala após adaptação dos modelos acústicos à um locutor específico (e da criação de modelos de linguagem específicos para um cenário de demonstração do sistema) demonstraram 86,39% de taxa de acerto de sentença para os modelos acústicos holandeses. Os mesmos dados demonstram 94,44% de taxa de acerto semântico de sentença
Gohr, André [Verfasser], Alexander [Akademischer Betreuer] Hinneburg, and Stefan [Akademischer Betreuer] Wrobel. "Learning and visualizing topics and their change with time for the exploratory analysis of social tags and multilingual topic modeling of chemical compounds / André Gohr. Betreuer: Alexander Hinneburg ; Stefan Wrobel." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2012. http://d-nb.info/1033306614/34.
Full textWright, Chrysalis L. "Parental Absence and Academic Achievement in Immigrant Students." FIU Digital Commons, 2010. http://digitalcommons.fiu.edu/etd/322.
Full textJackson, Brianne L. "Assessing K12 Online Teachers Knowledge of Online Student Identities and Characteristics." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5316.
Full textMuller, Benjamin. "How Can We Make Language Models Better at Handling the Diversity and Variability of Natural Languages ?" Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS399.
Full textDeep Learning for NLP has led to impressive empirical progress in recent years. In essence, this progress is based on better contextualized representations that can be easily used for a wide variety of tasks. However, these models usually require substantial computing power and large amounts of raw textual data. This makes language’s inherent diversity and variability a vivid challenge in NLP. We focus on the following: How can we make language models better at handling the variability and diversity of natural languages?. First, we explore the generalizability of language models by building and analyzing one of the first large-scale replication of a BERT model for a non-English language. Our results raise the question of using these language models on highly-variable domains such as these found online. Focusing on lexical normalization, we show that this task can be approached with BERT-like models. However, we show that it only partially helps downstream performance. In consequence, we focus on adaptation techniques using what we refer to as representation transfer and explore challenging settings such as the zero-shot setting, low-resource languages. We show that multilingual language models can be adapted and used efficiently with low-resource languages, even with the ones unseen during pretraining, and that the script is a critical component in this adaptation
Martin, Terrence Lance. "Towards improved speech recognition for resource poor languages." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/35771/1/Terrence_Martin_Thesis.pdf.
Full textBalikas, Georgios. "Explorer et apprendre à partir de collections de textes multilingues à l'aide des modèles probabilistes latents et des réseaux profonds." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAM054/document.
Full textText is one of the most pervasive and persistent sources of information. Content analysis of text in its broad sense refers to methods for studying and retrieving information from documents. Nowadays, with the ever increasing amounts of text becoming available online is several languages and different styles, content analysis of text is of tremendous importance as it enables a variety of applications. To this end, unsupervised representation learning methods such as topic models and word embeddings constitute prominent tools.The goal of this dissertation is to study and address challengingproblems in this area, focusing on both the design of novel text miningalgorithms and tools, as well as on studying how these tools can be applied to text collections written in a single or several languages.In the first part of the thesis we focus on topic models and more precisely on how to incorporate prior information of text structure to such models.Topic models are built on the premise of bag-of-words, and therefore words are exchangeable. While this assumption benefits the calculations of the conditional probabilities it results in loss of information.To overcome this limitation we propose two mechanisms that extend topic models by integrating knowledge of text structure to them. We assume that the documents are partitioned in thematically coherent text segments. The first mechanism assigns the same topic to the words of a segment. The second, capitalizes on the properties of copulas, a tool mainly used in the fields of economics and risk management that is used to model the joint probability density distributions of random variables while having access only to their marginals.The second part of the thesis explores bilingual topic models for comparable corpora with explicit document alignments. Typically, a document collection for such models is in the form of comparable document pairs. The documents of a pair are written in different languages and are thematically similar. Unless translations, the documents of a pair are similar to some extent only. Meanwhile, representative topic models assume that the documents have identical topic distributions, which is a strong and limiting assumption. To overcome it we propose novel bilingual topic models that incorporate the notion of cross-lingual similarity of the documents that constitute the pairs in their generative and inference processes. Calculating this cross-lingual document similarity is a task on itself, which we propose to address using cross-lingual word embeddings.The last part of the thesis concerns the use of word embeddings and neural networks for three text mining applications. First, we discuss polylingual document classification where we argue that translations of a document can be used to enrich its representation. Using an auto-encoder to obtain these robust document representations we demonstrate improvements in the task of multi-class document classification. Second, we explore multi-task sentiment classification of tweets arguing that by jointly training classification systems using correlated tasks can improve the obtained performance. To this end we show how can achieve state-of-the-art performance on a sentiment classification task using recurrent neural networks. The third application we explore is cross-lingual information retrieval. Given a document written in one language, the task consists in retrieving the most similar documents from a pool of documents written in another language. In this line of research, we show that by adapting the transportation problem for the task of estimating document distances one can achieve important improvements
Cossu, Jean-Valère. "Analyse de l’image de marque sur le Web 2.0." Thesis, Avignon, 2015. http://www.theses.fr/2015AVIG0207/document.
Full textAnalyse of entities representation over the Web 2.0Every day, millions of people publish their views on Web 2.0 (social networks,blogs, etc.). These comments focus on subjects as diverse as news, politics,sports scores, consumer objects, etc. The accumulation and agglomerationof these notices on an entity (be it a product, a company or a public entity) givebirth to the brand image of that entity. Internet has become in recent years aprivileged place for the emergence and dissemination of opinions and puttingWeb 2.0 at the head of observatories of opinions. The latter being a means ofaccessing the knowledge of the opinion of the world population.The image is here understood as the idea that a person or a group of peopleis that entity. This idea carries a priori on a particular subject and is onlyvalid in context for a given time. This perceived image is different from theentity initially wanted to broadcast (eg via a communication campaign). Moreover,in reality, there are several images in the end living together in parallel onthe network, each specific to a community and all evolve differently over time(imagine how would be perceived in each camp together two politicians edgesopposite). Finally, in addition to the controversy caused by the voluntary behaviorof some entities to attract attention (think of the declarations required orshocking). It also happens that the dissemination of an image beyond the frameworkthat governed the and sometimes turns against the entity (for example,« marriage for all » became « the demonstration for all »). The views expressedthen are so many clues to understand the logic of construction and evolution ofthese images. The aim is to be able to know what we are talking about and howwe talk with filigree opportunity to know who is speaking.viiIn this thesis we propose to use several simple supervised statistical automaticmethods to monitor entity’s online reputation based on textual contentsmentioning it. More precisely we look the most important contents and theirsauthors (from a reputation manager point-of-view). We introduce an optimizationprocess allowing us to enrich the data using a simulated relevance feedback(without any human involvement). We also compare content contextualizationmethod using information retrieval and automatic summarization methods.Wealso propose a reflection and a new approach to model online reputation, improveand evaluate reputation monitoring methods using Partial Least SquaresPath Modelling (PLS-PM). In designing the system, we wanted to address localand global context of the reputation. That is to say the features can explain thedecision and the correlation betweens topics and reputation. The goal of ourwork was to propose a different way to combine usual methods and featuresthat may render reputation monitoring systems more accurate than the existingones. We evaluate and compare our systems using state of the art frameworks: Imagiweb and RepLab. The performances of our proposals are comparableto the state of the art. In addition, the fact that we provide reputation modelsmake our methods even more attractive for reputation manager or scientistsfrom various fields
Books on the topic "Multilingual Modeling"
(Editor), Kenneth Hyltenstam, and Manfred Pienemann (Editor), eds. Modelling Assessing SEC Lang (Multilingual Matters). Multilingual Matters Limited, 1985.
Find full text(Editor), Kenneth Hyltenstam, and Manfred Pienemann (Editor), eds. Modelling and Assessing: Second Language Acquisition (Multilingual Matters). Multilingual Matters, 1998.
Find full textBook chapters on the topic "Multilingual Modeling"
Ghorab, M. Rami, Séamus Lawless, Alexander O’Connor, Dong Zhou, and Vincent Wade. "Multilingual vs. Monolingual User Models for Personalized Multilingual Information Retrieval." In User Modeling, Adaptation, and Personalization, 356–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38844-6_38.
Full textSteichen, Ben, M. Rami Ghorab, Alexander O’Connor, Séamus Lawless, and Vincent Wade. "Towards Personalized Multilingual Information Access - Exploring the Browsing and Search Behavior of Multilingual Users." In User Modeling, Adaptation, and Personalization, 435–46. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08786-3_39.
Full textGao, Ming, Shilian Wu, and Zengfu Wang. "A Length-Sensitive Language-Bound Recognition Network for Multilingual Text Recognition." In MultiMedia Modeling, 139–50. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27818-1_12.
Full textEmbley, David W., Stephen W. Liddle, Deryle W. Lonsdale, and Yuri Tijerino. "Multilingual Ontologies for Cross-Language Information Extraction and Semantic Search." In Conceptual Modeling – ER 2011, 147–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24606-7_12.
Full textDíaz Esteban, Alberto. "Integrating Multilingual Text Classification Tasks and User Modeling in Personalized Newspaper Services." In User Modeling 2001, 268–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44566-8_41.
Full textChew, Peter A., and Jessica G. Turnley. "Understanding Russian Information Operations Using Unsupervised Multilingual Topic Modeling." In Social, Cultural, and Behavioral Modeling, 102–7. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60240-0_12.
Full textDonahue, Christiane. "Trends in modeling academic writing in multilingual contexts." In Academic writing across languages: multilingual and contrastive approaches in higher education, 41–58. Wien: Böhlau Verlag, 2019. http://dx.doi.org/10.7767/9783205208815.41.
Full textChew, Peter A. "‘Linguistics-Lite’ Topic Extraction from Multilingual Social Media Data." In Social Computing, Behavioral-Cultural Modeling, and Prediction, 276–82. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16268-3_30.
Full textMogadala, Aditya, Rambhoopal Kothwal, and Vasudeva Varma. "Language Modeling Approach to Retrieval for SMS and FAQ Matching." In Multilingual Information Access in South Asian Languages, 119–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40087-2_12.
Full textWu, Jiajia, Kun Zhao, Zhengyan Yang, Bing Yin, Cong Liu, and Lirong Dai. "End-to-End Multilingual Text Recognition Based on Byte Modeling." In Lecture Notes in Computer Science, 128–37. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-46311-2_11.
Full textConference papers on the topic "Multilingual Modeling"
Tian, Jilei, Juha Häkkinen, and Olli Viikki. "Multilingual pronunciation modeling for improving multilingual speech recognition." In 7th International Conference on Spoken Language Processing (ICSLP 2002). ISCA: ISCA, 2002. http://dx.doi.org/10.21437/icslp.2002-176.
Full textDatta, Arindrima, Bhuvana Ramabhadran, Jesse Emond, Anjuli Kannan, and Brian Roark. "Language-Agnostic Multilingual Modeling." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9053443.
Full textKanthak, S., and Hermann Ney. "Multilingual acoustic modeling using graphemes." In 8th European Conference on Speech Communication and Technology (Eurospeech 2003). ISCA: ISCA, 2003. http://dx.doi.org/10.21437/eurospeech.2003-373.
Full textMusa, Ibrahim Hussein, Kang Xu, and Ibrahim Zamit. "Multilingual Document Concept Topic Modeling." In 2022 European Conference on Natural Language Processing and Information Retrieval (ECNLPIR). IEEE, 2022. http://dx.doi.org/10.1109/ecnlpir57021.2022.00027.
Full textLowe, Ryan, and Ben Steichen. "Multilingual Search User Behaviors -- Exploring Multilingual Querying and Result Selection Through Crowdsourcing." In UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3079628.3079702.
Full textMoosa, Ibraheem Muhammad, Mahmud Elahi Akhter, and Ashfia Binte Habib. "Does Transliteration Help Multilingual Language Modeling?" In Findings of the Association for Computational Linguistics: EACL 2023. Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.findings-eacl.50.
Full textZha, Hongyuan, and Xiang Ji. "Correlating multilingual documents via bipartite graph modeling." In the 25th annual international ACM SIGIR conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/564376.564485.
Full textGoyal, Naman, Jingfei Du, Myle Ott, Giri Anantharaman, and Alexis Conneau. "Larger-Scale Transformers for Multilingual Masked Language Modeling." In Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021). Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.repl4nlp-1.4.
Full textImseng, David, John Dines, Petr Motlicek, Philip N. Garner, and Hervé Bourlard. "Comparing different acoustic modeling techniques for multilingual boosting." In Interspeech 2012. ISCA: ISCA, 2012. http://dx.doi.org/10.21437/interspeech.2012-369.
Full textRomeo, Salvatore, Andrea Tagarelli, and Dino Ienco. "Semantic-Based Multilingual Document Clustering via Tensor Modeling." In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/d14-1065.
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