Download or read book Natural Statistical Models for Automatic Speech Recognition written by Jeff Bilmes and published by . This book was released on 1999 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptation of Statistical Language Models for Automatic Speech Recognition written by P. R. Clarkson and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Language and Speech Processing written by Nathalie Camelin and published by Springer. This book was released on 2017-10-09 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Statistical Language and Speech Processing, SLSP 2017, held in Le Mans, France, in October 2017. The 21 full papers presented were carefully reviewed and selected from 39 submissions. The papers cover topics such as anaphora and conference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semanticweb; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question and answering systems; semantic role labeling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; speech correction; spoken dialogue systems; term extraction; text categorization; test summarization; user modeling. They are organized in the following sections: language and information extraction; post-processing and applications of automatic transcriptions; speech paralinguistics and synthesis; speech recognition: modeling and resources.
Download or read book Statistical Methods for Speech Recognition written by Frederick Jelinek and published by MIT Press. This book was released on 2022-11-01 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint
Download or read book Statistical Methods for Speech Recognition written by Frederick Jelinek and published by MIT Press. This book was released on 1998-01-15 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.
Download or read book Statistical Language and Speech Processing written by Thierry Dutoit and published by Springer. This book was released on 2018-10-08 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 6th International Conference on Statistical Language and Speech Processing, SLSP 2018, held in Mons, Belgium, in October 2018. The 15 full papers presented in this volume were carefully reviewed and selected from 40 submissions. They were organized in topical sections named: speech synthesis and spoken language generation; speech recognition and post-processing; natural language processing and understanding; and text processing and analysis.
Download or read book Dynamic Speech Models written by Li Deng and published by Morgan & Claypool Publishers. This book was released on 2006-12-01 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech dynamics refer to the temporal characteristics in all stages of the human speech communication process. This speech “chain” starts with the formation of a linguistic message in a speaker's brain and ends with the arrival of the message in a listener's brain. Given the intricacy of the dynamic speech process and its fundamental importance in human communication, this monograph is intended to provide a comprehensive material on mathematical models of speech dynamics and to address the following issues: How do we make sense of the complex speech process in terms of its functional role of speech communication? How do we quantify the special role of speech timing? How do the dynamics relate to the variability of speech that has often been said to seriously hamper automatic speech recognition? How do we put the dynamic process of speech into a quantitative form to enable detailed analyses? And finally, how can we incorporate the knowledge of speech dynamics into computerized speech analysis and recognition algorithms? The answers to all these questions require building and applying computational models for the dynamic speech process. What are the compelling reasons for carrying out dynamic speech modeling? We provide the answer in two related aspects. First, scientific inquiry into the human speech code has been relentlessly pursued for several decades. As an essential carrier of human intelligence and knowledge, speech is the most natural form of human communication. Embedded in the speech code are linguistic (as well as para-linguistic) messages, which are conveyed through four levels of the speech chain. Underlying the robust encoding and transmission of the linguistic messages are the speech dynamics at all the four levels. Mathematical modeling of speech dynamics provides an effective tool in the scientific methods of studying the speech chain. Such scientific studies help understand why humans speak as they do and how humans exploit redundancy and variability by way of multitiered dynamic processes to enhance the efficiency and effectiveness of human speech communication. Second, advancement of human language technology, especially that in automatic recognition of natural-style human speech is also expected to benefit from comprehensive computational modeling of speech dynamics. The limitations of current speech recognition technology are serious and are well known. A commonly acknowledged and frequently discussed weakness of the statistical model underlying current speech recognition technology is the lack of adequate dynamic modeling schemes to provide correlation structure across the temporal speech observation sequence. Unfortunately, due to a variety of reasons, the majority of current research activities in this area favor only incremental modifications and improvements to the existing HMM-based state-of-the-art. For example, while the dynamic and correlation modeling is known to be an important topic, most of the systems nevertheless employ only an ultra-weak form of speech dynamics; e.g., differential or delta parameters. Strong-form dynamic speech modeling, which is the focus of this monograph, may serve as an ultimate solution to this problem. After the introduction chapter, the main body of this monograph consists of four chapters. They cover various aspects of theory, algorithms, and applications of dynamic speech models, and provide a comprehensive survey of the research work in this area spanning over past 20~years. This monograph is intended as advanced materials of speech and signal processing for graudate-level teaching, for professionals and engineering practioners, as well as for seasoned researchers and engineers specialized in speech processing
Download or read book A Tree based Statistical Language Model for Natural Language Speech Recognition written by L. R. Bahl and published by . This book was released on 1987 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Incorporating Knowledge Sources into Statistical Speech Recognition written by Sakriani Sakti and published by Springer. This book was released on 2008-11-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.
Download or read book Statistical Language and Speech Processing written by Luis Espinosa-Anke and published by Springer Nature. This book was released on 2021-10-16 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Conference on Statistical Language and Speech Processing, SLSP 2021, held in Cardiff, UK, in November 2021. The 9 full papers presented in this volume were carefully reviewed and selected from 21 submissions. The papers present topics of either theoretical or applied interest discussing the employment of statistical models (including machine learning) within language and speech processing.
Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Download or read book Towards Adaptive Spoken Dialog Systems written by Alexander Schmitt and published by Springer Science & Business Media. This book was released on 2012-09-19 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use. Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted recordings several thousand real users from commercial and non-commercial SDS. Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer more natural and robust interactions. This work provides insights, lessons and inspiration for future research and development, not only for spoken dialog systems, but for data-driven approaches to human-machine interaction in general.
Download or read book Statistical Pronunciation Modeling for Non Native Speech Processing written by Rainer E. Gruhn and published by Springer Science & Business Media. This book was released on 2011-05-08 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.
Download or read book Robustness in Language and Speech Technology written by Jean-Claude Junqua and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book we address robustness issues at the speech recognition and natural language parsing levels, with a focus on feature extraction and noise robust recognition, adaptive systems, language modeling, parsing, and natural language understanding. This book attempts to give a clear overview of the main technologies used in language and speech processing, along with an extensive bibliography to enable topics of interest to be pursued further. It also brings together speech and language technologies often considered separately. Robustness in Language and Speech Technology serves as a valuable reference and although not intended as a formal university textbook, contains some material that can be used for a course at the graduate or undergraduate level.
Download or read book Statistical Language Modeling for Automatic Speech Recognition of Agglutinative Languages written by Ebru Arısoy and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Language Modeling for Automatic Speech Recognition of Agglutinative Languages.
Download or read book Statistical Language and Speech Processing written by Adrian-Horia Dediu and published by Springer. This book was released on 2013-07-24 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Conference on Statistical Language and Speech Processing, SLSP 2013, held in Tarragona, Spain, in July 2013. The 24 full papers presented together with two invited talks were carefully reviewed and selected from 61 submissions. The papers cover a wide range of topics in the fields of computational language and speech processing and the statistical methods that are currently in use.
Download or read book Audio Processing and Speech Recognition written by Soumya Sen and published by Springer. This book was released on 2019-01-30 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an overview of audio processing, including the latest advances in the methodologies used in audio processing and speech recognition. First, it discusses the importance of audio indexing and classical information retrieval problem and presents two major indexing techniques, namely Large Vocabulary Continuous Speech Recognition (LVCSR) and Phonetic Search. It then offers brief insights into the human speech production system and its modeling, which are required to produce artificial speech. It also discusses various components of an automatic speech recognition (ASR) system. Describing the chronological developments in ASR systems, and briefly examining the statistical models used in ASR as well as the related mathematical deductions, the book summarizes a number of state-of-the-art classification techniques and their application in audio/speech classification. By providing insights into various aspects of audio/speech processing and speech recognition, this book appeals a wide audience, from researchers and postgraduate students to those new to the field.
