Speaker Perception and Recognition. An Integrative Framework for Computational Speech Processing PDF Download
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Author: Oxana Lapteva
Publisher: kassel university press GmbH
ISBN: 3862191753
Category : Automatic speech recognition
Languages : en
Pages : 192
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Book Description
Author: Oxana Lapteva
Publisher: kassel university press GmbH
ISBN: 3862191753
Category : Automatic speech recognition
Languages : en
Pages : 192
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Book Description
Author: Gerry T. M. Altmann
Publisher: MIT Press
ISBN: 9780262510844
Category : Language Arts & Disciplines
Languages : en
Pages : 560
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Book Description
Cognitive Models of Speech Processing presents extensive reviews of current thinking on psycholinguistic and computational topics in speech recognition and natural-language processing, along with a substantial body of new experimental data and computational simulations. Topics range from lexical access and the recognition of words in continuous speech to syntactic processing and the relationship between syntactic and intonational structure. A Bradford Book. ACL-MIT Press Series in Natural Language Processing
Author: Kelly Iverson
Publisher: Cambridge University Press
ISBN: 1009033859
Category : Religion
Languages : en
Pages : 241
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Book Description
Scholars of early Christian literature acknowledge that oral traditions lie behind the New Testament gospels. While the concept of orality is widely accepted, it has not resulted in a corresponding effort to understand the reception of the gospels within their oral milieu. In this book, Kelly Iverson reconsiders the experiential context in which early Christian literature was received and interpreted. He argues that reading and performance are distinguishable media events, and, significantly, that they produce distinctive interpretive experiences for readers and audiences alike. Iverson marshals an array of methodological perspectives demonstrating how performance generates a unique experiential context that shapes and informs the interpretive process. Iverson's study explores the dynamic oral environment in which ancient audiences experienced the gospel stories. He shows why an understanding of oral performance has important implications for the study of the NT, as well as for several issues that are largely unquestioned by biblical scholars.
Author: Eileen C. Schwab
Publisher: Academic Press
ISBN: 1483220109
Category : Reference
Languages : en
Pages : 337
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Book Description
Pattern Recognition by Humans and Machines, Volume 1: Speech Perception covers perception from the perspectives of cognitive psychology, artificial intelligence, and brain theory. The book discusses on the research, theory, and the principal issues of speech perception; the auditory and phonetic coding of speech; and the role of the lexicon in speech perception. The text also describes the role of attention and active processing in speech perception; the suprasegmental in very large vocabulary word recognition; and the adaptive self-organization of serial order in behavior. The cognitive science and the study of cognition and language are also considered. Psychologists will find the book invaluable.
Author: Louis Abbott
Publisher: Tebbo
ISBN: 9781486199600
Category : Reference
Languages : en
Pages : 410
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Book Description
Complete, Unabridged Guide to Speech recognition. Get the information you need--fast! This comprehensive guide offers a thorough view of key knowledge and detailed insight. It's all you need. Here's part of the content - you would like to know it all? Delve into this book today!..... : Speech recognition applications include voice user interfaces such as voice dialing (e. g. , Call home), call routing (e. g. , I would like to make a collect call), domotic appliance control, search (e. g. , find a podcast where particular words were spoken), simple data entry (e. g. , entering a credit card number), preparation of structured documents (e. g. , a radiology report), speech-to-text processing (e. g. , word processors or emails), and aircraft (usually termed Direct Voice Input). ...Each word, or (for more general speech recognition systems), each phoneme, will have a different output distribution; a hidden Markov model for a sequence of words or phonemes is made by concatenating the individual trained hidden Markov models for the separate words and phonemes. ...A typical large-vocabulary system would need context dependency for the phonemes (so phonemes with different left and right context have different realizations as HMM states); it would use cepstral normalization to normalize for different speaker and recording conditions; for further speaker normalization it might use vocal tract length normalization (VTLN) for male-female normalization and maximum likelihood linear regression (MLLR) for more general speaker adaptation. ... Decoding of the speech (the term for what happens when the system is presented with a new utterance and must compute the most likely source sentence) would probably use the Viterbi algorithm to find the best path, and here there is a choice between dynamically creating a combination hidden Markov model, which includes both the acoustic and language model information, and combining it statically beforehand (the finite state transducer, or FST, approach). There is absolutely nothing that isn't thoroughly covered in the book. It is straightforward, and does an excellent job of explaining all about Speech recognition in key topics and material. There is no reason to invest in any other materials to learn about Speech recognition. You'll understand it all. Inside the Guide: Speech recognition, Xuedong Huang, Word error rate, Windows Speech Recognition, VoxForge, Voice user interface, Voice recognition, VoiceXML, Viterbi algorithm, Transcription (linguistics), Technological singularity, Speech verification, Speech technology, Speech synthesis, Speech recognition in Linux, Speech processing, Speech perception, Speech interface guideline, Speech corpus, Speech analytics, Speech-to-text reporter, Speaker recognition, Speaker diarisation, Sensory, Inc., Robotics, Robot Interaction Language, Real time factor, Phonetic search technology, Outline of technology, Outline of artificial intelligence, Nuance Communications, Natural language processing, Multimodal interaction, Multimedia Information Retrieval, Microphone, Mars Polar Lander, Manfred R. Schroeder, Machine learning, LumenVox, Lifeline (video game), Lawrence Rabiner, Language model, Kinect, Keyword spotting, Jott, Interactive voice response, Hidden Markov model, Hands-free computing, HTK (software), Eurofighter Typhoon, Dynamic time warping, Digital dictation, DARPA, Constructed language, Computer engineering, Computational finance, Carnegie Mellon University, Cache language model, Audio mining, Audio-visual speech recognition, Artificial intelligence, Articulatory speech recognition, Applications of artificial intelligence, Andrew Sears, Acoustic model
Author: Gerard Chollet
Publisher: Springer Science & Business Media
ISBN: 1447108450
Category : Technology & Engineering
Languages : en
Pages : 352
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Book Description
Speech Processing, Recognition and Artificial Neural Networks contains papers from leading researchers and selected students, discussing the experiments, theories and perspectives of acoustic phonetics as well as the latest techniques in the field of spe ech science and technology. Topics covered in this book include; Fundamentals of Speech Analysis and Perceptron; Speech Processing; Stochastic Models for Speech; Auditory and Neural Network Models for Speech; Task-Oriented Applications of Automatic Speech Recognition and Synthesis.
Author: Gokhan Tur
Publisher: John Wiley & Sons
ISBN: 1119993946
Category : Language Arts & Disciplines
Languages : en
Pages : 443
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Book Description
Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.
Author: Chin-Hui Lee
Publisher: Springer Science & Business Media
ISBN: 1461313678
Category : Technology & Engineering
Languages : en
Pages : 524
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Book Description
Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use of dynamic, programming based heuristic search methods to find the best word sequence in the lexical network corresponding to the spoken utterance. Automatic Speech and Speaker Recognition: Advanced Topics groups together in a single volume a number of important topics on speech and speaker recognition, topics which are of fundamental importance, but not yet covered in detail in existing textbooks. Although no explicit partition is given, the book is divided into five parts: Chapters 1-2 are devoted to technology overviews; Chapters 3-12 discuss acoustic modeling of fundamental speech units and lexical modeling of words and pronunciations; Chapters 13-15 address the issues related to flexibility and robustness; Chapter 16-18 concern the theoretical and practical issues of search; Chapters 19-20 give two examples of algorithm and implementational aspects for recognition system realization. Audience: A reference book for speech researchers and graduate students interested in pursuing potential research on the topic. May also be used as a text for advanced courses on the subject.
Author: Björn Schuller
Publisher: John Wiley & Sons
ISBN: 9781119971368
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human speech and language. It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. C overs the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system integration. Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. Outlines machine learning approaches including static, dynamic and context‑sensitive algorithms for classification and regression. Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus.
Author: Joseph Keshet
Publisher: John Wiley & Sons
ISBN: 9780470742037
Category : Technology & Engineering
Languages : en
Pages : 268
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Book Description
This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.
