Real World Speech Processing
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Real World Speech Processing
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Author : Jhing-Fa Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-03-31
Real World Speech Processing written by Jhing-Fa Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-31 with Technology & Engineering categories.
Real World Speech Processing brings together in one place important contributions and up-to-date research results in this fast-moving area. The contributors to this work were selected from the leading researchers and practitioners in this field. The work, originally published as Volume 36, Numbers 2-3 of the Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, will be valuable to anyone working or researching in the field of speech processing. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.
Automatic Speech Recognition
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Author : Dong Yu
language : en
Publisher: Springer
Release Date : 2014-11-11
Automatic Speech Recognition written by Dong Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-11 with Technology & Engineering categories.
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
Real World Natural Language Processing
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Author : Masato Hagiwara
language : en
Publisher: Simon and Schuster
Release Date : 2021-12-14
Real World Natural Language Processing written by Masato Hagiwara and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-14 with Computers categories.
Training computers to interpret and generate speech and text is a monumental challenge, and the payoff for reducing labor and improving human/computer interaction is huge! The field of Natural language processing (NLP) is advancing rapidly, with countless new tools and practices. This unique book offers an innovative collection of NLP techniques with applications in machine translation, voice assitants, text generation and more. "Real-world natural language processing" shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you'll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you'll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process.
Deep Learning For Nlp And Speech Recognition
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Speech Processing In Modern Communication
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Author : Israel Cohen
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-18
Speech Processing In Modern Communication written by Israel Cohen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-18 with Technology & Engineering categories.
Modern communication devices, such as mobile phones, teleconferencing systems, VoIP, etc., are often used in noisy and reverberant environments. Therefore, signals picked up by the microphones from telecommunication devices contain not only the desired near-end speech signal, but also interferences such as the background noise, far-end echoes produced by the loudspeaker, and reverberations of the desired source. These interferences degrade the fidelity and intelligibility of the near-end speech in human-to-human telecommunications and decrease the performance of human-to-machine interfaces (i.e., automatic speech recognition systems). The proposed book deals with the fundamental challenges of speech processing in modern communication, including speech enhancement, interference suppression, acoustic echo cancellation, relative transfer function identification, source localization, dereverberation, and beamforming in reverberant environments. Enhancement of speech signals is necessary whenever the source signal is corrupted by noise. In highly non-stationary noise environments, noise transients, and interferences may be extremely annoying. Acoustic echo cancellation is used to eliminate the acoustic coupling between the loudspeaker and the microphone of a communication device. Identification of the relative transfer function between sensors in response to a desired speech signal enables to derive a reference noise signal for suppressing directional or coherent noise sources. Source localization, dereverberation, and beamforming in reverberant environments further enable to increase the intelligibility of the near-end speech signal.
Digital Signal Processing
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Author : Li Tan
language : en
Publisher: Academic Press
Release Date : 2018-10-02
Digital Signal Processing written by Li Tan and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-02 with Technology & Engineering categories.
Digital Signal Processing: Fundamentals and Applications, Third Edition, not only introduces students to the fundamental principles of DSP, it also provides a working knowledge that they take with them into their engineering careers. Many instructive, worked examples are used to illustrate the material, and the use of mathematics is minimized for an easier grasp of concepts. As such, this title is also useful as a reference for non-engineering students and practicing engineers. The book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as PCM, μ-law, ADPCM, and multi-rate DSP, over-sampling ADC subband coding, and wavelet transform. - Covers DSP principles with an emphasis on communications and control applications - Includes chapter objectives, worked examples, and end-of-chapter exercises that aid the reader in grasping key concepts and solving related problems - Provides an accompanying website with MATLAB programs for simulation and C programs for real-time DSP - Presents new problems of varying types and difficulties
Adaptive Signal Processing
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Author : Jacob Benesty
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Adaptive Signal Processing written by Jacob Benesty and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Technology & Engineering categories.
By adaptive signal processing, we mean, in general, adaptive ?ltering.In- known environments where we need to model, identify, or track time-varying channels, adaptive ?ltering has been proven to be an e?ective and powerful tool. As a result, this tool is now in use in many di?erent ?elds. Since the invention, by Widrow and Ho? in 1959, of one of the ?rst ad- tive ?lters, the so-called least-mean-square, many applications appeared to have the potential to use this fundamental concept. While the number of - plications (using adaptive algorithms) has been (and keeps) ?ourishing with time, thanks to several successes, the need for more sophisticated adaptive algorithms became obvious as real-world problems are more complex and more demanding. Even though the theory of adaptive ?ltering is already a well-established topic in signal processing, new and improved concepts are discovered every year by researchers. Some of these recent approaches are discussed in this book. The goal of this book is to provide, for the ?rst time, a reference to the hottest real-world applications where adaptive ?ltering techniques play an important role. To do so, we invited top researchers in di?erent ?elds to c- tribute chapters addressing their speci?c topic of study. Thousands of pages wouldprobablynotbe enoughto describeallthe practicalapplicationsutil- ing adaptive algorithms. Therefore, we limited the topics to some important applications in acoustics, speech, wireless, and networking, where research is still very active and open.
Speech Processing
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Author : Li Deng
language : en
Publisher: CRC Press
Release Date : 2018-10-03
Speech Processing written by Li Deng and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Technology & Engineering categories.
Based on years of instruction and field expertise, this volume offers the necessary tools to understand all scientific, computational, and technological aspects of speech processing. The book emphasizes mathematical abstraction, the dynamics of the speech process, and the engineering optimization practices that promote effective problem solving in this area of research and covers many years of the authors' personal research on speech processing. Speech Processing helps build valuable analytical skills to help meet future challenges in scientific and technological advances in the field and considers the complex transition from human speech processing to computer speech processing.
Speech Processing In Embedded Systems
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Author : Priyabrata Sinha
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-12-01
Speech Processing In Embedded Systems written by Priyabrata Sinha and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-01 with Technology & Engineering categories.
Speech Processing has rapidly emerged as one of the most widespread and well-understood application areas in the broader discipline of Digital Signal Processing. Besides the telecommunications applications that have hitherto been the largest users of speech processing algorithms, several non-traditional embedded processor applications are enhancing their functionality and user interfaces by utilizing various aspects of speech processing. "Speech Processing in Embedded Systems" describes several areas of speech processing, and the various algorithms and industry standards that address each of these areas. The topics covered include different types of Speech Compression, Echo Cancellation, Noise Suppression, Speech Recognition and Speech Synthesis. In addition this book explores various issues and considerations related to efficient implementation of these algorithms on real-time embedded systems, including the role played by processor CPU and peripheral functionality.
Speech Recognition Synthesis From Basics To Advanced Techniques
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Author : Navneet Singh
language : en
Publisher: Navneet Singh
Release Date :
Speech Recognition Synthesis From Basics To Advanced Techniques written by Navneet Singh and has been published by Navneet Singh this book supported file pdf, txt, epub, kindle and other format this book has been release on with Antiques & Collectibles categories.
Part 1: Introduction to Speech Technology Chapter 1: Understanding Speech Technology Overview of speech recognition and synthesis Historical evolution of speech technology Real-world applications and significance Chapter 2: Basic Concepts in Speech Acoustic features: Pitch, tone, and frequency Phonetics and phonology in speech processing How humans produce and perceive speech Part 2: Speech Recognition Chapter 3: Introduction to Speech Recognition What is speech recognition? Key challenges in speech recognition Components of a speech recognition system Chapter 4: Signal Processing for Speech Recognition Preprocessing: Noise reduction, feature extraction Mel-Frequency Cepstral Coefficients (MFCC) Fourier Transform and its role in speech analysis Chapter 5: Speech Recognition Models Hidden Markov Models (HMM) Gaussian Mixture Models (GMM) Neural Networks for speech recognition (Deep Learning in ASR) Chapter 6: Automatic Speech Recognition (ASR) Pipeline Feature extraction and encoding Acoustic modeling and language modeling Decoding and output generation Practical tools and frameworks (e.g., CMU Sphinx, Kaldi, DeepSpeech) Chapter 7: Real-World Applications of Speech Recognition Voice assistants (Siri, Alexa, Google Assistant) Speech-to-text for transcription Speech recognition in healthcare, automotive, and more Part 3: Speech Synthesis Chapter 8: Introduction to Speech Synthesis What is speech synthesis (Text-to-Speech, TTS)? Basic principles of speech generation Early techniques vs. modern approaches Chapter 9: Text-to-Speech (TTS) Models Rule-based synthesis Concatenative synthesis Statistical Parametric Speech Synthesis Deep Learning-based TTS (Tacotron, WaveNet) Chapter 10: Signal Processing for Speech Synthesis Preprocessing of text input: Tokenization, phonetic conversion Prosody generation (intonation, rhythm, stress) Formant synthesis and waveform generation Chapter 11: Real-World Applications of Speech Synthesis Virtual assistants and accessibility tools Speech synthesis in entertainment and media Voiceovers, podcasts, and audiobook generation Part 4: Advanced Topics in Speech Technology Chapter 12: Multilingual and Accented Speech Recognition Challenges in multilingual speech recognition Language models and accent adaptation Building a multilingual ASR system Chapter 13: Deep Learning in Speech Technology Deep neural networks for speech recognition and synthesis Recurrent Neural Networks (RNNs), LSTMs, and GRUs Transfer learning and pre-trained models Chapter 14: Enhancing Speech Recognition and Synthesis with AI Voice cloning and speaker recognition Speech enhancement: Noise suppression and echo cancellation Emotion recognition in speech Part 5: Practical Applications and Future Directions Chapter 15: Developing Your Own Speech Recognition and Synthesis System Tools and libraries for building your own systems (e.g., Kaldi, PyTorch, TensorFlow) Designing a simple ASR and TTS system Challenges and troubleshooting Chapter 16: Future of Speech Recognition and Synthesis Integration with IoT and smart devices Voice biometrics and security Ethical considerations and privacy in speech tech