-PDF Download- Neutrosophic Speech Recognition Algorithm For Speech Under Stress By Machine Learning EBOOK

Neutrosophic speech recognition Algorithm for speech under stress by Machine learning

Author: D. Nagarajan

Publisher: Infinite Study

Published: 2023-01-01

Total Pages: 12

ISBN-13:

It is well known that the unpredictable speech production brought on by stress from the task at hand has a significant negative impact on the performance of speech processing algorithms. Speech therapy benefits from being able to detect stress in speech. Speech processing performance suffers noticeably when perceptually produced stress causes variations in speech production. Using the acoustic speech signal to objectively characterize speaker stress is one method for assessing production variances brought on by stress. Real-world complexity and ambiguity make it difficult for decision-makers to express their conclusions with clarity in their speech. In particular, the Neutrosophic speech algorithm is used to encode the language variables because they cannot be computed directly. Neutrosophic sets are used to manage indeterminacy in a practical situation. Existing algorithms are used except for stress on Neutrosophic speech recognition. The creation of algorithms that calculate, categorize, or differentiate between different stress circumstances. Understanding stress and developing strategies to combat its effects on speech recognition and human-computer interaction system are the goals of this recognition.

A Convoloutional Neural Network model based on Neutrosophy for Noisy Speech Recognition

Author: Elyas Rashno

Publisher: Infinite Study

Published:

Total Pages: 6

ISBN-13:

DOWNLOAD EBOOK →

Convolutional neural networks are sensitive to unknown noisy condition in the test phase and so their performance degrades for the noisy data classification task including noisy speech recognition. In this research, a new convolutional neural network (CNN) model with data uncertainty handling; referred as NCNN (Neutrosophic Convolutional Neural Network); is proposed for classification task.

New Era for Robust Speech Recognition

Author: Shinji Watanabe

Publisher: Springer

Published: 2017-10-30

Total Pages: 433

ISBN-13: 331964680X

DOWNLOAD EBOOK →

This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.

Speech Recognition

Author: Fouad Sabry

Publisher: One Billion Knowledgeable

Published: 2022-07-10

Total Pages: 435

ISBN-13:

DOWNLOAD EBOOK →

What Is Speech Recognition Computer science and computational linguistics have spawned a subfield known as speech recognition, which is an interdisciplinary field that focuses on the development of methodologies and technologies that enable computers to recognize and translate spoken language into text. The primary advantage of this is that the text can then be searched. Automatic speech recognition, sometimes abbreviated as ASR, is another name for it, as is computer speech recognition and voice to text (STT). The domains of computer science, linguistics, and computer engineering are all represented in its incorporation of knowledge and study. Speech synthesis is the process of doing things backwards. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Speech recognition Chapter 2: Computational linguistics Chapter 3: Natural language processing Chapter 4: Speech processing Chapter 5: Speech synthesis Chapter 6: Vector quantization Chapter 7: Pattern recognition Chapter 8: Lawrence Rabiner Chapter 9: Recurrent neural network Chapter 10: Julius (software) Chapter 11: Long short-term memory Chapter 12: Time delay neural network Chapter 13: Types of artificial neural networks Chapter 14: Deep learning Chapter 15: Nelson Morgan Chapter 16: Sinsy Chapter 17: Outline of machine learning Chapter 18: Steve Young (academic) Chapter 19: Tony Robinson (speech recognition) Chapter 20: Voice computing Chapter 21: Joseph Keshet (II) Answering the public top questions about speech recognition. (III) Real world examples for the usage of speech recognition in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of speech recognition' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of speech recognition.

Automatic Speech Recognition

Author: Dong Yu

Publisher: Springer

Published: 2014-11-11

Total Pages: 329

ISBN-13: 1447157796

DOWNLOAD EBOOK →

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.

Speech Recognition

Author: Fouad Sabry

Publisher: One Billion Knowledgeable

Published: 2023-07-05

Total Pages: 149

ISBN-13:

DOWNLOAD EBOOK →

What Is Speech Recognition Computer science and computational linguistics include a subfield called speech recognition that focuses on the development of approaches and technologies that enable computers to recognize spoken language and translate it into text. Speech recognition is an interdisciplinary subfield of computer science. It is also known as computer speech recognition (CSR) and speech to text (STT). Another name for it is automatic speech recognition (ASR). The domains of computer science, linguistics, and computer engineering are all represented in its incorporation of knowledge and study. Speech synthesis is the process of doing things backwards. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Speech recognition Chapter 2: Computational linguistics Chapter 3: Natural language processing Chapter 4: Speech processing Chapter 5: Pattern recognition Chapter 6: Language model Chapter 7: Deep learning Chapter 8: Recurrent neural network Chapter 9: Long short-term memory Chapter 10: Voice computing (II) Answering the public top questions about speech recognition. (III) Real world examples for the usage of speech recognition in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of speech recognition' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of speech recognition.

Speech Recognition Under Stress

Author: Yonglian Wang

Publisher:

Published: 2009

Total Pages: 100

ISBN-13:

DOWNLOAD EBOOK →

In this dissertation, three techniques--dynamic time warping (DTW), hidden Markov models (HMM), and hidden control neural network (HCNN)--are utilized to realize talker-independent isolated word recognition. When stress (angry, question, and soft) is induced into normal talking speech, speech recognition performance degrades greatly. Therefore hypothesis driven approach, a stress compensation technique is introduced to cancel the distortion caused by stress. The characteristic feature analysis has been carried out in three domains: pitch, intensity, and glottal spectrum. Our results showed that HMM technique can achieve 91% recognition rate for normal speech; however, the recognition rate dropped to 60% for angry stress condition, 65% for question stress condition, and 76% for soft stress condition. After compensation was applied for the cepstral tilts, the recognition rate increased by 10% for angry stress condition, 8% for question stress condition, and 4% for soft stress condition. Finally, HCNN technique increased the recognition rate to 90% for angry stress condition and it also differentiated the angry stress from other stress group.

Deep Learning for Speech Classification and Speaker Recognition

Author: Muhammad Muneeb Saleem

Publisher:

Published: 2014

Total Pages:

ISBN-13:

DOWNLOAD EBOOK →

Deep learning is the state-of-the-art technique in machine learning with applications in speech recognition. In this study, an efficient system is formulated to process large amounts of speech data within the deep learning framework by harnessing the parallel processing power of High-Performance Computing oriented Graphics Processing Unit (GPU). This thesis focuses on applications of this approach to address stressed speech classification as well as discrimination between different flavors of noise-free speech under Lombard Effect. Different architectures of deep neural networks (DNN) are explored to build state-of-the-art classifiers for detection and classification of stressed speech and Lombard Effect flavors. Furthermore, applications of deep networks are explored to improve current state-of-the-art speaker recognition systems. Further integration of discriminative deep architectures is accomplished for unsupervised methods in training front-ends for Speaker Recognition Evaluation systems.

Interval Neutrosophic Sets and Logic: Theory and Applications in Computing

Author: Haibin Wang

Publisher: Infinite Study

Published: 2005

Total Pages: 99

ISBN-13: 1931233942

DOWNLOAD EBOOK →

This book presents the advancements and applications of neutrosophics, which are generalizations of fuzzy logic, fuzzy set, and imprecise probability. The neutrosophic logic, neutrosophic set, neutrosophic probability, and neutrosophic statistics are increasingly used in engineering applications (especially for software and information fusion), medicine, military, cybernetics, physics.In the last chapter a soft semantic Web Services agent framework is proposed to facilitate the registration and discovery of high quality semantic Web Services agent. The intelligent inference engine module of soft semantic Web Services agent is implemented using interval neutrosophic logic.

2021 International Conference on Decision Aid Sciences and Application (DASA)

Author: IEEE Staff

Publisher:

Published: 2021-12-07

Total Pages:

ISBN-13: 9781665416351

DOWNLOAD EBOOK →

The International Conference on Decision Aid Sciences and Applications is an interdisciplinary forum for the presentation of recent developments and applications in the field of Decision Aid Sciences This Conference aims to disseminate recent models and techniques related to decision making and decision processes through researchers and practitioners from all over the world There will be rigorous plenary talks by invited speakers as well as contributed talks A Workshop for postgraduate students at the early stage of their dissertation research will be organized during the conference and will include a variety of panels as well as, practical sessions on developing dissertation proposals, launching academic careers, and a meet the editors session