Speech Recognition Synthesis From Basics To Advanced Techniques
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Speech Recognition & Synthesis: From Basics to Advanced Techniques
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
Advanced Methods, Techniques, and Applications in Modeling and Simulation
Author: Jong-Hyun Kim
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-10-19
This book is a compilation of research accomplishments in the fields of modeling, simulation, and their applications, as presented at AsiaSim 2011 (Asia Simulation Conference 2011). The conference, held in Seoul, Korea, November 16–18, was organized by ASIASIM (Federation of Asian Simulation Societies), KSS (Korea Society for Simulation), CASS (Chinese Association for System Simulation), and JSST (Japan Society for Simulation Technology). AsiaSim 2011 provided a forum for scientists, academicians, and professionals from the Asia-Pacific region and other parts of the world to share their latest exciting research findings in modeling and simulation methodologies, techniques, and their tools and applications in military, communication network, industry, and general engineering problems.
Advanced Techniques in Computing Sciences and Software Engineering
Author: Khaled Elleithy
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-03-10
Advanced Techniques in Computing Sciences and Software Engineering includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Software Engineering, Computer Engineering, and Systems Engineering and Sciences. Advanced Techniques in Computing Sciences and Software Engineering includes selected papers form the conference proceedings of the International Conference on Systems, Computing Sciences and Software Engineering (SCSS 2008) which was part of the International Joint Conferences on Computer, Information and Systems Sciences and Engineering (CISSE 2008).