Audio source separation and speech enhancement

Audio Source Separation

✍ Shoji Makino (eds.) 📂 Library 📅 2018 🏛 Springer International Publishing 🌐 English

This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negati

Speech and Audio Processing for Coding,

📁 Speech and Audio Processing for Coding, Enhancement and Recognition

✍ Tokunbo Ogunfunmi, Roberto Togneri, Madihally (Sim) Narasimha (eds.) 📂 Library 📅 2015 🏛 Springer-Verlag New York 🌐 English

This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for speech and speaker recognition with an overview of the key innovations in these areas. Key re

Time-Domain Beamforming and Blind Source

📁 Time-Domain Beamforming and Blind Source Separation: Speech Input in the Car Environment

✍ Julien Bourgeois, Wolfgang Minker (eds.) 📂 Library 📅 2009 🏛 Springer US 🌐 English

Time-Domain Beamforming and Blind Source Separation addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. While existing techniques require a Double-Talk Detector (DTD) that interrupts the adaptat

Time-domain beamforming and blind source

📁 Time-domain beamforming and blind source separation: speech input in the car environment

✍ Julien Bourgeois, Wolfgang Minker (eds.) 📂 Library 📅 2009 🏛 Springer US 🌐 English

Time-Domain Beamforming and Blind Source Separation addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. While existing techniques require a Double-Talk Detector (DTD) that interrupts the adaptat

Speech Enhancement

📁 Speech Enhancement

✍ Prof. Dr. Jacob Benesty, Shoji Makino, Jingdong Chen (auth.) 📂 Library 📅 2005 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be

Source Modeling Techniques for Quality E

📁 Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis

✍ K. Sreenivasa Rao, N. P. Narendra 📂 Library 📅 2019 🏛 Springer International Publishing 🌐 English

This book presents a statistical parametric speech synthesis (SPSS) framework for developing a speech synthesis system where the desired speech is generated from the parameters of vocal tract and excitation source. Throughout the book, the authors discuss novel source modeling techniques to en

Audio source separation and speech enhancement

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