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Speech Enhancement
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 "...
| Call Number: | Libro Electrónico |
|---|---|
| Corporate Author: | |
| Other Authors: | , , |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2005.
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| Edition: | 1st ed. 2005. |
| Series: | Signals and Communication Technology,
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| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- Study of the Wiener Filter for Noise Reduction
- Statistical Methods for the Enhancement of Noisy Speech
- Single- and Multi-Microphone Spectral Amplitude Estimation Using a Super-Gaussian Speech Model
- From Volatility Modeling of Financial Time-Series to Stochastic Modeling and Enhancement of Speech Signals
- Single-Microphone Noise Suppression for 3G Handsets Based on Weighted Noise Estimation
- Signal Subspace Techniques for Speech Enhancement
- Speech Enhancement: Application of the Kalman Filter in the Estimate-Maximize (EM) Framework
- Speech Distortion Weighted Multichannel Wiener Filtering Techniques for Noise Reduction
- Adaptive Microphone Array Employing Spatial Quadratic Soft Constraints and Spectral Shaping
- Single-Microphone Blind Dereverberation
- Separation and Dereverberation of Speech Signals with Multiple Microphones
- Frequency-Domain Blind Source Separation
- Subband Based Blind Source Separation
- Real-Time Blind Source Separation for Moving Speech Signals
- Separation of Speech by Computational Auditory Scene Analysis.