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 "...
Κύριοι συγγραφείς: | , , |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2005.
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Σειρά: | Signals and Communication Technology
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.