Diese Bachelorarbeit umfasst die Themen Acoustic Echo Cancellation und Speech
Separation. Zunächst wird ein Acoustic Echo Cancellation System in Matlab im-
plementiert und anschließend werden Teile dieses Systems für die Sprachtrennung
genutzt. Die Experimente zur Sprachtrennung werden mit einem automatischen
Spracherkennungsystem ausgewertet und mit Hilfe des benutzten Filters ist eine
deutliche Verbesserung der Sprachtrennung zu beobachten. Das System erreicht
eine Word-Error-Rate von 44,20 %. Dies entspricht einer Verbesserung von 24 %
im Vergleich zum Superdirective Beamformer.
Contents
Danksagung
Abstract
1 Introduction
1.1 Motivation
1.2 Overview
2 Digital Filters
2.1 FIR-Filter
2.2 IIR-Filter
2.3 Wiener Filter
2.3.1 Solution in the Time Domain
2.3.2 Solution in the Frequency Domain
2.4 Adaptive Filters
2.4.1 LMS Algorithm
2.4.2 NLMS Algorithm
3 Acoustic Echo Cancellation
3.1 Problem Definition
3.2 Adaptive Filter
3.3 Voice Activity Detection VAD
3.4 Pre-Emphasis/De-Emphasis
3.5 Residual Echo Suppression
3.6 Matlab Results
4 Speech Separation
4.1 Beamforming
4.1.1 Diffuse Noise Field and Directivity
4.1.2 Delay-and-Sum Beamformer
4.1.3 MVDR Beamformer
4.1.4 Superdirective Beamformer
4.1.5 Zelinski Postfilter
4.2 Echo Suppression Postfilter ES
5 Experiments
5.1 Corpus
5.2 Automatic Speech Recognition System ASR
5.3 Experiments and Results
5.3.1 Superdirective Beamformer
5.3.2 Zelinski Postfilter
5.3.3 Echo Suppression Filter
5.3.4 Row of Echo Suppression Systems
5.3.5 Zelinski Postfilter and Echo Suppression System
6 Summary, Conclusions and Future Work
- Quote paper
- Christian Siegwart (Author), 2012, Improving Speech Separation by Acoustic Echo Cancellation, Munich, GRIN Verlag, https://www.grin.com/document/207359
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