Real-Time speech recognition in a multi-talker reverberated acoustic scenario

Authors:
Rudy Rotili;Emanuele Principi;Stefano Squartini;Björn Schuller
Affiliations:
A3LAB, Department of Biomedics, Electronics and Telecommunications, Università Politecnica delle Marche, Ancona, Italy;A3LAB, Department of Biomedics, Electronics and Telecommunications, Università Politecnica delle Marche, Ancona, Italy;A3LAB, Department of Biomedics, Electronics and Telecommunications, Università Politecnica delle Marche, Ancona, Italy;Institute for Human-Machine Communication, Technische Universität München, Munich, Germany
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

Citing 2
Cited 0

Speech Recognition over Digital Channels: Robustness And Standards

Speech Recognition over Digital Channels: Robustness And Standards
A class of frequency-domain adaptive approaches to blind multichannel identification

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a real-time algorithmic framework for Automatic Speech Recognition (ASR) in presence of multiple sources in reverberated environment. The addressed real-life acoustic scenario definitely asks for a robust signal processing solution to reduce the impact of source mixing and reverberation on ASR performances. Here the authors show how the implemented approach allows to improve recognition accuracies under real-time processing constraints and overlapping distant-talking speakers. A suitable database has been generated on purpose, by adapting an existing large vocabulary continuous speech recognition (LVCSR) corpus to deal with the acoustic conditions under study.