8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Advanced Front-End for Robust Speech Recognition in Extremely Adverse Environments

Dimitrios Dimitriadis (1), Jose C. Segura (2), Luz Garcia (2), Alexandros Potamianos (3), Petros Maragos (1), Vassilis Pitsikalis (1)

(1) National Technical University of Athens, Greece
(2) Universidad de Granada, Spain
(3) Technical University of Crete, Greece

In this paper, a unified approach to speech enhancement, feature extraction and feature normalization for speech recognition in adverse recording conditions is presented. The proposed front-end system consists of several different, independent, processing modules. Each of the algorithms contained in these modules has been independently applied to the problem of speech recognition in noise, significantly improving the recognition rates. In this work, these algorithms are merged in a single front-end and their combined performance is demonstrated. Specifically, the proposed advanced front-end extracts noise-invariant features via the following modules: Wiener filtering, voice-activity detection, robust feature extraction (nonlinear modulation or fractal features), parameter equalization and frame-dropping. The advanced front-end is applied to extremely adverse environments where most feature extraction schemes fail. We show that by combining speech enhancement, robust feature extraction and feature normalization up to a fivefold error rate reduction can be achieved for certain tasks.

Full Paper

Bibliographic reference.  Dimitriadis, Dimitrios / Segura, Jose C. / Garcia, Luz / Potamianos, Alexandros / Maragos, Petros / Pitsikalis, Vassilis (2007): "Advanced front-end for robust speech recognition in extremely adverse environments", In INTERSPEECH-2007, 2425-2428.