Title :
Frame recursive dynamic mean bias removal technique for robust environment-aware speech recognition in real world applications
Author :
Chowdhury, Md Fozur Rahman ; Selouani, Sid-Ahmed ; Shaughnessy, Douglas O.
Author_Institution :
INRS, Univ. du Quebec, Montréal, QC, Canada
Abstract :
In this paper, we investigated and simulated the frame recursive dynamic mean bias removing technique in the cepstral domain with a time smoothing parameter in order to improve the robustness of automatic speech recognition (ASR) in realtime environments. The objective of this simulation was to examine the suitability of the frame recursive cepstral mean bias removal technique as a part of an effort to develop single channel joint additive noise and channel distortion compensation (JAC) algorithm in feature space for real-world applications. The Aurora2 speech corpus was used in this simulation. The simulation results show that the frame recursive dynamic mean bias removal technique performs better in real-time scenarios compared to conventional approaches (non real-time) to improve the robustness of ASR under noisy conditions.
Keywords :
noise; speech recognition; ASR; automatic speech recognition; frame recursive dynamic mean bias removal technique; real world applications; realtime environments; robust environment aware speech recognition; time smoothing parameter; Cepstral analysis; Hidden Markov models; Real time systems; Signal to noise ratio; Speech; Speech recognition; Frame recursive bias removal; distributed speech recognition; feature compensation; joint additive noise and channel distortion compensation; robust speech recognition;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2010 23rd Canadian Conference on
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-5376-4
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2010.5575258