EUROSPEECH 2001 Scandinavia
7th European Conference on Speech Communication and Technology

Aalborg, Denmark
September 3-7, 2001


Modeling the Mixtures of Known Noise and Unknown Unexpected Noise for Robust Speech Recognition

Ji Ming, Peter Jancovic, Philip Hanna, Darryl Stewart

Queens University of Belfast, UK

Real-world noise may be a mixture of known or trainable noise and unknown unexpected noise. This paper investigates the combination of the conventional noise-reduction techniques with the probabilistic union model to deal with this type of mixed noise for robust speech recognition. In particular, we have developed a multi-environment system to remove the known or trainable acoustic mismatch across different environments. The novelty of this system, in contrast to other multi-environment models, is that the acoustic model for each environment is built upon the probabilistic union model, so that this system is also capable of accommodating further unknown unexpected noise within a specific environment. We have tested the new system for connected digit recognition in different environments, each involving an environment-specific noise and some unknown untrained noise. The results indicate that the new system offers significantly improved performance for the environments involving unknown additional noise, in comparison to a baseline multi-environment system.

Full Paper

Bibliographic reference.  Ming, Ji / Jancovic, Peter / Hanna, Philip / Stewart, Darryl (2001): "Modeling the mixtures of known noise and unknown unexpected noise for robust speech recognition", In EUROSPEECH-2001, 1111-1114.