EUROSPEECH 2003 - INTERSPEECH 2003
This paper presents experiments of noise robust ASR on the Aurora4 database. The database is designed to test large vocabulary systems in presence of noise and channel distortions. A number of different model-based and signal-based noise robustness techniques have been tested. Results show that it is difficult to design a technique that is superior in every condition. Because of this we combined different techniques to improve results. Best results have been obtained when short time compensation / normalization methods are combined with long term environmental adaptation and robust acoustic models. The best average error rate obtained over the 52 conditions is 30.8%. This represents a 40% relative improvement compared to the baseline results .
Bibliographic reference. Rigazio, Luca / Nguyen, Patrick / Kryze, David / Junqua, Jean-Claude (2003): "Large vocabulary noise robustness on Aurora4", In EUROSPEECH-2003, 345-348.