Unsupervised noise reduction scheme for voice-based information retrieval in mobile environments

Abstract

This study proposes an unsupervised noise reduction scheme that improves the performance of voice-based information retrieval tasks in mobile environments. Various types of noises could interfere with speech processing tasks, and noise reduction has become an essential technique in this field. In particular, noise reduction needs to be carefully processed in mobile environments based on the speech coding system and the client-server architecture. In this study, we propose an effective noise reduction scheme that employs the adaptive comb filtering technique. A way of directly using several codec parameters during the filtering process is also investigated. In particular, we modify the conventional comb filter using line spectral pair parameters. To verify the efficiency of the proposed noise reduction approach, we conducted speech recognition experiments using the Aurora2 database. Our approach provided superior recognition performance under various noise conditions compared to the conventional techniques.

Abordagem de Simulação de Ruídos para Avaliação do Reconhecimento de Locutores em Ambientes Ruidosos

“…Esses ruídos possuem potencial para impactar negativamente qualquer tipo de processamento de sinais. Especialmente, para dispositivos mobile, a acurácia do processamento de voz é reduzida por conta dos ruídos [9].…”