International Symposium on Chinese Spoken Language Processing (ISCSLP 2002)

Taipei, Taiwan
August 23-24, 2002

An Investigation on Wireless Speech Recognition by Data Contamination and Robust Training Techniques

Wei-Tyng Hong (1), Ke-Shiu Chen (2)

(1) PenPower Technology, (2) Industrial Technology Research Institute, Hsinchu, Taiwan

This paper is concerned with the robust endpoint detection and noisy speech recognition over wireless network. Firstly, the MLP-based and GMM-based endpoint detection incorporated with data contamination and continuous spectral subtraction techniques were investigated. Then, for noisy wireless speech recognition, a combined technique of data contamination and robust training was proposed to separately model the environmental characteristics and phonetic information. According to the results from an abbreviated stock name recognition task, we observe that the proposed techniques has the potential to improve robustness not only on diverse data contaminated training data, but also on the unmatched noise-type condition between training and testing environments.

Full Paper

Bibliographic reference.  Hong, Wei-Tyng / Chen, Ke-Shiu (2002): "An investigation on wireless speech recognition by data contamination and robust training techniques", In ISCSLP 2002, paper 51.