Title :
On a robust ASR based on complex AR speech analysis
Author :
Keita Higa;Keiichi Funaki
Author_Institution :
Graduate School of Science and Engineering, University of the Ryukyus, Okinawa, Japan
Abstract :
The advanced front-end (AFE) for automatic speech recognition (ASR) was standardized by the European Telecommunications Standards Institute (ETSI). The AFE provides speech enhancement realized by an iterative Wiener filter (IWF) in which a smoothed FFT spectrum over adjacent frames is used to design the filter. We have previously proposed robust time-varying complex AR (TV-CAR) speech analysis and evaluated the performance of speech processing such as F0 estimation and speech enhancement. TV-CAR analysis can estimate more accurate spectrum than FFT, especially in low frequencies because of the nature of the analytic signal. In addition, the TV-CAR can estimate more accurate speech spectrum against additive noise. In this paper, the time-invariant version of wide-band TV-CAR analysis is introduced to the IWF in the AFE and is evaluated using the CENSREC-2 database.
Keywords :
"Speech","Speech enhancement","Speech recognition","Additive noise","Robustness","Frequency estimation","Hidden Markov models"
Conference_Titel :
Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2015 Asia-Pacific
DOI :
10.1109/APSIPA.2015.7415470