Title :
Whispery Speech Recognition using Adapted Articulatory Features
Author :
Jou, Szu-Chen ; Schultz, Tanja ; Waibel, Alex
Author_Institution :
Interactive Syst. Labs., Carnegie Mellon Univ., Pittsburgh, PA, USA
fDate :
March 18-23, 2005
Keywords :
adaptive signal detection; error statistics; feature extraction; hidden Markov models; learning (artificial intelligence); low-pass filters; maximum likelihood decoding; maximum likelihood detection; maximum likelihood estimation; regression analysis; signal sampling; speech recognition; adapted articulatory features; articulatory feature detection; decoding; downsampling re-training; feature-space adaptation; linear multivariate regression; maximum likelihood linear regression; senone-based HMM models; sigmoidal low-pass filter; stream architecture; throat microphone; whispery speech recognition; word error rate; Acoustic signal detection; Automatic speech recognition; Computer vision; Detectors; Hidden Markov models; Interactive systems; Microphones; Robustness; Speech processing; Speech recognition;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1415287