Paper Info
Title
A New Speech Enhancement: Speech Stream Segregation
Abstract
Speech stream segregation is presented as a new speech enhancement for automatic speech recognition. Two issues an addressed: speech stream segregation from a mixture of sounds, and interfacing speech stream segregation with automatic speech recognition. Speech stream segregation is modeled as a process of extracting harmonic fragments, grouping these extracted harmonic fragments, and substituting non-harmonic residue for non-harmonic parts of groups. The main problem in interfacing speech stream segregation with HMM-based speech recognition is how to improve the degradation of recognition performance due to spectral distortion of segregated sounds, which is caused mainly by transfer function of a binaural input Our solution is to re-rain the parameters of HMM with training data binauralized for four directions. Experiments with 500 mixtures of two women's utterances of a word showed that the cumulative accuracy of word recognition up to the 10th candidate of each woman's utterance is, on average, 75%.
Year
DOI
Venue
1996
10.1109/ICSLP.1996.607281
ICSLP 96 - FOURTH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, PROCEEDINGS, VOLS 1-4
Keywords
Field
DocType
hidden markov models,layout,cumulant,feature extraction,speech processing,training data,automatic speech recognition,speech recognition,transfer function,word recognition,human voice
Speech enhancement,Speech processing,Human voice,Computer science,Audio mining,Word recognition,Speech recognition,Feature extraction,Hidden Markov model,Acoustic model
Conference
Citations 
PageRank 
References 
3
1.09
8
Authors
3
Name
Order
Citations
PageRank
Hiroshi G. Okuno12092233.19
Tomohiro Nakatani21327139.18
Takeshi Kawabata329651.73