Format

Send to

Choose Destination
J Acoust Soc Am. 2011 Oct;130(4):EL251-7. doi: 10.1121/1.3634122.

Automatic speech recognition using articulatory features from subject-independent acoustic-to-articulatory inversion.

Author information

1
Signal Analysis and Interpretation Laboratory, Department of Electrical Engineering, University of Southern California, Los Angeles, California 90089, USA. prasantg@usc.edu

Abstract

An automatic speech recognition approach is presented which uses articulatory features estimated by a subject-independent acoustic-to-articulatory inversion. The inversion allows estimation of articulatory features from any talker's speech acoustics using only an exemplary subject's articulatory-to-acoustic map. Results are reported on a broad class phonetic classification experiment on speech from English talkers using data from three distinct English talkers as exemplars for inversion. Results indicate that the inclusion of the articulatory information improves classification accuracy but the improvement is more significant when the speaking style of the exemplar and the talker are matched compared to when they are mismatched.

PMID:
21974500
PMCID:
PMC3189967
DOI:
10.1121/1.3634122
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for American Institute of Physics Icon for PubMed Central
Loading ...
Support Center