Towards language independent acoustic modeling

We describe procedures and experimental results using speech from diverse source languages to build an ASR system for a single target language. This work is intended to improve ASR in languages for which large amounts of training data are not available. We have developed both knowledge-based and aut...

Full description

Saved in:
Bibliographic Details
Main Authors: Byrne, W., Beyerlein, P., Huerta, J.M., Khudanpur, S., Marthi, B., Morgan, J., Peterek, N., Picone, J., Vergyri, D., Wang, T.
Format: Conference Proceeding
Language:English
Subjects:
Acoustical engineering
Asia
Automatic speech recognition
Europe
Hidden Markov models
Loudspeakers
Natural languages
Speech recognition
Statistical analysis
Training data
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We describe procedures and experimental results using speech from diverse source languages to build an ASR system for a single target language. This work is intended to improve ASR in languages for which large amounts of training data are not available. We have developed both knowledge-based and automatic methods to map phonetic units from the source languages to the target language. We employed HMM adaptation techniques and discriminative model combination to combine acoustic models from the individual source languages for recognition of speech in the target language. Experiments are described in which Czech Broadcast News is transcribed using acoustic models trained from small amounts of Czech read speech augmented by English, Spanish, Russian, and Mandarin acoustic models.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2000.859138