Lexical triggers and latent semantic analysis for cross-lingual language model adaptation
ACM Transactions on Asian Language Information Processing (TALIP)
A large-vocabulary continuous speech recognition system for Hindi
IBM Journal of Research and Development
Cross-lingual lexical triggers in statistical language modeling
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Multidialectal Spanish acoustic modeling for speech recognition
Speech Communication
Collecting and evaluating speech recognition corpora for nine Southern Bantu languages
AfLaT '09 Proceedings of the First Workshop on Language Technologies for African Languages
IEEE Transactions on Audio, Speech, and Language Processing
Collecting and evaluating speech recognition corpora for 11 South African languages
Language Resources and Evaluation
Toward acoustic models for languages with limited linguistic resources
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
ACM Transactions on Information Systems (TOIS)
Cross-Lingual Subspace Gaussian Mixture Models for Low-Resource Speech Recognition
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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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.