Paper: Cross-Lingual Language Modeling with Syntactic Reordering for Low-Resource Speech Recognition

ACL ID D12-1070
Title Cross-Lingual Language Modeling with Syntactic Reordering for Low-Resource Speech Recognition
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

This paper proposes cross-lingual language modeling for transcribing source resource- poor languages and translating them into tar- get resource-rich languages if necessary. Our focus is to improve the speech recognition performance of low-resource languages by leveraging the language model statistics from resource-rich languages. The most challeng- ing work of cross-lingual language modeling is to solve the syntactic discrepancies between the source and target languages. We therefore propose syntactic reordering for cross-lingual language modeling, and present a first result that compares inversion transduction grammar (ITG) reordering constraints to IBM and lo- cal constraints in an integrated speech tran- scription and translation system. Evaluations on resource-poor Cantonese speech tr...