Information Retrieval
The LIMSI Broadcast News transcription system
Speech Communication - Special issue on automatic transcription of broadcast news data
Triphone analysis: a combined method for the correction of orthographical and typographical errors
ANLC '88 Proceedings of the second conference on Applied natural language processing
Paraphrasing with bilingual parallel corpora
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Coping with out-of-vocabulary words: Open versus huge vocabulary asr
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
SRWS '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
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Constructing a pronunciation lexicon with variants in a fully automatic and language-independent way is a challenge, with many uses in human language technologies. Moreover, with the growing use of web data, there is a recurrent need to add words to existing pronunciation lexicons, and an automatic method can greatly simplify the effort required to generate pronunciations for these out-of-vocabulary words. In this paper, a machine translation approach is used to perform grapheme-to-phoneme (g2p) conversion, the task of finding the pronunciation of a word from its written form. Two alternative methods are proposed to derive pronunciation variants. In the first case, an n-best pronunciation list is extracted directly from the g2p converter. The second is a novel method based on a pivot approach, traditionally used for the paraphrase extraction task, and applied as a post-processing step to the g2p converter. The performance of these two methods is compared under different training conditions. The range of applications which require pronunciation lexicons is discussed and the generated pronunciations are further tested in some preliminary automatic speech recognition experiments.