In this paper, phone-to-word transduction is first investigated by coupling a speech recognizer, generating for each speech segment a phone sequence or a phone confusion network, with the efficient decoder of confusion networks adopted by MOSES, a popular statistical machine translation toolkit. Then, system combination is investigated by combining the outputs of several conventional ASR systems with the output of a system embedding phone-to-word decoding through statistical machine translation. Experiments are carried out in the context of a large vocabulary speech recognition task consisting of transcription of speeches delivered in English during the European Parliament Plenary Sessions (EPPS). While only a marginal performance improvements is achieved in system combination experiments when the output of the phone-to-word transducer is included in the combination, partial results show a great potential for improvements.

Phone-to-word decoding through statistical machine translation and complementary system combination

Falavigna, Giuseppe Daniele;Giuliani, Diego;Gretter, Roberto;Gerosa, Matteo
2009

Abstract

In this paper, phone-to-word transduction is first investigated by coupling a speech recognizer, generating for each speech segment a phone sequence or a phone confusion network, with the efficient decoder of confusion networks adopted by MOSES, a popular statistical machine translation toolkit. Then, system combination is investigated by combining the outputs of several conventional ASR systems with the output of a system embedding phone-to-word decoding through statistical machine translation. Experiments are carried out in the context of a large vocabulary speech recognition task consisting of transcription of speeches delivered in English during the European Parliament Plenary Sessions (EPPS). While only a marginal performance improvements is achieved in system combination experiments when the output of the phone-to-word transducer is included in the combination, partial results show a great potential for improvements.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/5228
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