Language model adaptation with additional text generated by machine translation
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ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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Multilingual Speech Processing
Multilingual Speech Processing
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Speech Communication
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Rule-Based Automatic Phonetic Transcription for the Romanian Language
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Automatic speech recognition for under-resourced languages: application to Vietnamese language
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Enhanced Rule-Based Phonetic Transcription for the Romanian Language
SYNASC '09 Proceedings of the 2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
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A Romanian corpus for speech perception and automatic speech recognition
NEHIPISIC'11 Proceeding of 10th WSEAS international conference on electronics, hardware, wireless and optical communications, and 10th WSEAS international conference on signal processing, robotics and automation, and 3rd WSEAS international conference on nanotechnology, and 2nd WSEAS international conference on Plasma-fusion-nuclear physics
Automatic speech recognition for under-resourced languages: A survey
Speech Communication
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This study investigates the possibility of using statistical machine translation to create domain-specific language resources. We propose a methodology that aims to create a domain-specific automatic speech recognition (ASR) system for a low-resourced language when in-domain text corpora are available only in a high-resourced language. Several translation scenarios (both unsupervised and semi-supervised) are used to obtain domain-specific textual data. Moreover this paper shows that a small amount of manually post-edited text is enough to develop other natural language processing systems that, in turn, can be used to automatically improve the machine translated text, leading to a significant boost in ASR performance. An in-depth analysis, to explain why and how the machine translated text improves the performance of the domain-specific ASR, is also made at the end of this paper. As bi-products of this core domain-adaptation methodology, this paper also presents the first large vocabulary continuous speech recognition system for Romanian, and introduces a diacritics restoration module to process the Romanian text corpora, as well as an automatic phonetization module needed to extend the Romanian pronunciation dictionary.