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Communication Dans Un Congrès Année : 2014

Improving a Long Audio Aligner through Phone-relatedness Matrices for English, Spanish and Basque.

Aitor Álvarez
Haritz Arzelus

Résumé

A multilingual long audio alignment system is presented in the automatic subtitling domain, supporting English, Spanish and Basque. Pre-recorded contents are recognized at phoneme level through language-dependent triphone- based decoders. In addition, the transcripts are phonetically translated using grapheme-to-phoneme transcriptors. An optimized version of Hirschberg’s algorithm performs an alignment between both phoneme sequences to find matches. The correctly aligned phonemes and their time-codes obtained in the recognition step are used as the reference to obtain near-perfectly aligned subtitles. The performance of the alignment algorithm is evaluated using different non-binary scoring matrices based on phone confusion-pairs from each decoder, on phonological similarity and on human perception errors. This system is an evolution of our previous successful system for long audio alignment. KW: long audio alignment;automatic subtitling;phonological similarity;perceptual similarity
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Dates et versions

hal-01404598 , version 1 (29-11-2016)

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  • HAL Id : hal-01404598 , version 1

Citer

Aitor Álvarez, Pablo Ruiz, Haritz Arzelus. Improving a Long Audio Aligner through Phone-relatedness Matrices for English, Spanish and Basque.. TSD, 17th Inter­na­tional Confe­rence on Text, Speech and Dia­logue, Sep 2014, Brno, Czech Republic. pp.476-483. ⟨hal-01404598⟩
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