Improving a long audio aligner through phone-relatedness matrices for english, spanish and basque

A Álvarez, P Ruiz, H Arzelus - … 2014, Brno, Czech Republic, September 8 …, 2014 - Springer
A Álvarez, P Ruiz, H Arzelus
Text, Speech and Dialogue: 17th International Conference, TSD 2014, Brno …, 2014Springer
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 …
Abstract
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.
Springer
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