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

摘要

A multilingual long audio alignment system is presented in the automatic subtitling domain, supporting English, Spanish and Basque. Prerecorded 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.