Long audio alignment for automatic subtitling using different phone-relatedness measures

In this work, long audio alignment systems for Spanish and English are presented in an automatic subtitling scenario. Pre-recorded contents are automatically recognized at phoneme level by language-dependent phone decoders. A dynamic-programming alignment algorithm finds matches between the automatically decoded phones and the ones in the phonetic transcription for the content´s script. The accuracy of the alignment algorithm is evaluated when applying three non-binary scoring matrices based on phone confusion-pairs from each phone decoder, on phonological similarity and on human perception errors. Alignment results with the three continuous-score matrices are compared to results with a baseline binary matrix, at word and subtitle levels. The non-binary matrices achieved clearly better results. Matrix samples are given in the project´s website.