Abstract
Our recent work was focused on automatic speech recognition (ASR) of spoken word archive documents [6, 7]. One of the important tasks was to structuralize the recognized document (to segment the document and to detect sentence boundaries). Prosodic features play significant role in the spoken document structuralization. In our previous work we bound the prosodic information on the ASR events – words and noises. Many prosodic features (e.g. speech rate, vowel prominence or prolongation of last syllables) require higher time resolution than word-level [1]. For that reason we propose a scheme that is able to automatically syllabify the recognized words and by forced-alignment of its phonetic content provide the syllables (and its phonemes) with time-stamps. We presume that words, non-speech events, syllables and phonemes represent an appropriate hierarchical set of structuralization units for processing various prosodic features.
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Acknowledgment
This work was partly supported by the Student’s Grant Scheme at the Technical University of Liberec (SGS 2016).
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Boháč, M., Matějů, L., Rott, M., Šafařík, R. (2016). Automatic Syllabification and Syllable Timing of Automatically Recognized Speech – for Czech. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2016. Lecture Notes in Computer Science(), vol 9924. Springer, Cham. https://doi.org/10.1007/978-3-319-45510-5_62
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