Abstract
In our paper we examine the usage prosodic features in speech recognition, with a special attention payed to agglutinating and fixed stress languages. The used prosodic features, acoustic-prosodic pre-processing, and segmentation in terms of prosodic units are presented in details. We use the expression ”prosodic unit” in order to make a difference from prosodic phrases, which are longer. We trained a HMM-based prosodic segmenter reliing on fundamental frequency and intensity of speech. The output of the prosodic segmenter is used for N-best lattice rescoring in parallel with a simplified bigram language model in a continuous speech recognizer, in order to improve speech recognition performance. Experiments for Hungarian language show a WER reduction of about 4% using a simple lattice rescoring.
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Szaszák, G., Vicsi, K. (2007). Speech Recognition Supported by Prosodic Information for Fixed Stress Languages. In: Matoušek, V., Mautner, P. (eds) Text, Speech and Dialogue. TSD 2007. Lecture Notes in Computer Science(), vol 4629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74628-7_35
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DOI: https://doi.org/10.1007/978-3-540-74628-7_35
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