Abstract
This study presents an approach to the task of automatically classifying and detecting speaking styles. The detection of speaking styles is useful for the segmentation of multimedia data into consistent parts and has important applications, such as identifying speech segments to train acoustic models for speech recognition. In this work the database consists of daily news broadcasts in Portuguese television, on which two main speaking styles are evident: read speech from voice-over and anchors, and spontaneous speech from interviews and commentaries. Using a combination of phonetic and prosodic features we can separate these two speaking styles with a good accuracy (93.7% read, 69.5% spontaneous). This is performed in two steps. The first step separates the speech segments from the non-speech audio segments and the second step classifies read versus spontaneous speaking style. The use of phonetic and prosodic features provides alternative information that leads to an improvement of the classification and detection task.
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Veiga, A., Celorico, D., Proença, J., Candeias, S., Perdigão, F. (2012). Prosodic and Phonetic Features for Speaking Styles Classification and Detection. In: Torre Toledano, D., et al. Advances in Speech and Language Technologies for Iberian Languages. Communications in Computer and Information Science, vol 328. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35292-8_10
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DOI: https://doi.org/10.1007/978-3-642-35292-8_10
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