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- W157687613 abstract "One limitation in prosody research is the lack of sufficient prosodically labelled speech data. In this paper, we present research on an automatic labelling system that is able to produce a phonological tonal labelling according to the ToBI like intonation model for German developed by Fery. The system is not totally dependent on the specific language and/or labelling system, as it uses corpus based techniques such as an HMM based word, syllable and phoneme segmentation and a decision tree learning algorithm (C4.5) for the phonetic-phonology mapping. The current system was trained on about 1 hour of expert prosodically labelled speech from a single male radio news announcer. We present experiments for finding a suitable feature set drawn from features that describe the prosodic correlates fundamental frequency, duration and intensity as well as some lexical and syntactic features. With the best feature set, we achieve a recognition rate of 78.7% for speaker dependent recognition of ToBI labels (simultaneously predicting prominence and phrasing) and 86.9% for the simpler accented/not accented decision. Although the system’s accuracy is well below that of human transcribers, it is a useful tool actively used in our laboratory due to it’s ability to process large amounts of speech data at low costs." @default.
- W157687613 created "2016-06-24" @default.
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- W157687613 date "1998-11-30" @default.
- W157687613 modified "2023-09-27" @default.
- W157687613 title "Automatic labelling of German prosody" @default.
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- W157687613 doi "https://doi.org/10.21437/icslp.1998-585" @default.
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