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Robust Automatic Evaluation of Intelligibility in Voice Rehabilitation Using Prosodic Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10415))

Abstract

Speech intelligibility for voice rehabilitation has been successfully evaluated by automatic prosodic analysis. In this paper, the influence of reading errors and the selection of certain words for the computation of prosodic features (nouns only, nouns and verbs, beginning of each sentence, beginnings of sentences and subclauses) are examined. 73 hoarse patients (48.3 ± 16.8 years) read the German version of the text “The North Wind and the Sun”. Their intelligibility was evaluated perceptually by 5 trained experts according to a 5-point scale. Eight prosodic features showed human-machine correlations of r \(\ge \) 0.4. The normalized energy in a word-pause-word interval, computed from all words (r = 0.69 for the full speaker set), the mean of jitter in nouns and verbs (r = 0.67), and the pause duration before a word (r = 0.66) were the most robust features. However, reading errors can significantly influence these results.

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Acknowledgments

Dr. Döllinger’s contribution was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft; DFG), grant no. DO1247/8-1.

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Correspondence to Tino Haderlein .

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Haderlein, T., Schützenberger, A., Döllinger, M., Nöth, E. (2017). Robust Automatic Evaluation of Intelligibility in Voice Rehabilitation Using Prosodic Analysis. In: Ekštein, K., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2017. Lecture Notes in Computer Science(), vol 10415. Springer, Cham. https://doi.org/10.1007/978-3-319-64206-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-64206-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64205-5

  • Online ISBN: 978-3-319-64206-2

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