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Chapitre D'ouvrage Lecture Notes in Computer Science Année : 2022

The Automatic Search for Sounding Segments of SPPAS: Application to Cheese! Corpus

Brigitte Bigi
Béatrice Priego-Valverde

Résumé

The development of corpora inevitably involves the need for segmentation. For most of the corpora, the first segmentation to operate consist in determining silences vs Inter-Pausal Units-IPUs, i.e. sounding segments. This paper presents the "Search for IPUs" feature included in SPPAS-the automatic annotation and analysis of speech software tool distributed under the terms of public licenses. Particularly, this paper is focusing on its evaluation on Cheese! corpus, a corpus of reading then conversational speech between two participants. The paper reports the number of manual actions which was performed manually by the annotators in order to obtain the expected segmentation: add new IPUs, ignore irrelevant ones, split an IPU, merge two consecutive ones and move boundaries. The evaluation shows that the proposed fully automatic method is relevant.
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Dates et versions

hal-03697808 , version 1 (23-09-2022)

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Citer

Brigitte Bigi, Béatrice Priego-Valverde. The Automatic Search for Sounding Segments of SPPAS: Application to Cheese! Corpus. Human Language Technology. Challenges for Computer Science and Linguistics., 13212, Springer, pp.16 - 27, 2022, Lecture Notes in Computer Science, 978-3-031-05328-3. ⟨10.1007/978-3-031-05328-3_2⟩. ⟨hal-03697808⟩
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