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EmoChildRu: Emotional Child Russian Speech Corpus

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Speech and Computer (SPECOM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9319))

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Abstract

We present the first child emotional speech corpus in Russian, called “EmoChildRu”, which contains audio materials of 3–7 year old kids. The database includes over 20 K recordings (approx. 30 h), collected from 100 children. Recordings were carried out in three controlled settings by creating different emotional states for children: playing with a standard set of toys; repetition of words from a toy-parrot in a game store setting; watching a cartoon and retelling of the story, respectively. This corpus is designed to study the reflection of the emotional state in the characteristics of voice and speech and for studies of the formation of emotional states in ontogenesis. A portion of the corpus is annotated for three emotional states (discomfort, neutral, comfort). Additional data include brain activity measurements (original EEG, evoked potentials records), the results of the adult listeners analysis of child speech, questionnaires, and description of dialogues. The paper reports two child emotional speech analysis experiments on the corpus: by adult listeners (humans) and by an automatic classifier (machine), respectively. Automatic classification results are very similar to human perception, although the accuracy is below 55 % for both, showing the difficulty of child emotion recognition from speech under naturalistic conditions.

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Acknowledgments

This study is financially supported by the Russian Foundation for Humanities (project # 13-06-00041a), the Russian Foundation for Basic Research (projects # 13-06-00281a, 15-06-07852a, and 15-07-04415a), the Council for grants of the President of Russia (project # MD-3035.2015.8) and by the Government of Russia (grant No. 074-U01).

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Correspondence to Elena Lyakso .

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Lyakso, E. et al. (2015). EmoChildRu: Emotional Child Russian Speech Corpus. In: Ronzhin, A., Potapova, R., Fakotakis, N. (eds) Speech and Computer. SPECOM 2015. Lecture Notes in Computer Science(), vol 9319. Springer, Cham. https://doi.org/10.1007/978-3-319-23132-7_18

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  • DOI: https://doi.org/10.1007/978-3-319-23132-7_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23131-0

  • Online ISBN: 978-3-319-23132-7

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