Evaluating New Set of Acoustical Features for Cry Signal Classification

Author:

Cano-Ortiz Sergio DanielORCID,Martinez-Canete YadisbelORCID,Veranes-Vicet LietteORCID

Publisher

Springer International Publishing

Reference23 articles.

1. Varallyay, G., Benyo, Z., Illenyi, A., Farkas, Z., Kovacs, L.: Acoustic analysis of the infant cry: classical and new methods. In: 26th Annual International Conference of the IEEE EM BS, pp. 313–316. San Francisco, CA, USA (2004)

2. Varallyay, G.: Future prospects of the infant cry in the medicine. Periodica Polytechnica Ser. El. Eng. 50(1–2), 47–62 (2006)

3. Lederman, D.: Estimation of infant’s cry fundamental frequency using a modified SIFT algorithm. arXiv:1009.2796v1 [cs. SD] 14 Sep, pp. 1–5 (2010)

4. Osmani, A., Hamidi, M., Chibani, A.: Machine learning approach for infant cry interpretation. In: Proceedings – International Conference on Tools with Artificial Intelligence, ICTAI. (2018). https://doi.org/10.1109/ICTAI.2017.00038

5. Huckvale, M.: Neural network architecture that combines temporal and summative features for infant cry classification. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH in the Interspeech 2018 Computational Paralinguistic Challenge, pp. 137–141 (2018). https://doi.org/10.21437/Interspeech.2018-1959

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