Identification of Subjects Wearing a Surgical Mask from Their Speech by Means of X-vectors and Fisher Vectors
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-13448-7_9
Reference37 articles.
1. Egas-López, J.V., Orozco-Arroyave, J.R., Gosztolya, G.: Assessing Parkinson’s disease from speech using fisher vectors. In: Proceedings of Interspeech (2019)
2. Gosztolya, G., Bagi, A., Szalóki, S., Szendi, I., Hoffmann, I.: Identifying schizophrenia based on temporal parameters in spontaneous speech. In: Proceedings of Interspeech, Hyderabad, India, pp. 3408–3412, September 2018
3. Grósz, T., Busa-Fekete, R., Gosztolya, G., Tóth, L.: Assessing the degree of nativeness and Parkinson’s condition using Gaussian processes and deep rectifier neural networks. In: Proceedings of Interspeech, Dresden, Germany, pp. 1339–1343, September 2015
4. Gosztolya, G., Grósz, T., Tóth, L.: General utterance-level feature extraction for classifying crying sounds, atypical & self-assessed affect and heart beats. In: Proceedings of Interspeech, Hyderabad, India, pp. 531–535, September 2018
5. Gosztolya, G., Grósz, T., Szaszák, G., Tóth, L.: Estimating the sincerity of apologies in speech by DNN rank learning and prosodic analysis. In: Proceedings of Interspeech, San Francisco, CA, USA, pp. 2026–2030, September 2016
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