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Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language. / Bukreeva, Liudmila; Guseva, Daria; Dolgushin, Mikhail; Evdokimova, Vera; Obotnina, Vasilisa.

Speech and Computer. 2023. p. 68-76 6 (Lecture Notes in Computer Science; Vol. 14338).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Bukreeva, L, Guseva, D, Dolgushin, M, Evdokimova, V & Obotnina, V 2023, Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language. in Speech and Computer., 6, Lecture Notes in Computer Science, vol. 14338, pp. 68-76, The 25th International Conference on Speech and Computer (SPECOM), Hubli-Dharwad, India, 29/11/23. https://doi.org/10.1007/978-3-031-48309-7_6

APA

Bukreeva, L., Guseva, D., Dolgushin, M., Evdokimova, V., & Obotnina, V. (2023). Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language. In Speech and Computer (pp. 68-76). [6] (Lecture Notes in Computer Science; Vol. 14338). https://doi.org/10.1007/978-3-031-48309-7_6

Vancouver

Bukreeva L, Guseva D, Dolgushin M, Evdokimova V, Obotnina V. Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language. In Speech and Computer. 2023. p. 68-76. 6. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-031-48309-7_6

Author

Bukreeva, Liudmila ; Guseva, Daria ; Dolgushin, Mikhail ; Evdokimova, Vera ; Obotnina, Vasilisa. / Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language. Speech and Computer. 2023. pp. 68-76 (Lecture Notes in Computer Science).

BibTeX

@inproceedings{ce22611b5c0948d8a5b21af1c57e6861,
title = "Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language",
abstract = "Recognition of highly emotional speech remains a challenging case of automatic speech recognition task. The aim of this article is to carry out experiments on highly emotional speech recognition by investigating oral history archives provided by the Yad Vashem foundation. The material consists of elderly peoples{\textquoteright} emotional speech full of accents and common language. We analyze and preprocess 26 h of publicly available video interviews with Holocaust survivors. Our objective was to develop a system able to perform emotional speech recognition based on deep neural network models. We present and evaluate the obtained results that contribute to the research field of oral history archives.",
keywords = "Corpora, Question Answering, Visual History Archives",
author = "Liudmila Bukreeva and Daria Guseva and Mikhail Dolgushin and Vera Evdokimova and Vasilisa Obotnina",
year = "2023",
month = nov,
day = "22",
doi = "10.1007/978-3-031-48309-7_6",
language = "English",
isbn = "9783031483080",
series = "Lecture Notes in Computer Science",
pages = "68--76",
booktitle = "Speech and Computer",
note = "null ; Conference date: 29-11-2023 Through 01-12-2023",
url = "https://www.iitdh.ac.in/specom-2023/",

}

RIS

TY - GEN

T1 - Emotional Speech Recognition of Holocaust Survivors with Deep Neural Network Models for Russian Language

AU - Bukreeva, Liudmila

AU - Guseva, Daria

AU - Dolgushin, Mikhail

AU - Evdokimova, Vera

AU - Obotnina, Vasilisa

PY - 2023/11/22

Y1 - 2023/11/22

N2 - Recognition of highly emotional speech remains a challenging case of automatic speech recognition task. The aim of this article is to carry out experiments on highly emotional speech recognition by investigating oral history archives provided by the Yad Vashem foundation. The material consists of elderly peoples’ emotional speech full of accents and common language. We analyze and preprocess 26 h of publicly available video interviews with Holocaust survivors. Our objective was to develop a system able to perform emotional speech recognition based on deep neural network models. We present and evaluate the obtained results that contribute to the research field of oral history archives.

AB - Recognition of highly emotional speech remains a challenging case of automatic speech recognition task. The aim of this article is to carry out experiments on highly emotional speech recognition by investigating oral history archives provided by the Yad Vashem foundation. The material consists of elderly peoples’ emotional speech full of accents and common language. We analyze and preprocess 26 h of publicly available video interviews with Holocaust survivors. Our objective was to develop a system able to perform emotional speech recognition based on deep neural network models. We present and evaluate the obtained results that contribute to the research field of oral history archives.

KW - Corpora

KW - Question Answering

KW - Visual History Archives

UR - https://www.mendeley.com/catalogue/5522248e-a4e0-3c7a-88e3-36cef66102a6/

U2 - 10.1007/978-3-031-48309-7_6

DO - 10.1007/978-3-031-48309-7_6

M3 - Conference contribution

SN - 9783031483080

T3 - Lecture Notes in Computer Science

SP - 68

EP - 76

BT - Speech and Computer

Y2 - 29 November 2023 through 1 December 2023

ER -

ID: 114283490