Standard

Automatic Phonetic Transcription for Russian: Speech Variability Modeling. / Evdokimova, Vera ; Skrelin, Pavel ; Chukaeva, Tatiana .

Speech and Computer: 19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings. Springer Nature, 2017. p. 192-199 (Lecture Notes in Computer Science; Vol. 10458).

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Harvard

Evdokimova, V, Skrelin, P & Chukaeva, T 2017, Automatic Phonetic Transcription for Russian: Speech Variability Modeling. in Speech and Computer: 19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings. Lecture Notes in Computer Science, vol. 10458, Springer Nature, pp. 192-199, 19th International Conference on Speech and Computer, Hatfield, United Kingdom, 11/09/17. <http://www.springer.com/gp/book/9783319664286#otherversion=9783319664293>

APA

Evdokimova, V., Skrelin, P., & Chukaeva, T. (2017). Automatic Phonetic Transcription for Russian: Speech Variability Modeling. In Speech and Computer: 19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings (pp. 192-199). (Lecture Notes in Computer Science; Vol. 10458). Springer Nature. http://www.springer.com/gp/book/9783319664286#otherversion=9783319664293

Vancouver

Evdokimova V, Skrelin P, Chukaeva T. Automatic Phonetic Transcription for Russian: Speech Variability Modeling. In Speech and Computer: 19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings. Springer Nature. 2017. p. 192-199. (Lecture Notes in Computer Science).

Author

Evdokimova, Vera ; Skrelin, Pavel ; Chukaeva, Tatiana . / Automatic Phonetic Transcription for Russian: Speech Variability Modeling. Speech and Computer: 19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings. Springer Nature, 2017. pp. 192-199 (Lecture Notes in Computer Science).

BibTeX

@inproceedings{947e7eaa229c4bb3a45114c5c4601d64,
title = "Automatic Phonetic Transcription for Russian: Speech Variability Modeling",
abstract = "At the moment more advanced approaches to phonetic transcription are required for different speech technology tasks such as TTS or ASR. All subtle differences in phonetic characteristics of sound sequences inside the words and in the word boundaries need more accurate and variable transcription rules. Moreover, there is a need to take into account not only the normal rules of phonetic transcription. it is important to include the information about speech variability in regional and social dialects, popular speech and colloquial variants of the high frequency lexis. In this paper a reliable method for automatic phonetic transcription of Russian text is presented. The system is used for making not only an ideal transcription for the Russian text but also takes into account the complex processes of sound change and variation within the Russian standard pronunciation. Our transcribing system is reliable and could be used not only for the TTS systems but also in ASR tasks that require more flexible approach to phonetic transcription of the text.",
keywords = "Automatic phonetic transcription, Russian, Phonetics, Speech processing, Speech transcription, Speech variability modeling",
author = "Vera Evdokimova and Pavel Skrelin and Tatiana Chukaeva",
note = "Evdokimova V., Skrelin P., Chukaeva T. (2017) Automatic Phonetic Transcription for Russian: Speech Variability Modeling. In: Karpov A., Potapova R., Mporas I. (eds) Speech and Computer. SPECOM 2017. Lecture Notes in Computer Science, vol 10458. Springer, Cham. https://doi.org/10.1007/978-3-319-66429-3_18; 19th International Conference on Speech and Computer, SPECOM 2017 ; Conference date: 11-09-2017 Through 15-09-2017",
year = "2017",
month = aug,
language = "English",
isbn = "978-3-319-66428-6",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "192--199",
booktitle = "Speech and Computer",
address = "Germany",

}

RIS

TY - GEN

T1 - Automatic Phonetic Transcription for Russian: Speech Variability Modeling

AU - Evdokimova, Vera

AU - Skrelin, Pavel

AU - Chukaeva, Tatiana

N1 - Evdokimova V., Skrelin P., Chukaeva T. (2017) Automatic Phonetic Transcription for Russian: Speech Variability Modeling. In: Karpov A., Potapova R., Mporas I. (eds) Speech and Computer. SPECOM 2017. Lecture Notes in Computer Science, vol 10458. Springer, Cham. https://doi.org/10.1007/978-3-319-66429-3_18

PY - 2017/8

Y1 - 2017/8

N2 - At the moment more advanced approaches to phonetic transcription are required for different speech technology tasks such as TTS or ASR. All subtle differences in phonetic characteristics of sound sequences inside the words and in the word boundaries need more accurate and variable transcription rules. Moreover, there is a need to take into account not only the normal rules of phonetic transcription. it is important to include the information about speech variability in regional and social dialects, popular speech and colloquial variants of the high frequency lexis. In this paper a reliable method for automatic phonetic transcription of Russian text is presented. The system is used for making not only an ideal transcription for the Russian text but also takes into account the complex processes of sound change and variation within the Russian standard pronunciation. Our transcribing system is reliable and could be used not only for the TTS systems but also in ASR tasks that require more flexible approach to phonetic transcription of the text.

AB - At the moment more advanced approaches to phonetic transcription are required for different speech technology tasks such as TTS or ASR. All subtle differences in phonetic characteristics of sound sequences inside the words and in the word boundaries need more accurate and variable transcription rules. Moreover, there is a need to take into account not only the normal rules of phonetic transcription. it is important to include the information about speech variability in regional and social dialects, popular speech and colloquial variants of the high frequency lexis. In this paper a reliable method for automatic phonetic transcription of Russian text is presented. The system is used for making not only an ideal transcription for the Russian text but also takes into account the complex processes of sound change and variation within the Russian standard pronunciation. Our transcribing system is reliable and could be used not only for the TTS systems but also in ASR tasks that require more flexible approach to phonetic transcription of the text.

KW - Automatic phonetic transcription

KW - Russian

KW - Phonetics

KW - Speech processing

KW - Speech transcription

KW - Speech variability modeling

UR - https://link.springer.com/chapter/10.1007/978-3-319-66429-3_18

M3 - Conference contribution

SN - 978-3-319-66428-6

T3 - Lecture Notes in Computer Science

SP - 192

EP - 199

BT - Speech and Computer

PB - Springer Nature

T2 - 19th International Conference on Speech and Computer

Y2 - 11 September 2017 through 15 September 2017

ER -

ID: 13721395