Automated rating of recorded classroom presentations using speech analysis in Kazakh

Akzharkyn Izbassarova; Aidana Irmanova; Alex Pappachen James

doi:10.1109/ICACCI.2017.8125872

Automated rating of recorded classroom presentations using speech analysis in Kazakh

Akzharkyn Izbassarova, Aidana Irmanova, Alex Pappachen James

School of Engineering and Digital Sciences

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

1 Citation (Scopus)

Abstract

Effective presentation skills can help to succeed in business, career and academy. This paper presents the design of speech assessment during the oral presentation and the algorithm for speech evaluation based on criteria of optimal intonation. As the pace of the speech and its optimal intonation varies from language to language, developing an automatic identification of language during the presentation is required. Proposed algorithm was tested with presentations delivered in Kazakh language. For testing purposes the features of Kazakh phonemes were extracted using MFCC and PLP methods and created a Hidden Markov Model (HMM) [5], [5] of Kazakh phonemes. Kazakh vowel formants were defined and the correlation between the deviation rate in fundamental frequency and the liveliness of the speech to evaluate intonation of the presentation was analyzed. It was established that the threshold value between monotone and dynamic speech is 0.16 and the error for intonation evaluation is 19%.

Original language	English
Title of host publication	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	393-397
Number of pages	5
Volume	2017-January
ISBN (Electronic)	9781509063673
DOIs	https://doi.org/10.1109/ICACCI.2017.8125872
Publication status	Published - Nov 30 2017
Event	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 - Manipal, Mangalore, India Duration: Sep 13 2017 → Sep 16 2017

Conference

Conference	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
Country/Territory	India
City	Manipal, Mangalore
Period	9/13/17 → 9/16/17

Keywords

Images
MFCC
PLP
Presentations
Recognition
Speech

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems

Access to Document

10.1109/ICACCI.2017.8125872

Cite this

Izbassarova, A., Irmanova, A., & James, A. P. (2017). Automated rating of recorded classroom presentations using speech analysis in Kazakh. In 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 (Vol. 2017-January, pp. 393-397). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCI.2017.8125872

Automated rating of recorded classroom presentations using speech analysis in Kazakh. / Izbassarova, Akzharkyn; Irmanova, Aidana; James, Alex Pappachen.

2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 393-397.

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

Izbassarova, A, Irmanova, A & James, AP 2017, Automated rating of recorded classroom presentations using speech analysis in Kazakh. in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 393-397, 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Manipal, Mangalore, India, 9/13/17. https://doi.org/10.1109/ICACCI.2017.8125872

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abstract = "Effective presentation skills can help to succeed in business, career and academy. This paper presents the design of speech assessment during the oral presentation and the algorithm for speech evaluation based on criteria of optimal intonation. As the pace of the speech and its optimal intonation varies from language to language, developing an automatic identification of language during the presentation is required. Proposed algorithm was tested with presentations delivered in Kazakh language. For testing purposes the features of Kazakh phonemes were extracted using MFCC and PLP methods and created a Hidden Markov Model (HMM) [5], [5] of Kazakh phonemes. Kazakh vowel formants were defined and the correlation between the deviation rate in fundamental frequency and the liveliness of the speech to evaluate intonation of the presentation was analyzed. It was established that the threshold value between monotone and dynamic speech is 0.16 and the error for intonation evaluation is 19%.",

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AB - Effective presentation skills can help to succeed in business, career and academy. This paper presents the design of speech assessment during the oral presentation and the algorithm for speech evaluation based on criteria of optimal intonation. As the pace of the speech and its optimal intonation varies from language to language, developing an automatic identification of language during the presentation is required. Proposed algorithm was tested with presentations delivered in Kazakh language. For testing purposes the features of Kazakh phonemes were extracted using MFCC and PLP methods and created a Hidden Markov Model (HMM) [5], [5] of Kazakh phonemes. Kazakh vowel formants were defined and the correlation between the deviation rate in fundamental frequency and the liveliness of the speech to evaluate intonation of the presentation was analyzed. It was established that the threshold value between monotone and dynamic speech is 0.16 and the error for intonation evaluation is 19%.

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ER -

Automated rating of recorded classroom presentations using speech analysis in Kazakh

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Conference

Keywords

ASJC Scopus subject areas

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