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 | |
| 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 | India |
| City | Manipal, Mangalore |
| Period | 9/13/17 → 9/16/17 |
Fingerprint
Keywords
- Images
- MFCC
- PLP
- Presentations
- Recognition
- Speech
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
Cite this
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
}
TY - GEN
T1 - Automated rating of recorded classroom presentations using speech analysis in Kazakh
AU - Izbassarova, Akzharkyn
AU - Irmanova, Aidana
AU - James, Alex Pappachen
PY - 2017/11/30
Y1 - 2017/11/30
N2 - 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%.
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%.
KW - Images
KW - MFCC
KW - PLP
KW - Presentations
KW - Recognition
KW - Speech
UR - http://www.scopus.com/inward/record.url?scp=85042804589&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85042804589&partnerID=8YFLogxK
U2 - 10.1109/ICACCI.2017.8125872
DO - 10.1109/ICACCI.2017.8125872
M3 - Conference contribution
VL - 2017-January
SP - 393
EP - 397
BT - 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -