Does my speech rock? Automatic assessment of public speaking skills

Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

Volumn 2015-January, Issue , 2015, Pages 2519-2523

  Azäis, Lucas ^a   Payan, Adrien ^a   Sun, Tianjiao ^a   Vidal, Guillaume ^a   Zhang, Tina ^a   Coutinho, Eduardo ^a   Eyben, Florian ^b   Schuller, Björn ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b AUDEERING GMBH   (Germany)

Author keywords

Automatic Public Speech Assessment; Classification; Database; Prosody; Regression

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DATABASE SYSTEMS; LEARNING SYSTEMS; PERSONNEL TRAINING; SPEECH; TECHNICAL PRESENTATIONS;

ACOUSTIC FEATURES; AUTOMATIC ASSESSMENT; AUTOMATIC PUBLIC SPEECH ASSESSMENT; MACHINE LEARNING MODELS; ORAL PRESENTATIONS; PROSODY; REGRESSION; SPEAKER INDEPENDENTS;

SPEECH COMMUNICATION;

EID: 84959169137     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. T. Sobol-Shikler and P. Robinson, "Classification of complex information: Inference of co-occurring affective states from their expressions in speech, " Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 32, no. 7, pp. 1284-1297, 2010.
2. B. Schuller, G. Rigoll, and M. Lang, "Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-belief network architecture, " in Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP'04). IEEE International Conference on, vol. 1. IEEE, 2004, pp. I-577.
3. D. Le and E. M. Provost, "Modeling pronunciation, rhythm, and intonation for automatic assessment of speech quality in aphasia rehabilitation, " in Fifteenth Annual Conference of the International Speech Communication Association, 2014, pp. 1563-1567.
4. J. Kim, N. Kumar, A. Tsiartas, M. Li, and S. S. Narayanan, "Automatic intelligibility classification of sentence-level pathological speech, " Computer speech & language, vol. 29, no. 1, pp. 132-144, 2015.
5. F. Rudzicz, A. K. Namasivayam, and T. Wolff, "The torgo database of acoustic and articulatory speech from speakers with dysarthria, " Language Resources and Evaluation, vol. 46, no. 4, pp. 523-541, 2012.
6. K. Zechner and I. I. Bejar, "Towards automatic scoring of nonnative spontaneous speech, " in Proceedings of the main conference on human language technology conference of the North American chapter of the association of computational linguistics. Association for Computational Linguistics, 2006, pp. 216-223.
7. J. Bernstein, M. Cohen, H. Murveit, D. Rtischev, and M. Weintraub, "Automatic evaluation and training in english pronunciation. " in ICSLP, vol. 90, 1990, pp. 1185-1188.
8. X. Xi, D. Higgins, K. Zechner, and D. M. Williamson, "Automated scoring of spontaneous speech using speechratersm v1. 0, " ETS Research Report Series, vol. 2008, no. 2, pp. i-102, 2008.
9. D. A. Silverstein and T. Zhang, "System and method of providing evaluation feedback to a speaker while giving a real-time oral presentation, " May 23 2006, uS Patent 7, 050, 978.
10. S. Lloyd-Hughes, How to Be Brilliant at Public Speaking: Any Audience. Any Situation. FT Press, 2011.
11. P. Lieberman, "A study of prosodic features, " in Status report on speech research, SR-23. Haskins Laboratories, New Haven, CT, 1970, pp. 179-208.
12. J. H. Byrns, Speak for yourself: An introduction to public speaking. McGraw-Hill, 1994.
13. L. M. Schreiber, G. D. Paul, and L. R. Shibley, "The development and test of the public speaking competence rubric, " Communication Education, vol. 61, no. 3, pp. 205-233, 2012.
14. L. Chen, G. Feng, J. Joe, C. W. Leong, C. Kitchen, and C. M. Lee, "Towards automated assessment of public speaking skills using multimodal cues, " in Proceedings of the 16th International Conference on Multimodal Interaction. ACM, 2014, pp. 200-203.
15. L. Batrinca, G. Stratou, A. Shapiro, L.-P. Morency, and S. Scherer, "Cicero-towards a multimodal virtual audience platform for public speaking training, " in Intelligent Virtual Agents. Springer, 2013, pp. 116-128.
16. K. Kurihara, M. Goto, J. Ogata, Y. Matsusaka, and T. Igarashi, "Presentation sensei: A presentation training system using speech and image processing, " in Proceedings of the 9th international conference on Multimodal interfaces. ACM, 2007, pp. 358-365.
17. T. Pfister and P. Robinson, "Speech emotion classification and public speaking skill assessment, " in Human Behavior Understanding. Springer, 2010, pp. 151-162.
18. F. Eyben, M. Wöllmer, and B. Schuller, "Opensmile: The munich versatile and fast open-source audio feature extractor, " in Proceedings of the international conference on Multimedia. ACM, 2010, pp. 1459-1462.
19. M. Grimm and K. Kroschel, "Evaluation of natural emotions using self assessment manikins, " in Automatic Speech Recognition and Understanding, 2005 IEEE Workshop on. IEEE, 2005, pp. 381-385.
20. B. Schuller, S. Steidl, A. Batliner, A. Vinciarelli, K. Scherer, F. Ringeval, M. Chetouani, F. Weninger, F. Eyben, E. Marchi, M. Mortillaro, H. Salamin, A. Polychroniou, F. Valente, and S. Kim, "The INTERSPEECH 2013 Computational Paralinguistics Challenge: Social Signals, Conflict, Emotion, Autism, " in Proceedings INTERSPEECH 2013, 14th Annual Conference of the International Speech Communication Association, ISCA. Lyon, France: ISCA, August 2013, pp. 148-152, (acceptance rate: 52 %, IF 1. 05 (2010)), 63 citations.
21. F. Eyben, K. Scherer, B. Schuller, J. Sundberg, E. Andre, C. Busso, L. Devillers, J. Epps, P. Laukka, S. Narayanan, and K. Truong, "The geneva minimalistic acoustic parameter set (gemaps) for voice research and affective computing, " Transactions on Affective Computing, submitted.
22. F. Weninger, F. Eyben, B. W. Schuller, M. Mortillaro, and K. R. Scherer, "On the Acoustics of Emotion in Audio: What Speech, Music and Sound have in Common, " Frontiers in Psychology, Emotion Science, Special Issue on Expression of emotion in music and vocal communication, vol. 4, no. Article ID 292, pp. 1-12, May 2013.
23. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. Witten, "The weka data mining software: An update, " SIGKDD Explorations, vol. 11, no. 1, pp. 10-18, 2009.
24. T. Pfister and P. Robinson, "Real-time recognition of affective states from nonverbal features of speech and its application for public speaking skill analysis, " Affective Computing, IEEE Transactions on, vol. 2, no. 2, pp. 66-78, 2011.
25. F. Hönig, A. Batliner, T. Booklet, G. Stemmer, E. Nöth, S. Schnieder, and J. Krajewski, "Are men more sleepy than women or does it only look like-automatic analysis of sleepy speech, " in Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, May 2014, pp. 995-999.
26. L. Breiman, "Random forests, " Machine learning, vol. 45, no. 1, pp. 5-32, 2001.
27. Q. Mao, M. Dong, Z. Huang, and Y. Zhan, "Learning salient features for speech emotion recognition using convolutional neural networks, " Multimedia, IEEE Transactions on, vol. 16, no. 8, pp. 2203-2213, Dec 2014.
28. A. Krizhevsky, I. Sutskever, and G. E. Hinton, "Imagenet classification with deep convolutional neural networks, " in Advances in neural information processing systems, 2012, pp. 1097-1105.