IITKGP-SESC: Speech Database for Emotion Analysis
In this paper, we are introducing the speech database for analyzing the emotions present in speech signals. The proposed database is recorded in Telugu language using the professional artists from All India Radio (AIR), Vijayawada, India. The speech corpus is collected by simulating eight different emotions using the neutral (emotion free) statements. The database is named as Indian Institute of Technology Kharagpur Simulated Emotion Speech Corpus (IITKGP-SESC). The proposed database will be useful for characterizing the emotions present in speech. Further, the emotion specific knowledge present in speech at different levels can be acquired by developing the emotion specific models using the features from vocal tract system, excitation source and prosody. This paper describes the design, acquisition, post processing and evaluation of the proposed speech database (IITKGP-SESC). The quality of the emotions present in the database is evaluated using subjective listening tests. Finally, statistical models are developed using prosodic features, and the discrimination of the emotions is carried out by performing the classification of emotions using the developed statistical models.
KeywordsIITKGP-SESC Duration Emotion Emotion recognition Energy Prosody Statistical models Pitch
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- 1.Database for Indian languages. Speech and Vision lab, Indian Institute of Technology Madras, India (2001)Google Scholar
- 3.Sagar, T.V.: Characterisation and synthesis of emotionsin speech using prosodic features. Master’s thesis, Dept. of Electronics and communications Engineering, Indian Institute of Technology Guwahati (May 2007)Google Scholar
- 4.Lee, C.M., Narayanan, S.: Toward detecting emotions in spoken dialogs. IEEEAUP 13(2), 293–303 (2005)Google Scholar
- 5.Ververidis, D., Kotropoulos, C.: A state of the art review on emotional speech databases. In: Eleventh Australasian International Conference on Speech Science and Technology, Auckland, New Zealand (December 2006)Google Scholar
- 6.Yang, L.: The expression and recognition of emotions through prosody. In: Proc. Int. Conf. Spoken Language Processing, pp. 74–77 (2000)Google Scholar
- 8.Prasanna, S.R.M., Yegnanarayana, B.: Extraction of pitch in adverse conditions. In: Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, Montreal, Canada (May 2004)Google Scholar
- 9.Haykin, S.: Neural Networks: A Comprehensive Foundation. Pearson Education Aisa, Inc., New Delhi (1999)Google Scholar