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A Study on Text-Independent Speaker Recognition Systems in Emotional Conditions Using Different Pattern Recognition Models

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Book cover Mining Intelligence and Knowledge Exploration (MIKE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10089))

Abstract

The present study focuses on the text-independent speaker recognition in emotional conditions. In this paper, both system and source features are considered to represent speaker specific information. At the model level, Gaussian Mixture Models (GMMs), Gaussian Mixture Model-Universal Background Model (GMM-UBM) and Deep Neural Networks (DNN) are explored. The experiments are performed using 3 emotional databases, i.e. German emotional speech database (EMO-DB), IITKGP-SESC: Hindi and IITKGP-SESC: Telugu databases. The emotions considered in the present study are neutral, anger, happy and sad. The results show that, the performance of a speaker recognition system trained with clean speech is degrading while testing with emotional data irrespective of feature used or model used to build the system. The best results are obtained for the score level fusion of system and source features based systems when speakers are modeled with DNNs.

R. Prasath—A part of this was carried out when the author was in Indian Institute of Information Technology (IIIT) Sricity, India.

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Acknowledgements

The first author would like to thank Department of Electronics and Information Technology, Ministry of Communication & IT, Govt of India for granting PhD Fellowship under Visvesvaraya PhD Scheme.

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Authors and Affiliations

  1. Speech and Vison Lab (LTRC), International Institute of Information Technology Hyderabad, Hyderabad, Andhra Pradesh, India

    K. N. R. K. Raju Alluri, Sivanand Achanta, Suryakanth V. Gangashetty & Anil Kumar Vuppala

  2. NTNU, Trondheim, Norway

    Rajendra Prasath

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  1. K. N. R. K. Raju Alluri
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  2. Sivanand Achanta
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  3. Rajendra Prasath
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  4. Suryakanth V. Gangashetty
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  5. Anil Kumar Vuppala
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Corresponding author

Correspondence to K. N. R. K. Raju Alluri .

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Editors and Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    Rajendra Prasath

  2. Center for Computing Research, CIC, National Polytechnic Institute, IPN, Mexico City, Distrito Federal, Mexico

    Alexander Gelbukh

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Alluri, K.N.R.K.R., Achanta, S., Prasath, R., Gangashetty, S.V., Vuppala, A.K. (2017). A Study on Text-Independent Speaker Recognition Systems in Emotional Conditions Using Different Pattern Recognition Models. In: Prasath, R., Gelbukh, A. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2016. Lecture Notes in Computer Science(), vol 10089. Springer, Cham. https://doi.org/10.1007/978-3-319-58130-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-58130-9_7

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