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Multi-style speaker recognition database in practical conditions

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Abstract

This work describes the process of collection and organization of a multi-style database for speaker recognition. The multi-style database organization is based on three different categories of speaker recognition: voice-password, text-dependent and text-independent framework. Three Indian institutes collaborated for the collection of the database at respective sites. The database is collected over an online telephone network that is deployed for speech based student attendance system. This enables the collection of data for a longer period from different speakers having session variabilities, which is useful for speaker verification (SV) studies in practical scenario. The database contains data of 923 speakers for the three different modes of SV and hence termed as multi-style speaker recognition database. This database is useful for session variability, multi-style speaker recognition and short utterance based SV studies. Initial results are reported over the database for the three different modes of SV. A copy of the database can be obtained by contacting the authors.

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Acknowledgements

This work is supported by a project grant 12(6)/2012-ESD for the project entitled “Development of Speech-Based Multi-level Person Authentication System” funded by the Department of Electronics and Information Technology (DeitY), Govt. of India. The authors would also like to acknowledge the consortium teams of the project at North-Eastern Hill University (NEHU), Shillong led by Dr. L. Joyprakash Singh and National Institute of Technology (NIT) Silchar led by Dr. R. H. Lashkar for their contribution in the collection and organization of the database.

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  1. Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India

    Rohan Kumar Das, Sarfaraz Jelil & S. R. Mahadeva Prasanna

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  1. Rohan Kumar Das
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  2. Sarfaraz Jelil
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  3. S. R. Mahadeva Prasanna
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Correspondence to Rohan Kumar Das.

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Das, R.K., Jelil, S. & Prasanna, S.R.M. Multi-style speaker recognition database in practical conditions. Int J Speech Technol 21, 409–419 (2018). https://doi.org/10.1007/s10772-017-9475-4

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