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In this paper, the authors present their initial study with the recently collected speech database for developing robust speaker recognition systems in Indian context. The database contains the speech data collected across different sensors, languages, speaking styles, and environments, from 200 speakers. The speech data is collected across five different sensors in parallel, in English and multiple Indian languages, in reading and conversational speaking styles, and in office and uncontrolled environments such as laboratories, hostel rooms and corridors etc. The collected database is evaluated using adapted Gaussian mixture model based speaker verification system following the NIST 2003 speaker recognition evaluation protocol and gives comparable performance to those obtained using NIST data sets.
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