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Speaker-Phrase-Specific Adaptation of PLDA Model for Improved Performance in Text-Dependent Speaker Verification

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Abstract

The i-vector/probabilistic linear discriminant analysis (PLDA) framework has been popularly used in the field of speaker verification for a long time. Lately, the introduction of online i-vectors and its integration with dynamic time warping template matching technique have significantly improved the performance of text-dependent speaker verification system. The PLDA model learns to discriminate among instances of different speaker-phrase classes and also compensates for channel and session variability. However, when exposed to unseen speakers and text, the variability compensation model turns less than optimal, leading to substantial verification error. In this paper, PLDA adaptation, in order to incorporate the idea of speaker-phrase-dependent variability in the ivector/PLDA technique, has been proposed. The adapted model gets specifically tuned to particular speaker-phrase class, leading to a more optimal solution. Two adaptation techniques, namely interpolation and weighted likelihood, have been explored in this work. Experiments have been performed on Part 1 of the RSR2015 database, and relative equal error rate (EER) reductions of up to 58.22% and 45% have been observed for interpolation and weighted likelihood techniques, respectively. The use of speaker-phrase-specific mean and whitening parameters has led to further improvement, resulting in EER reduction of up to 20% relative to that of the adapted models.

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Data Availability

The data that support the findings of this study are available from Exploit Technologies Pte Ltd, Singapore under licence agreement and is publicly available.

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Acknowledgements

The authors would like to thank the Speech and Image Processing Laboratory of National Institute of Technology Silchar for supporting the research work.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar, Assam, 788010, India

    Mohammad Azharuddin Laskar, Chuya China Bhanja & Rabul Hussain Laskar

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  1. Mohammad Azharuddin Laskar
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  2. Chuya China Bhanja
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  3. Rabul Hussain Laskar
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Correspondence to Mohammad Azharuddin Laskar.

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Laskar, M.A., Bhanja, C.C. & Laskar, R.H. Speaker-Phrase-Specific Adaptation of PLDA Model for Improved Performance in Text-Dependent Speaker Verification. Circuits Syst Signal Process 40, 5127–5151 (2021). https://doi.org/10.1007/s00034-021-01713-w

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