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I-vector speaker and language recognition system on Android

Published in:
HPEC 2016: IEEE Conf. on High Performance Extreme Computing, 13-15 September 2016.

Summary

I-Vector based speaker and language identification provides state of the art performance. However, this comes as a more computationally complex solution, which can often lead to challenges in resource-limited devices, such as phones or tablets. We present the implementation of an I-Vector speaker and language recognition system on the Android platform in the form of a fully functional application that allows speaker enrollment and language/speaker scoring within mobile contexts. We include a detailed account of the challenges to port the system and its dependencies, which were necessary to optimize matrix operations in the I-Vector implementation. The system was benchmarked on a for a Google Nexus 6, showing a speed increase of 61.68% in scoring and 82.63% in enrollment operations with the implemented optimizations. The application was tested in mobile settings on a Nexus 7 tablet with forty participants, showing a rough accuracy of 84%. The optimized platform showed the capacity to perform near real-time recognition within a mobile setting and showcases the viability of I-Vector systems on resource-limited environments.
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Summary

I-Vector based speaker and language identification provides state of the art performance. However, this comes as a more computationally complex solution, which can often lead to challenges in resource-limited devices, such as phones or tablets. We present the implementation of an I-Vector speaker and language recognition system on the Android...

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