Amazigh Speech Recognition Embedded System

This paper investigates the Amazigh speech recognition and its usage for controlling external devices. We describe our experience to design a speech system founded on hidden Markov Models (HMMs), Gaussian mixture models (GMMs), Mel frequency spectral coefficients (MFCCs) and optimization of parameters in order to have a portability in resource limited embedded system. Our objective is developing a control Amazigh speech recognition system through a Raspberry Pi board, as well as achieving the best solution with a higher automatic speech recognition parametrization for lowcost minicomputers on a speaker-independent approach. The designed speech system was implemented on the open-source platform. The system achieves the best performance of 90.43% when trained by using 3 HMMs and 16 GMMs.

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