Abstract
This paper describes the implementation of Hidden Markov Model based speaker independent spoken digits and letters speech recognition system for Amazigh language which is an official language in Morocco. The system is developed using HTK. The system is trained on 33 Amazigh alphabets and 10 first digits by collecting data from 60 speakers and is tested using data collected from another 20 speakers. This document details the experiment by discussing the implementation using the HTK Toolkit. Performance was measured using combinations of HMM 8-states and various number of Gaussian mixture distribution. The experimental results show that the system have given better recognition rate 85.95 % with 4 Gaussian Mixture. The results obtained are improved in comparison with our previous work.
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El Ouahabi, S., Atounti, M., Bellouki, M. (2017). Building HMM Independent Isolated Speech Recognizer System for Amazigh Language. In: Rocha, Á., Serrhini, M., Felgueiras, C. (eds) Europe and MENA Cooperation Advances in Information and Communication Technologies. Advances in Intelligent Systems and Computing, vol 520. Springer, Cham. https://doi.org/10.1007/978-3-319-46568-5_31
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DOI: https://doi.org/10.1007/978-3-319-46568-5_31
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