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Amazigh speech recognition based on the Kaldi ASR toolkit

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Abstract

In this work, we offer a new approach to integrating the Amazigh language, which is a less-resourced language, into an isolated speech recognition system by exploiting the Kaldi open-source platform. Our designed system is able to recognize the ten first Amazigh digits and ten daily must-used Amazigh isolated words, which present typical syllabic structure and which are considered a good representative sample of the Amazigh language. The designed speech system was implemented using Hidden Markov Models (HMMs) with different number of Gaussian distributions. In addition, we evaluated our created system performance by varying the feature extraction methods in order to determine the optimal method for maximum performance. The best-obtained result is 93.96% was obtained with Mel Frequency Cepstral Coefficients (MFCCs) technique.

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Data availability

The dataset generated during the current study is not publicly available because it is laboratory-specific data.

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Funding

The authors declare they have no financial interests.

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Authors and Affiliations

  1. Laboratory of Computer Science, Signals, Automation and Cognitivism, Faculty of Sciences Dhar Mahraz, University Sidi Mohamed Ben Abdellah, Fez, Morocco

    Fatima Barkani, Naouar Laaidi, Ouissam Zealouk, Hassan Satori & Khalid Satori

  2. Team of modeling and scientific computing, Pluridisciplinary Faculty of Nador, Mohammed First University, Oujda, Morocco

    Mohamed Hamidi

Authors
  1. Fatima Barkani
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  2. Mohamed Hamidi
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  3. Naouar Laaidi
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  4. Ouissam Zealouk
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  5. Hassan Satori
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  6. Khalid Satori
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Correspondence to Mohamed Hamidi.

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Barkani, F., Hamidi, M., Laaidi, N. et al. Amazigh speech recognition based on the Kaldi ASR toolkit. Int. j. inf. tecnol. 15, 3533–3540 (2023). https://doi.org/10.1007/s41870-023-01354-z

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  • DOI: https://doi.org/10.1007/s41870-023-01354-z

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