Mohamed Hamidi

Prof. Mohamed Hamidi

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Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 December 2019 in International Journal of Speech Technology
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Journal Article
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Mohamed HamidiMohamed Hamidi
Mohamed Hamidi
HShassan satori
hassan satori
OZOuissam Zealouk
Ouissam Zealouk
KSKhalid Satori
Khalid Satori

18 January 2018 in International Journal of Speech Technology
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Journal Article
Closed access
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OZOuissam Zealouk
Ouissam Zealouk
HShassan satori
hassan satori
Mohamed HamidiMohamed Hamidi
Mohamed Hamidi
NLNaouar Laaidi
Naouar Laaidi
KSKhalid Satori
Khalid Satori

1 March 2024 in International Journal of Speech Technology
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Journal Article
Closed access
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HBHossam Boulal
Hossam Boulal
Mohamed HamidiMohamed Hamidi
Mohamed Hamidi
MAMustapha Abarkan
Mustapha Abarkan
JBJamal Barkani
Jamal Barkani

1 October 2018
Verified
Conference Paper
Closed access
Mohamed HamidiMohamed Hamidi
Mohamed Hamidi
HShassan satori
hassan satori
OZOuissam Zealouk
Ouissam Zealouk
KSKhalid Satori
Khalid Satori
NLNaouar Laaidi
Naouar Laaidi
This paper describes our experience to create a secure Telephony Amazigh Spoken System over the network. The designed system was created by combining HMM automatic speech recognition and IVR technologies. It allows the user to control from distance the security network and backup system using his voice to network tasks administration managing and his biological voiceprint for security identification. This research project is carried out using Amazigh language for the interaction system. The designed system was implemented on the open source platform. Our experimental results show that the administrator recognition rates were all above 80 % whereas the non-admin recognition rate is less than 6% which demonstrates the security aspect of our system.

1 April 2020
Verified
Conference Paper
Closed access
KLKhaled Lounnas
Khaled Lounnas
HShassan satori
hassan satori
Mohamed HamidiMohamed Hamidi
Mohamed Hamidi
HTHocine Teffahi
Hocine Teffahi
MAMourad Abbas
Mourad Abbas
Mohamed LichouriMohamed Lichouri
Mohamed Lichouri
In this paper, we aim to describe a novel technique which is a Combined Automatic Speech Recognition and Language Identification System that uses both ASR and LI technologies which consists of the recognition of spoken digits after identifying their language. An in-house corpus was used mainly for both speech-based multi-lingual identification and speech recognition tasks made of bilingual digits sounds that contains ten digits spoken mainly in two languages: Modern Standard Arabic (MSA) and Amazigh Moroccan dialect. First of all, we develop the Language Identification stage which is the basis of our hybrid system which behaves as front-end of our system that serves for spoken language detection. This facilitates the task of recognition by allocating the output to the appropriate Hidden Model Markov (HMM) based recognition system (Arabic or Amazigh) which improves recognition of a bilingual spoken digit efficiently. For this purpose, a set of parameters were adjusted on our CLIASR system to achieve good results, including classifier parameters, feature vector, and HMM-GMM parameters. The results show that our proposed LI-ASR system performs 33% better than an ordinary ASR for a given bilingual mixed speech corpus.

25 October 2022 in International Journal of Information Technology
Verified
Journal Article
Closed access
PDF file
Mohamed HamidiMohamed Hamidi
Mohamed Hamidi
OZOuissam Zealouk
Ouissam Zealouk
HSHassan Satori
Hassan Satori
NLNaouar Laaidi
Naouar Laaidi
ASAmine Salek
Amine Salek