Abderrahman Amrouche

Publications (2)0 Total impact

• Article: Robust Arabic speech recognition in noisy environments using prosodic features and formant

  Anissa Imen Amrous, Mohamed Debyeche, Abderrahman Amrouche
  [show abstract] [hide abstract]
  ABSTRACT: This paper investigates the contribution of formants and prosodic features such as pitch and energy in Arabic speech recognition under real-life conditions. Our speech recognition system based on Hidden Markov Models (HMMs) is implemented using the HTK Toolkit. The front-end of the system combines features based on conventional Mel-Frequency Cepstral Coefficient (MFFC), prosodic information and formants. The experiments are performed on the ARADIGIT corpus which is a database of Arabic spoken words. The obtained results show that the resulting multivariate feature vectors, in noisy environment, lead to a significant improvement, up to 27%, in word accuracy relative the word accuracy obtained from the state-of-the-art MFCC-based system. KeywordsASR system–HMM–MFCC–Formant–Prosodic features–Speech variability–Additive noise
  International Journal of Speech Technology 05/2012; 14(4):351-359.
• Chapter: Prosodic Features and Formant Contribution for Arabic Speech Recognition in Noisy Environments

  Anissa Imen Amrous, Mohamed Debyeche, Abderrahman Amrouche
  [show abstract] [hide abstract]
  ABSTRACT: This paper investigates the contribution of formants and prosodic features like pitch and energy in Arabic speech recognition under real-life conditions. Our speech recognition system based on Hidden Markov Model (HMM) is implemented using the HTK Toolkit. The front-end of the system combines features based on conventional Mel-Frequency Cepstral Coefficient (MFFC), prosodic information and formants. The obtained results show that the resulting multivariate feature vectors lead to a significant improvement of the recognition system performance in noisy environment compared to cepstral system alone. KeywordsASR system–HMM–MFCC–formant–prosodic features
  03/2011: pages 465-474;