Affiliation:
1. University of Orleans, Orleans, France
2. University of Tunis El Manar, Tunisia
Abstract
In the field of human-machine interaction, automatic speech recognition (ASR) has been a prominent research area since the 1950s. Single-word speech recognition is widely used in voice command systems, which can be implemented in various applications such as access control systems, robots, and voice-enabled devices. This study describes the implementation of a single-word speech recognition system using wave atoms transform (WAT) and frequency-mel cepstral coefficients (MFCC) on a Raspberry Pi 3 (RPi 3) board. The WAT-MFCC approach is combined with a support vector machine (SVM). The experiment was conducted on an Arabic word database, and the results showed that the proposed WAT-MFCC-SVM method is highly reliable, achieving a detection rate of 100% and a real-time factor (RTF) of 1.50.
Reference53 articles.
1. Bilingual Automatic Speech Recognition: A Review, Taxonomy and Open Challenges
2. Design and implementation of an automatic speech recognition based voice control system.;N.Adnene;Conference on Electrical Engineering,2021
3. Ahmed Rahat, S., Imteaj, A., & Rahman, T. (2018). An IoT based Interactive Speech Recognizable Robot with Distance control using Raspberry Pi. 2018 2nd Int. Conf. on Innovations in Science, Engineering and Technology (ICISET), Chittagong, Bangladesh.
4. Implementation of a Speech Recognition System in a DSC
5. Station hybride (DSP/FPGA) pour un système rapide de reconnaissance automatique de la parole. Synthèse;H.Atoui;Revue des Sciences et de la Technologie,2020