Accès ouvert

Automatic Speech Recognition with BERT and CTC Transformers: A Review

Article scientifique 2023 Anglais

Résumé

This review paper provides a comprehensive analysis of recent advances in automatic speech recognition (ASR) with bidirectional encoder representations from transformers BERT and connectionist temporal classification (CTC) transformers. The paper first introduces the fundamental concepts of ASR and discusses the challenges associated with it. It then explains the architecture of BERT and CTC transformers and their potential applications in ASR. The paper reviews several studies that have used these models for speech recognition tasks and discusses the results obtained. Additionally, the paper highlights the limitations of these models and outlines potential areas for further research. All in all, this review provides valuable insights for researchers and practitioners who are interested in ASR with BERT and CTC transformers.

Citer ce document

Djeffal, N., Kheddar, H., Addou, D., Mazari, A., Himeur, Y. (2023). Automatic Speech Recognition with BERT and CTC Transformers: A Review. https://doi.org/10.1109/ic2em59347.2023.10419784

Accès au document

Texte intégral en lecture en ligne, réservé aux abonnés SPHAERO et aux membres de l'institution. Se connecter

Voir l'article sur le site de la revue

Auteur(s)

Noussaiba Djeffal Hamza Kheddar Djamel Addou Ahmed Cherif Mazari Yassine Himeur

Statistiques

Consultations : 1

Téléchargements : 0