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End-to-end neural automatic speech recognition system for low resource languages

The rising popularity of end-to-end (E2E) automatic speech recognition (ASR) systems can be attributed to their ability to learn complex speech patterns directly from raw data, eliminating the need for intricate feature extraction pipelines and handcrafted language models. E2E-ASR systems have consi...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Sami Dhahbi, Nasir Saleem, Sami Bourouis, Mouhebeddine Berrima, Elena Verdú
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2025-03-01
Schriftenreihe:Egyptian Informatics Journal
Schlagworte:
Speech recognition
Deep learning
Low-resource language
E2E learning
Data augmentation
Synthetic speech
Online-Zugang:http://www.sciencedirect.com/science/article/pii/S1110866525000088
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