Combined CNN-LSTM for Enhancing Clean and Noisy Speech Recognition

Combined CNN-LSTM for Enhancing Clean and Noisy Speech Recognition

This paper presents a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) approach for Automatic Speech Recognition (ASR) using deep learning techniques on the Aurora-2 dataset. The dataset includes both clean and multi-condition modes, encompassing four noise scenarios : subway,...

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Bibliographic Details
Main Authors: Noussaiba Djeffal, Djamel Addou, Hamza Kheddar, Sid Ahmed Selouani
Format: Article
Language:Arabic
Published: Scientific and Technological Research Center for the Development of the Arabic Language 2024-12-01
Series:Al-Lisaniyyat
Subjects:
ASR - CNN - LSTM - Clean speech - Noisy speech - CNN-LSTM - DNN - SNR
Online Access:https://crstdla.dz/ojs/index.php/allj/article/view/732
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https://crstdla.dz/ojs/index.php/allj/article/view/732

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