A Robust Voice Pathology Detection System Based on the Combined BiLSTM–CNN Architecture
Voice recognition systems have become increasingly important in recent years due to the growing need for more efficient and intuitive human-machine interfaces. The use of Hybrid LSTM networks and deep learning has been very successful in improving speech detection systems. The aim of this paper is...
Main Authors: | Rimah Amami, Rim Amami, Chiraz Trabelsi, Sherin Hassan Mabrouk, Hassan A. Khalil |
---|---|
Format: | Article |
Language: | English |
Published: |
Brno University of Technology
2023-12-01
|
Series: | Mendel |
Subjects: | |
Online Access: | http://46.28.109.63/index.php/mendel/article/view/254 |
Similar Items
-
Research on sentiment classification for netizens based on the BERT-BiLSTM-TextCNN model
by: Xuchu Jiang, et al.
Published: (2022-06-01) -
Aspect Based Sentiment Analysis With Feature Enhanced Attention CNN-BiLSTM
by: Wei Meng, et al.
Published: (2019-01-01) -
Stock Price Prediction Using CNN-BiLSTM-Attention Model
by: Jilin Zhang, et al.
Published: (2023-04-01) -
Remaining Useful Life Prediction of Milling Cutters Based on CNN-BiLSTM and Attention Mechanism
by: Lei Nie, et al.
Published: (2022-10-01) -
New Hybrid Deep Learning Approach Using BiGRU-BiLSTM and Multilayered Dilated CNN to Detect Arrhythmia
by: Md Shofiqul Islam, et al.
Published: (2022-01-01)