Deep Belief Neural Networks and Bidirectional Long-Short Term Memory Hybrid for Speech Recognition
This paper describes a Deep Belief Neural Network (DBNN) and Bidirectional Long-Short Term Memory (LSTM) hybrid used as an acoustic model for Speech Recognition. It was demonstrated by many independent researchers that DBNNs exhibit superior performance to other known machine learning frameworks in...
Saved in:
| Main Authors: | Łukasz BROCKI, Krzysztof MARASEK |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute of Fundamental Technological Research Polish Academy of Sciences
2015-02-01
|
| Series: | Archives of Acoustics |
| Subjects: | |
| Online Access: | https://acoustics.ippt.pan.pl/index.php/aa/article/view/1445 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Deep Learning Based Automatic Speech Recognition for Turkish
by: Hamit Erdem, et al.
Published: (2020-08-01) -
Deep learning techniques for speech emotion recognition: A review
by: Silviana Widya Lestari, et al.
Published: (2023-06-01) -
System for Automatic Transcription of Sessions of the Polish Senate
by: Krzysztof MARASEK, et al.
Published: (2014-10-01) -
CNN Based Automatic Speech Recognition: A Comparative Study
by: Hilal Ilgaz, et al.
Published: (2024-08-01) -
Application of new acoustic parameters in ANN-aided pathological speech diagnosis
by: Joanna SZALENIEC, et al.
Published: (2014-04-01)