A Spiking LSTM Accelerator for Automatic Speech Recognition Application Based on FPGA

A Spiking LSTM Accelerator for Automatic Speech Recognition Application Based on FPGA

Long Short-Term Memory (LSTM) finds extensive application in sequential learning tasks, notably in speech recognition. However, existing accelerators tailored for traditional LSTM networks grapple with high power consumption, primarily due to the intensive matrix–vector multiplication operations inh...

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Bibliographic Details
Main Authors: Tingting Yin, Feihong Dong, Chao Chen, Chenghao Ouyang, Zheng Wang, Yongkui Yang
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Electronics
Subjects:
spiking LSTM
spiking neural networks
hardware acceleration
FPGA
automatic speech recognition (ASR)
Online Access:https://www.mdpi.com/2079-9292/13/5/827

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https://www.mdpi.com/2079-9292/13/5/827

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