1. Home
2. Premium
3. IEEE ICASSP 2020 Virtual Conference May 2020
4. Dynamic Temporal Residual Learning For Speech Recognition

Dynamic Temporal Residual Learning For Speech Recognition

Collection:

IEEE ICASSP 2020 Virtual Conference May 2020

Long short-term memory (LSTM) networks have been widely used in automatic speech recognition (ASR). This paper proposes a novel dynamic temporal residual learning mechanism for LSTM networks to better explore temporal dependencies in sequential data. The

• IEEE MemberUS $11.00
• Society MemberUS $0.00
• IEEE Student MemberUS $11.00
• Non-IEEE MemberUS $15.00

Purchase

Videos in this product

Dynamic Temporal Residual Learning For Speech Recognition

00:11:18

0 views

Long short-term memory (LSTM) networks have been widely used in automatic speech recognition (ASR). This paper proposes a novel dynamic temporal residual learning mechanism for LSTM networks to better explore temporal dependencies in sequential data. The