Abstract: We newly introduce a novel processing scenario of long short-term memory (LSTM) network for the energy-efficient speech recognition.
We newly introduce a novel processing scenario of long short-term memory (LSTM) network for the energy-efficient speech recognition.
Nov 25, 2020 · This paper presents an approximate computing method of long short-term memory (LSTM) operations for energy-efficient end-to-end speech recognition.
Multi-mode LSTM network for energy-efficient speech recognition. J Jo, S Hwang, S Lee, Y Lee. 2018 International SoC Design Conference (ISOCC), 133-134, 2018.
Jul 6, 2024 · This paper presents an approximate computing method of long short-term memory (LSTM) operations for energy-efficient end-to-end speech ...
Multi-mode LSTM network for energy-efficient speech recognition. J Jo, S Hwang, S Lee, Y Lee. 2018 International SoC Design Conference (ISOCC), 133-134, 2018.
Multi-mode LSTM network for energy-efficient speech recognition. J Jo, S Hwang, S Lee, Y Lee. 2018 International SoC Design Conference (ISOCC), 133-134, 2018.
We design the hardware architecture, named Efficient Speech Recognition Engine (ESE) that works directly on the sparse LSTM model.
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Aug 23, 2023 · The FC model achieves a classification accuracy of 86.75%, compared with 90% for the MLPerf convolutional neural network, but offers a simpler ...
Feb 20, 2017 · ABSTRACT. Long Short-Term Memory (LSTM) is widely used in speech recognition. In order to achieve higher prediction accuracy,.
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