Mar 19, 2020 · Our model consists of three parts: TDNN, BiGRU and Attention Mechanism. TDNN models the time information and BiGRU extracts the hidden layer ...
Our model consists of three parts: TDNN, BiGRU and Attention Mechanism. TDNN models the time information and BiGRU extracts the hidden layer features of the ...
An End-to-End Model Based on TDNN-BiGRU for Keyword Spotting
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A neural network architecture based on Time-Delay Neural Network (TDNN)Bidirectional Gated Recurrent Unit (BiGRU) for small-footprint keyWord spotting and ...
The system is composed of character segmentation, feature extraction for the query keyword, and word-to-word matching. In the character segmentation step, we ...
Sep 25, 2020 · In this paper, we propose a network for small footprint keyword spotting. It includes four parts, data augmentation, Time-Delay Neural ...
An End-to-End Model Based on TDNN-BiGRU for Keyword Spotting · Streaming small-footprint keyword spotting using sequence-to-sequence models · End-to-End Speech ...
In this paper, we propose a network for small footprint keyword spotting. It includes four parts, data augmentation, Time-Delay Neural Network (TDNN) and ...
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Zhang, ''An end-to-end model based on TDNN-BiGRU for keyword spotting,'' in Proc. Int. Conf. Asian Lang. Process., Shanghai, China, Nov. 2019, pp. 402–406 ...
Nov 28, 2016 · We propose a single neural network architecture for two tasks: on-line keyword spotting and voice activity detection.
Missing: TDNN- BiGRU
An End-To-End Model Based on TDNN-BiGRU for Keyword Spotting. 2019 ... A Stochastic Segment Model for Phoneme-Based Continuous Speech Recognition. 1989 ...