Adaptive Sparse and Monotonic Attention for Transformer-based Automatic Speech Recognition-Reference-Cited by-同舟云学术

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Adaptive Sparse and Monotonic Attention for Transformer-based Automatic Speech Recognition

Published:2022-10-13 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)
language:
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Author:

Zhao Chendong¹,Wang Jianzong¹,Wei Wenqi¹,Qu Xiaoyang¹,Wang Haoqian²,Xiao Jing¹

Affiliation:

1. Ping An Technology (Shenzhen) Co., Ltd.,Shenzhen,China

2. Tsinghua University,The Shenzhen International Graduate School,China

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10032305/10032324/10032360.pdf?arnumber=10032360

Reference51 articles.

1. When Hearing the Voice, Who Will Come to Your Mind

2. DT-SV: A Transformer-based Time-domain Approach for Speaker Verification

3. Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction

4. RFormer: Transformer-Based Generative Adversarial Network for Real Fundus Image Restoration on a New Clinical Benchmark

5. Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection

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