Flexible Keyword Spotting Based on Homogeneous Audio-Text Embedding-Reference-Cited by-同舟云学术

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Flexible Keyword Spotting Based on Homogeneous Audio-Text Embedding

Published:2024-04-14 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Nishu Kumari¹,Cho Minsik¹,Dixon Paul¹,Naik Devang¹

Affiliation:

1. Apple

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447547.pdf?arnumber=10447547

Reference19 articles.

1. Small-footprint keyword spotting using deep neural networks

2. Deep Residual Learning for Small-Footprint Keyword Spotting

3. Learning Efficient Representations for Keyword Spotting with Triplet Loss

4. Generalized Keyword Spotting using ASR embeddings

5. Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Iphonmatchnet: Zero-Shot User-Defined Keyword Spotting Using Implicit Acoustic Echo Cancellation;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Open-Vocabulary Keyword-Spotting with Adaptive Instance Normalization;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Bridging the Gap Between Audio and Text Using Parallel-Attention for User-Defined Keyword Spotting;IEEE Signal Processing Letters;2024

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