End-to-end speaker diarization of Tibetan based on BLSTM-Reference-Cited by-同舟云学术

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End-to-end speaker diarization of Tibetan based on BLSTM

Published:2022-07 Issue: Volume: Page:
ISSN:
Container-title:2022 Global Conference on Robotics, Artificial Intelligence and Information Technology (GCRAIT)
language:
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Author:

Gan Zhenve¹,Guo Hanwen²,Li Tingting¹,Ding Xu¹,Li Jincheng¹,Qu Ziqian¹

Affiliation:

1. School of Physics and Electronic Engineering, Northwest Normal University, Engineering Research Center of Gansu,Province for Intelligent Information, Technology and Application,Lanzhou,China

2. School of Physics and Electronic Engineering, Northwest Normal University,Lanzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9898141/9898099/09898377.pdf?arnumber=9898377

Reference10 articles.

1. BUT System for DIHARD Speech Diarization Challenge 2018

2. Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge

3. A study on data augmentation of reverberant speech for robust speech recognition

4. Fully Supervised Speaker Diarization

5. Speaker Diarization with Enhancing Speech for the First DIHARD Challenge

Cited by 1 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. A new speaker-diarization technology with denoising spectral-LSTM for online automatic multi-dialogue recording;Multimedia Tools and Applications;2023-10-21

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