Deep learning methods for unsupervised acoustic modeling — Leap submission to ZeroSpeech challenge 2017-Reference-Cited by-同舟云学术

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Deep learning methods for unsupervised acoustic modeling — Leap submission to ZeroSpeech challenge 2017

Published:2017-12 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
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Author:

Ansari T K,Kumar Rajath,Singh Sonali,Ganapathy Sriram

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8260578/8268903/08269013.pdf?arnumber=8269013

Cited by 7 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. Representation Learning With Hidden Unit Clustering for Low Resource Speech Applications;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

2. Discovering phonetic inventories with crosslingual automatic speech recognition;Computer Speech & Language;2022-07

3. Self Supervised Representation Learning with Deep Clustering for Acoustic Unit Discovery from Raw Speech;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

4. The Effectiveness of Unsupervised Subword Modeling With Autoregressive and Cross-Lingual Phone-Aware Networks;IEEE Open Journal of Signal Processing;2021

5. Perceptimatic: A Human Speech Perception Benchmark for Unsupervised Subword Modelling;Interspeech 2020;2020-10-25

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