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20102023
most citedSelf-Supervised Speech Representation Learning: A Review

371 citations · 804 across the 127 of their papers we have counts for

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Showing 2021 · cs.SDShow all

7 papers · 2 filters

cs.SD2021★ 1 cited

Characterizing the adversarial vulnerability of speech self-supervised learning

Haibin Wu, Bo Zheng, Xu Li +3

A leaderboard named Speech processing Universal PERformance Benchmark (SUPERB), which aims at benchmarking the performance of a shared self-supervised learning (SSL) speech model a…

cs.SD2021★ 54 cited

Meta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech

Sung-Feng Huang, Chyi-Jiunn Lin, Da-Rong Liu +2

Personalizing a speech synthesis system is a highly desired application, where the system can generate speech with the user's voice with rare enrolled recordings. There are two mai…

cs.SD2021★ 2 cited

S3PRL-VC: Open-source Voice Conversion Framework with Self-supervised Speech Representations

Wen-Chin Huang, Shu-Wen Yang, Tomoki Hayashi +3

This paper introduces S3PRL-VC, an open-source voice conversion (VC) framework based on the S3PRL toolkit. In the context of recognition-synthesis VC, self-supervised speech repres…

cs.SD2021

Adversarial Sample Detection for Speaker Verification by Neural Vocoders

Haibin Wu, Po-chun Hsu, Ji Gao +6

Automatic speaker verification (ASV), one of the most important technology for biometric identification, has been widely adopted in security-critical applications. However, ASV is…

cs.SD2021

Multi-accent Speech Separation with One Shot Learning

Kuan-Po Huang, Yuan-Kuei Wu, Hung-yi Lee

Speech separation is a problem in the field of speech processing that has been studied in full swing recently. However, there has not been much work studying a multi-accent speech…

cs.SD2021

Improving the Adversarial Robustness for Speaker Verification by Self-Supervised Learning

Haibin Wu, Xu Li, Andy T. Liu +3

Previous works have shown that automatic speaker verification (ASV) is seriously vulnerable to malicious spoofing attacks, such as replay, synthetic speech, and recently emerged ad…