8 citations · 28 across the 8 of their papers we have counts for
10 papers
SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learning
Tzu-hsun Feng, Annie Dong, Ching-Feng Yeh +11
We present the SUPERB challenge at SLT 2022, which aims at learning self-supervised speech representation for better performance, generalization, and efficiency. The challenge buil…
Investigating self-supervised learning for speech enhancement and separation
Zili Huang, Shinji Watanabe, Shu-wen Yang +2
Speech enhancement and separation are two fundamental tasks for robust speech processing. Speech enhancement suppresses background noise while speech separation extracts target spe…
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities
Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang +14
Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervi…
Speech Representation Learning Through Self-supervised Pretraining And Multi-task Finetuning
Yi-Chen Chen, Shu-wen Yang, Cheng-Kuang Lee +2
Speech representation learning plays a vital role in speech processing. Among them, self-supervised learning (SSL) has become an important research direction. It has been shown tha…
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…
An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition
Xuankai Chang, Takashi Maekaku, Pengcheng Guo +8
Self-supervised pretraining on speech data has achieved a lot of progress. High-fidelity representation of the speech signal is learned from a lot of untranscribed data and shows p…