20 citations · 88 across the 13 of their papers we have counts for
15 papers
Simple and Effective Unsupervised Speech Synthesis
Alexander H. Liu, Cheng-I Jeff Lai, Wei-Ning Hsu +3
We introduce the first unsupervised speech synthesis system based on a simple, yet effective recipe. The framework leverages recent work in unsupervised speech recognition as well…
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…
On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis
Cheng-I Jeff Lai, Erica Cooper, Yang Zhang +8
Are end-to-end text-to-speech (TTS) models over-parametrized? To what extent can these models be pruned, and what happens to their synthesis capabilities? This work serves as a sta…
Cross-Modal Discrete Representation Learning
Alexander H. Liu, SouYoung Jin, Cheng-I Jeff Lai +3
Recent advances in representation learning have demonstrated an ability to represent information from different modalities such as video, text, and audio in a single high-level emb…
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu +7
Self-supervised speech representation learning (speech SSL) has demonstrated the benefit of scale in learning rich representations for Automatic Speech Recognition (ASR) with limit…
SUPERB: Speech processing Universal PERformance Benchmark
Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang +17
Self-supervised learning (SSL) has proven vital for advancing research in natural language processing (NLP) and computer vision (CV). The paradigm pretrains a shared model on large…