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Cheng-I Lai

Massachusetts Institute of Technology

22 papers hereh-index 182.9k citations28 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author8
  • middle author12
  • last author1

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CL11
  • eess.AS5
  • cs.SD4
  • cs.CV1
  • cs.LG1
affiliations
  • Massachusetts Institute of Technology
Homepage

identity via Semantic Scholar / OpenAlex

activity
20182024
most citedSUPERB: Speech processing Universal PERformance Benchmark

53 citations · 175 across the 22 of their papers we have counts for

collaborators
Showing cs.SDShow all

4 papers · 1 filter

cs.SD2022★ 1 cited

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…

cs.SD2022★ 24 cited

ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers

Kaizhi Qian, Yang Zhang, Heting Gao +5

Self-supervised learning in speech involves training a speech representation network on a large-scale unannotated speech corpus, and then applying the learned representations to do…

cs.SD2021

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…

cs.SD2021★ 3 cited

SSAST: Self-Supervised Audio Spectrogram Transformer

Yuan Gong, Cheng-I Jeff Lai, Yu-An Chung +1

Recently, neural networks based purely on self-attention, such as the Vision Transformer (ViT), have been shown to outperform deep learning models constructed with convolutional ne…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.