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Po-Chun Hsu

4 papers hereh-index 171.5k citations41 works total

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.AS3
  • cs.SD1
same name
  • Po-chun Hsu — 12 papers, h 8
  • Po-Chun Hsu — 8 papers, h 5
  • Po-Chun Hsu — 2 papers, h 0
  • Po-Chun Hsu — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192023
most citedMockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders

352 citations · 376 across the 3 of their papers we have counts for

collaborators

4 papers

eess.AS2023★ 1 cited

Low-Resource Self-Supervised Learning with SSL-Enhanced TTS

Po-chun Hsu, Ali Elkahky, Wei-Ning Hsu +6

Self-supervised learning (SSL) techniques have achieved remarkable results in various speech processing tasks. Nonetheless, a significant challenge remains in reducing the reliance…

eess.AS2020

WG-WaveNet: Real-Time High-Fidelity Speech Synthesis without GPU

Po-chun Hsu, Hung-yi Lee

In this paper, we propose WG-WaveNet, a fast, lightweight, and high-quality waveform generation model. WG-WaveNet is composed of a compact flow-based model and a post-filter. The t…

cs.SD2019★ 23 cited

Towards Robust Neural Vocoding for Speech Generation: A Survey

Po-chun Hsu, Chun-hsuan Wang, Andy T. Liu +1

Recently, neural vocoders have been widely used in speech synthesis tasks, including text-to-speech and voice conversion. However, when encountering data distribution mismatch betw…

eess.AS2019★ 352 cited

Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders

Andy T. Liu, Shu-wen Yang, Po-Han Chi +2

We present Mockingjay as a new speech representation learning approach, where bidirectional Transformer encoders are pre-trained on a large amount of unlabeled speech. Previous spe…

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