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Pengyu Wang

6 papers hereh-index 466 citations8 works total

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

author position
  • first author3
  • middle author3

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • eess.AS4
  • cs.CV1
  • cs.SD1
same name
  • Pengyu Wang — 13 papers, h 5
  • Pengyu Wang — 12 papers, h 5
  • Pengyu Wang — 11 papers, h 10
  • Pengyu Wang — 8 papers, h 3
  • Pengyu Wang — 6 papers, h 4
  • Pengyu Wang — 5 papers, h 6

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
20232026
collaborators
Showing eess.ASShow all

4 papers · 1 filter

eess.AS2025

Blind Room Impulse Response Identification via Reverberant Speech Spectrum Reconstruction

Pengyu Wang, Xiaofei Li

This paper proposes Rec-RIR for blind room impulse response (RIR) identification. Based on the convolutive transfer function (CTF) approximation, we propose a multi-task deep neura…

eess.AS2025

CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR

Nian Shao, Rui Zhou, Pengyu Wang +4

In this work, we propose CleanMel, a single-channel Mel-spectrogram denoising and dereverberation network for improving both speech quality and automatic speech recognition (ASR) p…

eess.AS2025

VINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR Identification

Pengyu Wang, Ying Fang, Xiaofei Li

Reverberant speech, denoting the speech signal degraded by reverberation, contains crucial knowledge of both anechoic source speech and room impulse response (RIR). This work propo…

eess.AS2023

RVAE-EM: Generative speech dereverberation based on recurrent variational auto-encoder and convolutive transfer function

Pengyu Wang, Xiaofei Li

In indoor scenes, reverberation is a crucial factor in degrading the perceived quality and intelligibility of speech. In this work, we propose a generative dereverberation method.…

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