activity
20202022
most citedNoise Tokens: Learning Neural Noise Templates for Environment-Aware Speech Enhancement

3 citations · 11 across the 7 of their papers we have counts for

collaborators

8 papers

cs.IT20223 cited

Hybrid HMM Decoder For Convolutional Codes By Joint Trellis-Like Structure and Channel Prior

Haoyu Li, Xuan Wang, Tong Liu +2

The anti-interference capability of wireless links is a physical layer problem for edge computing. Although convolutional codes have inherent error correction potential due to the…

eess.AS2022

Joint Noise Reduction and Listening Enhancement for Full-End Speech Enhancement

Haoyu Li, Yun Liu, Junichi Yamagishi

Speech enhancement (SE) methods mainly focus on recovering clean speech from noisy input. In real-world speech communication, however, noises often exist in not only speaker but al…

eess.AS2021

Multi-Metric Optimization using Generative Adversarial Networks for Near-End Speech Intelligibility Enhancement

Haoyu Li, Junichi Yamagishi

The intelligibility of speech severely degrades in the presence of environmental noise and reverberation. In this paper, we propose a novel deep learning based system for modifying…

eess.AS2020

Enhancing Low-Quality Voice Recordings Using Disentangled Channel Factor and Neural Waveform Model

Haoyu Li, Yang Ai, Junichi Yamagishi

High-quality speech corpora are essential foundations for most speech applications. However, such speech data are expensive and limited since they are collected in professional rec…

cs.SD2020

Denoising-and-Dereverberation Hierarchical Neural Vocoder for Robust Waveform Generation

Yang Ai, Haoyu Li, Xin Wang +2

This paper presents a denoising and dereverberation hierarchical neural vocoder (DNR-HiNet) to convert noisy and reverberant acoustic features into a clean speech waveform. We impl…

eess.AS20203 cited

Improved Prosody from Learned F0 Codebook Representations for VQ-VAE Speech Waveform Reconstruction

Yi Zhao, Haoyu Li, Cheng-I Lai +3

Vector Quantized Variational AutoEncoders (VQ-VAE) are a powerful representation learning framework that can discover discrete groups of features from a speech signal without super…