activity
20172022
most citedMinimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition

16 citations · 54 across the 11 of their papers we have counts for

collaborators

11 papers

eess.AS20225 cited

NeuralEcho: A Self-Attentive Recurrent Neural Network For Unified Acoustic Echo Suppression And Speech Enhancement

Meng Yu, Yong Xu, Chunlei Zhang +2

Acoustic echo cancellation (AEC) plays an important role in the full-duplex speech communication as well as the front-end speech enhancement for recognition in the conditions when…

eess.AS2022

Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion

Jiachen Lian, Chunlei Zhang, Dong Yu

Traditional studies on voice conversion (VC) have made progress with parallel training data and known speakers. Good voice conversion quality is obtained by exploring better alignm…

eess.AS20215 cited

MetricNet: Towards Improved Modeling For Non-Intrusive Speech Quality Assessment

Meng Yu, Chunlei Zhang, Yong Xu +2

The objective speech quality assessment is usually conducted by comparing received speech signal with its clean reference, while human beings are capable of evaluating the speech q…

eess.AS2021

Towards Robust Speaker Verification with Target Speaker Enhancement

Chunlei Zhang, Meng Yu, Chao Weng +1

This paper proposes the target speaker enhancement based speaker verification network (TASE-SVNet), an all neural model that couples target speaker enhancement and speaker embeddin…

cs.SD202010 cited

Phonetic Posteriorgrams based Many-to-Many Singing Voice Conversion via Adversarial Training

Haohan Guo, Heng Lu, Na Hu +5

This paper describes an end-to-end adversarial singing voice conversion (EA-SVC) approach. It can directly generate arbitrary singing waveform by given phonetic posteriorgram (PPG)…

eess.AS20202 cited

Self-supervised Text-independent Speaker Verification using Prototypical Momentum Contrastive Learning

Wei Xia, Chunlei Zhang, Chao Weng +2

In this study, we investigate self-supervised representation learning for speaker verification (SV). First, we examine a simple contrastive learning approach (SimCLR) with a moment…