activity
20162025
most citedMonaural Speech Enhancement with Complex Convolutional Block Attention Module and Joint Time Frequency Losses

4 citations · 12 across the 12 of their papers we have counts for

collaborators

13 papers

cs.SD2025

InspireMusic: Integrating Super Resolution and Large Language Model for High-Fidelity Long-Form Music Generation

Chong Zhang, Yukun Ma, Qian Chen +12

We introduce InspireMusic, a framework integrated super resolution and large language model for high-fidelity long-form music generation. A unified framework generates high-fidelit…

eess.AS2024

Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions

Kun Zhou, You Zhang, Dianwen Ng +3

Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…

eess.AS2024

Phonetic Enhanced Language Modeling for Text-to-Speech Synthesis

Kun Zhou, Shengkui Zhao, Yukun Ma +7

Recent language model-based text-to-speech (TTS) frameworks demonstrate scalability and in-context learning capabilities. However, they suffer from robustness issues due to the acc…

cs.SD2023★ 1 cited

MossFormer2: Combining Transformer and RNN-Free Recurrent Network for Enhanced Time-Domain Monaural Speech Separation

Shengkui Zhao, Yukun Ma, Chongjia Ni +7

Our previously proposed MossFormer has achieved promising performance in monaural speech separation. However, it predominantly adopts a self-attention-based MossFormer module, whic…

cs.SD2023

Are Soft Prompts Good Zero-shot Learners for Speech Recognition?

Dianwen Ng, Chong Zhang, Ruixi Zhang +7

Large self-supervised pre-trained speech models require computationally expensive fine-tuning for downstream tasks. Soft prompt tuning offers a simple parameter-efficient alternati…

eess.AS2023

SPGM: Prioritizing Local Features for enhanced speech separation performance

Jia Qi Yip, Shengkui Zhao, Yukun Ma +8

Dual-path is a popular architecture for speech separation models (e.g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separatel…

cs.SD2023

ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention

Jia Qi Yip, Tuan Truong, Dianwen Ng +7

In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetri…

cs.SD2023★ 1 cited

Contrastive Speech Mixup for Low-resource Keyword Spotting

Dianwen Ng, Ruixi Zhang, Jia Qi Yip +6

Most of the existing neural-based models for keyword spotting (KWS) in smart devices require thousands of training samples to learn a decent audio representation. However, with the…

cs.CL2023★ 1 cited

Adaptive Knowledge Distillation between Text and Speech Pre-trained Models

Jinjie Ni, Yukun Ma, Wen Wang +7

Learning on a massive amount of speech corpus leads to the recent success of many self-supervised speech models. With knowledge distillation, these models may also benefit from the…

cs.SD2021★ 1 cited

Towards Natural and Controllable Cross-Lingual Voice Conversion Based on Neural TTS Model and Phonetic Posteriorgram

Shengkui Zhao, Hao Wang, Trung Hieu Nguyen +1

Cross-lingual voice conversion (VC) is an important and challenging problem due to significant mismatches of the phonetic set and the speech prosody of different languages. In this…

cs.SD2021★ 4 cited

Monaural Speech Enhancement with Complex Convolutional Block Attention Module and Joint Time Frequency Losses

Shengkui Zhao, Trung Hieu Nguyen, Bin Ma

Deep complex U-Net structure and convolutional recurrent network (CRN) structure achieve state-of-the-art performance for monaural speech enhancement. Both deep complex U-Net and C…

cs.SD2020★ 3 cited

Towards Natural Bilingual and Code-Switched Speech Synthesis Based on Mix of Monolingual Recordings and Cross-Lingual Voice Conversion

Shengkui Zhao, Trung Hieu Nguyen, Hao Wang +1

Recent state-of-the-art neural text-to-speech (TTS) synthesis models have dramatically improved intelligibility and naturalness of generated speech from text. However, building a g…

cs.CL2016★ 1 cited

Fantastic 4 system for NIST 2015 Language Recognition Evaluation

Kong Aik Lee, Ville Hautamäki, Anthony Larcher +14

This article describes the systems jointly submitted by Institute for Infocomm (IR), the Laboratoire d'Informatique de l'Université du Maine (LIUM), Nanyang Technology Universi…