activity
20192025
most citedAny-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence Modeling

84 citations · 183 across the 32 of their papers we have counts for

collaborators

32 papers

eess.AS2025

learning discriminative features from spectrograms using center loss for speech emotion recognition

Dongyang Dai, Zhiyong Wu, Runnan Li +3

Identifying the emotional state from speech is essential for the natural interaction of the machine with the speaker. However, extracting effective features for emotion recognition…

eess.AS2025

Disambiguation of Chinese Polyphones in an End-to-End Framework with Semantic Features Extracted by Pre-trained BERT

Dongyang Dai, Zhiyong Wu, Shiyin Kang +5

Grapheme-to-phoneme (G2P) conversion serves as an essential component in Chinese Mandarin text-to-speech (TTS) system, where polyphone disambiguation is the core issue. In this pap…

cs.SD2023

Improving Language Model-Based Zero-Shot Text-to-Speech Synthesis with Multi-Scale Acoustic Prompts

Shun Lei, Yixuan Zhou, Liyang Chen +8

Zero-shot text-to-speech (TTS) synthesis aims to clone any unseen speaker's voice without adaptation parameters. By quantizing speech waveform into discrete acoustic tokens and mod…

cs.CL2023

Natural Language Embedded Programs for Hybrid Language Symbolic Reasoning

Tianhua Zhang, Jiaxin Ge, Hongyin Luo +7

How can we perform computations over natural language representations to solve tasks that require symbolic and numeric reasoning? We propose natural language embedded programs (NLE…

cs.SD2023

QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation Learning

Haohan Guo, Fenglong Xie, Jiawen Kang +3

This paper proposes a novel semi-supervised TTS framework, QS-TTS, to improve TTS quality with lower supervised data requirements via Vector-Quantized Self-Supervised Speech Repres…

cs.SD2023

Improving Mandarin Prosodic Structure Prediction with Multi-level Contextual Information

Jie Chen, Changhe Song, Deyi Tuo +4

For text-to-speech (TTS) synthesis, prosodic structure prediction (PSP) plays an important role in producing natural and intelligible speech. Although inter-utterance linguistic in…

cs.CL2023★ 5 cited

Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories?

Jingyan Zhou, Minda Hu, Junan Li +4

Making moral judgments is an essential step toward developing ethical AI systems. Prevalent approaches are mostly implemented in a bottom-up manner, which uses a large set of annot…

cs.SD2023★ 1 cited

MSStyleTTS: Multi-Scale Style Modeling with Hierarchical Context Information for Expressive Speech Synthesis

Shun Lei, Yixuan Zhou, Liyang Chen +4

Expressive speech synthesis is crucial for many human-computer interaction scenarios, such as audiobooks, podcasts, and voice assistants. Previous works focus on predicting the sty…

cs.CL2023★ 6 cited

SAIL: Search-Augmented Instruction Learning

Hongyin Luo, Yung-Sung Chuang, Yuan Gong +6

Large language models (LLMs) have been significantly improved by instruction fine-tuning, but still lack transparency and the ability to utilize up-to-date knowledge and informatio…

cs.SD2023★ 1 cited

Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator

Lingwei Meng, Jiawen Kang, Mingyu Cui +3

Multi-talker overlapped speech poses a significant challenge for speech recognition and diarization. Recent research indicated that these two tasks are inter-dependent and compleme…

cs.CL2023★ 8 cited

Interpretable Unified Language Checking

Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang +7

Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-…

eess.AS2023

A Hierarchical Regression Chain Framework for Affective Vocal Burst Recognition

Jinchao Li, Xixin Wu, Kaitao Song +3

As a common way of emotion signaling via non-linguistic vocalizations, vocal burst (VB) plays an important role in daily social interaction. Understanding and modeling human vocal…

eess.AS2023★ 1 cited

Leveraging Pretrained Representations with Task-related Keywords for Alzheimer's Disease Detection

Jinchao Li, Kaitao Song, Junan Li +5

With the global population aging rapidly, Alzheimer's disease (AD) is particularly prominent in older adults, which has an insidious onset and leads to a gradual, irreversible dete…

cs.SD2023★ 1 cited

A Sidecar Separator Can Convert a Single-Talker Speech Recognition System to a Multi-Talker One

Lingwei Meng, Jiawen Kang, Mingyu Cui +3

Although automatic speech recognition (ASR) can perform well in common non-overlapping environments, sustaining performance in multi-talker overlapping speech recognition remains c…

cs.CL2023

Improving Rare Words Recognition through Homophone Extension and Unified Writing for Low-resource Cantonese Speech Recognition

HoLam Chung, Junan Li, Pengfei Liu1 +3

Homophone characters are common in tonal syllable-based languages, such as Mandarin and Cantonese. The data-intensive end-to-end Automatic Speech Recognition (ASR) systems are more…

cs.SD2022★ 2 cited

Towards High-Quality Neural TTS for Low-Resource Languages by Learning Compact Speech Representations

Haohan Guo, Fenglong Xie, Xixin Wu +2

This paper aims to enhance low-resource TTS by reducing training data requirements using compact speech representations. A Multi-Stage Multi-Codebook (MSMC) VQ-GAN is trained to le…

eess.AS2022

Disentangled Speech Representation Learning for One-Shot Cross-lingual Voice Conversion Using -VAE

Hui Lu, Disong Wang, Xixin Wu +3

We propose an unsupervised learning method to disentangle speech into content representation and speaker identity representation. We apply this method to the challenging one-shot c…

cs.SD2022

A Multi-Stage Multi-Codebook VQ-VAE Approach to High-Performance Neural TTS

Haohan Guo, Fenglong Xie, Frank K. Soong +2

We propose a Multi-Stage, Multi-Codebook (MSMC) approach to high-performance neural TTS synthesis. A vector-quantized, variational autoencoder (VQ-VAE) based feature analyzer is us…

cs.SD2022

Tackling Spoofing-Aware Speaker Verification with Multi-Model Fusion

Haibin Wu, Jiawen Kang, Lingwei Meng +5

Recent years have witnessed the extraordinary development of automatic speaker verification (ASV). However, previous works show that state-of-the-art ASV models are seriously vulne…

cs.LG2022

Exploring linguistic feature and model combination for speech recognition based automatic AD detection

Yi Wang, Tianzi Wang, Zi Ye +5

Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care and delay progression. Speech based automatic AD screening systems provide a non-intrusive an…

cs.SD2022

Neural Architecture Search for Speech Emotion Recognition

Xixin Wu, Shoukang Hu, Zhiyong Wu +2

Deep neural networks have brought significant advancements to speech emotion recognition (SER). However, the architecture design in SER is mainly based on expert knowledge and empi…

cs.SD2022★ 1 cited

Spoofing-Aware Speaker Verification by Multi-Level Fusion

Haibin Wu, Lingwei Meng, Jiawen Kang +5

Recently, many novel techniques have been introduced to deal with spoofing attacks, and achieve promising countermeasure (CM) performances. However, these works only take the stand…

cs.SD2022

A Multi-Scale Time-Frequency Spectrogram Discriminator for GAN-based Non-Autoregressive TTS

Haohan Guo, Hui Lu, Xixin Wu +1

The generative adversarial network (GAN) has shown its outstanding capability in improving Non-Autoregressive TTS (NAR-TTS) by adversarially training it with an extra model that di…

cs.CL2022★ 15 cited

Estimating the Uncertainty in Emotion Class Labels with Utterance-Specific Dirichlet Priors

Wen Wu, Chao Zhang, Xixin Wu +1

Emotion recognition is a key attribute for artificial intelligence systems that need to naturally interact with humans. However, the task definition is still an open problem due to…