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20232026
most citedSpeech Separation with Pretrained Frontend to Minimize Domain Mismatch

11 citations · 12 across the 24 of their papers we have counts for

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cs.SD2026

AlphaFlowTSE: One-Step Generative Target Speaker Extraction via Conditional AlphaFlow

Duojia Li, Shuhan Zhang, Zihan Qian +5

In target speaker extraction (TSE), we aim to recover target speech from a multi-talker mixture using a short enrollment utterance as reference. Recent studies on diffusion and flo…

cs.SD2025

Multi-Step Prediction and Control of Hierarchical Emotion Distribution in Text-to-Speech Synthesis

Sho Inoue, Kun Zhou, Shuai Wang +1

We investigate hierarchical emotion distribution (ED) for achieving multi-level quantitative control of emotion rendering in text-to-speech synthesis (TTS). We introduce a novel mu…

cs.SD2025

PersonaTAB: Predicting Personality Traits using Textual, Acoustic, and Behavioral Cues in Fully-Duplex Speech Dialogs

Sho Inoue, Shai Wang, Haizhou Li

Despite significant progress in neural spoken dialog systems, personality-aware conversation agents -- capable of adapting behavior based on personalities -- remain underexplored d…

cs.SD2025

Causal Self-supervised Pretrained Frontend with Predictive Code for Speech Separation

Wupeng Wang, Zexu Pan, Xinke Li +2

Speech separation (SS) seeks to disentangle a multi-talker speech mixture into single-talker speech streams. Although SS can be generally achieved using offline methods, such a pro…

cs.SD2025

Context-Aware Two-Step Training Scheme for Domain Invariant Speech Separation

Wupeng Wang, Zexu Pan, Jingru Lin +2

Speech separation seeks to isolate individual speech signals from a multi-talk speech mixture. Despite much progress, a system well-trained on synthetic data often experiences perf…

cs.SD2024

Hierarchical Control of Emotion Rendering in Speech Synthesis

Sho Inoue, Kun Zhou, Shuai Wang +1

Emotional text-to-speech synthesis (TTS) aims to generate realistic emotional speech from input text. However, quantitatively controlling multi-level emotion rendering remains chal…

cs.SD2024

MoMuSE: Momentum Multi-modal Target Speaker Extraction for Real-time Scenarios with Impaired Visual Cues

Junjie Li, Ke Zhang, Shuai Wang +3

Audio-visual Target Speaker Extraction (AV-TSE) aims to isolate the speech of a specific target speaker from an audio mixture using time-synchronized visual cues. In real-world sce…

cs.SD2024★ 11 cited

Speech Separation with Pretrained Frontend to Minimize Domain Mismatch

Wupeng Wang, Zexu Pan, Xinke Li +2

Speech separation seeks to separate individual speech signals from a speech mixture. Typically, most separation models are trained on synthetic data due to the unavailability of ta…

cs.SD2024

On the effectiveness of enrollment speech augmentation for Target Speaker Extraction

Junjie Li, Ke Zhang, Shuai Wang +3

Deep learning technologies have significantly advanced the performance of target speaker extraction (TSE) tasks. To enhance the generalization and robustness of these algorithms wh…

cs.SD2024

MacST: Multi-Accent Speech Synthesis via Text Transliteration for Accent Conversion

Sho Inoue, Shuai Wang, Wanxing Wang +3

In accented voice conversion or accent conversion, we seek to convert the accent in speech from one another while preserving speaker identity and semantic content. In this study, w…