1 citations · 3 across the 20 of their papers we have counts for
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Multimodal Fine-grained Context Interaction Graph Modeling for Conversational Speech Synthesis
Zhenqi Jia, Rui Liu, Berrak Sisman +1
Conversational Speech Synthesis (CSS) aims to generate speech with natural prosody by understanding the multimodal dialogue history (MDH). The latest work predicts the accurate pro…
NE-PADD: Leveraging Named Entity Knowledge for Robust Partial Audio Deepfake Detection via Attention Aggregation
Huhong Xian, Rui Liu, Berrak Sisman +1
Different from traditional sentence-level audio deepfake detection (ADD), partial audio deepfake detection (PADD) requires frame-level positioning of the location of fake speech. W…
Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech Synthesis
Rui Liu, Zhenqi Jia, Feilong Bao +1
Conversational speech synthesis (CSS) aims to take the current dialogue (CD) history as a reference to synthesize expressive speech that aligns with the conversational style. Unlik…
Emphasis Rendering for Conversational Text-to-Speech with Multi-modal Multi-scale Context Modeling
Rui Liu, Zhenqi Jia, Jie Yang +2
Conversational Text-to-Speech (CTTS) aims to accurately express an utterance with the appropriate style within a conversational setting, which attracts more attention nowadays. Whi…
FluentEditor2: Text-based Speech Editing by Modeling Multi-Scale Acoustic and Prosody Consistency
Rui Liu, Jiatian Xi, Ziyue Jiang +1
Text-based speech editing (TSE) allows users to edit speech by modifying the corresponding text directly without altering the original recording. Current TSE techniques often focus…
Generative Expressive Conversational Speech Synthesis
Rui Liu, Yifan Hu, Yi Ren +2
Conversational Speech Synthesis (CSS) aims to express a target utterance with the proper speaking style in a user-agent conversation setting. Existing CSS methods employ effective…
Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Rui Liu, Haolin Zuo, Zheng Lian +3
Emotion and Intent Joint Understanding in Multimodal Conversation (MC-EIU) aims to decode the semantic information manifested in a multimodal conversational history, while inferrin…
Emotion Rendering for Conversational Speech Synthesis with Heterogeneous Graph-Based Context Modeling
Rui Liu, Yifan Hu, Yi Ren +2
Conversational Speech Synthesis (CSS) aims to accurately express an utterance with the appropriate prosody and emotional inflection within a conversational setting. While recognisi…