1 citations · 3 across the 20 of their papers we have counts for
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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…
Multi-Source Spatial Knowledge Understanding for Immersive Visual Text-to-Speech
Shuwei He, Rui Liu
Visual Text-to-Speech (VTTS) aims to take the environmental image as the prompt to synthesize reverberant speech for the spoken content. Previous works focus on the RGB modality fo…
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…
Fine-Grained Quantitative Emotion Editing for Speech Generation
Sho Inoue, Kun Zhou, Shuai Wang +1
It remains a significant challenge how to quantitatively control the expressiveness of speech emotion in speech generation. In this work, we present a novel approach for manipulati…