activity
20212023
most citedBuilding Synthetic Speaker Profiles in Text-to-Speech Systems

2 citations · 5 across the 6 of their papers we have counts for

collaborators

7 papers

cs.SD2023

CALM: Contrastive Cross-modal Speaking Style Modeling for Expressive Text-to-Speech Synthesis

Yi Meng, Xiang Li, Zhiyong Wu +6

To further improve the speaking styles of synthesized speeches, current text-to-speech (TTS) synthesis systems commonly employ reference speeches to stylize their outputs instead o…

cs.SD2023

Joint Multi-scale Cross-lingual Speaking Style Transfer with Bidirectional Attention Mechanism for Automatic Dubbing

Jingbei Li, Sipan Li, Ping Chen +7

Automatic dubbing, which generates a corresponding version of the input speech in another language, could be widely utilized in many real-world scenarios such as video and game loc…

eess.AS2022★ 1 cited

Graph-based Multi-View Fusion and Local Adaptation: Mitigating Within-Household Confusability for Speaker Identification

Long Chen, Yixiong Meng, Venkatesh Ravichandran +1

Speaker identification (SID) in the household scenario (e.g., for smart speakers) is an important but challenging problem due to limited number of labeled (enrollment) utterances,…

cs.SD2022★ 1 cited

NeuFA: Neural Network Based End-to-End Forced Alignment with Bidirectional Attention Mechanism

Jingbei Li, Yi Meng, Zhiyong Wu +4

Although deep learning and end-to-end models have been widely used and shown superiority in automatic speech recognition (ASR) and text-to-speech (TTS) synthesis, state-of-the-art…

eess.AS2022★ 2 cited

Building Synthetic Speaker Profiles in Text-to-Speech Systems

Jie Pu, Yixiong Meng, Oguz Elibol

The diversity of speaker profiles in multi-speaker TTS systems is a crucial aspect of its performance, as it measures how many different speaker profiles TTS systems could possibly…

cs.LG2021

SynthASR: Unlocking Synthetic Data for Speech Recognition

Amin Fazel, Wei Yang, Yulan Liu +4

End-to-end (E2E) automatic speech recognition (ASR) models have recently demonstrated superior performance over the traditional hybrid ASR models. Training an E2E ASR model require…

cs.SD2021★ 1 cited

Enhancing Speaking Styles in Conversational Text-to-Speech Synthesis with Graph-based Multi-modal Context Modeling

Jingbei Li, Yi Meng, Chenyi Li +4

Comparing with traditional text-to-speech (TTS) systems, conversational TTS systems are required to synthesize speeches with proper speaking style confirming to the conversational…