activity
20162022
most citedSelf-Attention Transducers for End-to-End Speech Recognition

85 citations · 328 across the 28 of their papers we have counts for

collaborators

38 papers

cs.SD2022

Text Enhancement for Paragraph Processing in End-to-End Code-switching TTS

Chunyu Qiang, Jianhua Tao, Ruibo Fu +4

Current end-to-end code-switching Text-to-Speech (TTS) can already generate high quality two languages speech in the same utterance with single speaker bilingual corpora. When the…

cs.SD2022

CampNet: Context-Aware Mask Prediction for End-to-End Text-Based Speech Editing

Tao Wang, Jiangyan Yi, Ruibo Fu +2

The text-based speech editor allows the editing of speech through intuitive cutting, copying, and pasting operations to speed up the process of editing speech. However, the major d…

cs.SD20222 cited

NeuralDPS: Neural Deterministic Plus Stochastic Model with Multiband Excitation for Noise-Controllable Waveform Generation

Tao Wang, Ruibo Fu, Jiangyan Yi +2

The traditional vocoders have the advantages of high synthesis efficiency, strong interpretability, and speech editability, while the neural vocoders have the advantage of high syn…

cs.AI20222 cited

MixKG: Mixing for harder negative samples in knowledge graph

Feihu Che, Guohua Yang, Pengpeng Shao +2

Knowledge graph embedding~(KGE) aims to represent entities and relations into low-dimensional vectors for many real-world applications. The representations of entities and relation…

cs.SD20223 cited

Singing-Tacotron: Global duration control attention and dynamic filter for End-to-end singing voice synthesis

Tao Wang, Ruibo Fu, Jiangyan Yi +2

End-to-end singing voice synthesis (SVS) is attractive due to the avoidance of pre-aligned data. However, the auto learned alignment of singing voice with lyrics is difficult to ma…

cs.LG20213 cited

Multi-Level Graph Contrastive Learning

Pengpeng Shao, Tong Liu, Dawei Zhang +3

Graph representation learning has attracted a surge of interest recently, whose target at learning discriminant embedding for each node in the graph. Most of these representation m…