7 citations · 13 across the 5 of their papers we have counts for
5 papers
A Systematic Exploration of Joint-training for Singing Voice Synthesis
Yuning Wu, Yifeng Yu, Jiatong Shi +2
There has been a growing interest in using end-to-end acoustic models for singing voice synthesis (SVS). Typically, these models require an additional vocoder to transform the gene…
PHONEix: Acoustic Feature Processing Strategy for Enhanced Singing Pronunciation with Phoneme Distribution Predictor
Yuning Wu, Jiatong Shi, Tao Qian +2
Singing voice synthesis (SVS), as a specific task for generating the vocal singing voice from a music score, has drawn much attention in recent years. SVS faces the challenge that…
MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition
Jinming Zhao, Ruichen Li, Qin Jin +2
Multimodal emotion recognition study is hindered by the lack of labelled corpora in terms of scale and diversity, due to the high annotation cost and label ambiguity. In this paper…
Sequence-to-sequence Singing Voice Synthesis with Perceptual Entropy Loss
Jiatong Shi, Shuai Guo, Nan Huo +2
The neural network (NN) based singing voice synthesis (SVS) systems require sufficient data to train well and are prone to over-fitting due to data scarcity. However, we often enco…
Context-aware Goodness of Pronunciation for Computer-Assisted Pronunciation Training
Jiatong Shi, Nan Huo, Qin Jin
Mispronunciation detection is an essential component of the Computer-Assisted Pronunciation Training (CAPT) systems. State-of-the-art mispronunciation detection models use Deep Neu…