58 citations · 150 across the 81 of their papers we have counts for
24 papers · 1 filter
Linguistic-Enhanced Transformer with CTC Embedding for Speech Recognition
Xulong Zhang, Jianzong Wang, Ning Cheng +3
The recent emergence of joint CTC-Attention model shows significant improvement in automatic speech recognition (ASR). The improvement largely lies in the modeling of linguistic in…
Improving Imbalanced Text Classification with Dynamic Curriculum Learning
Xulong Zhang, Jianzong Wang, Ning Cheng +1
Recent advances in pre-trained language models have improved the performance for text classification tasks. However, little attention is paid to the priority scheduling strategy on…
Semi-Supervised Learning Based on Reference Model for Low-resource TTS
Xulong Zhang, Jianzong Wang, Ning Cheng +1
Most previous neural text-to-speech (TTS) methods are mainly based on supervised learning methods, which means they depend on a large training dataset and hard to achieve comparabl…
MetaSpeech: Speech Effects Switch Along with Environment for Metaverse
Xulong Zhang, Jianzong Wang, Ning Cheng +1
Metaverse expands the physical world to a new dimension, and the physical environment and Metaverse environment can be directly connected and entered. Voice is an indispensable com…
Improving Speech Representation Learning via Speech-level and Phoneme-level Masking Approach
Xulong Zhang, Jianzong Wang, Ning Cheng +2
Recovering the masked speech frames is widely applied in speech representation learning. However, most of these models use random masking in the pre-training. In this work, we prop…
Adapitch: Adaption Multi-Speaker Text-to-Speech Conditioned on Pitch Disentangling with Untranscribed Data
Xulong Zhang, Jianzong Wang, Ning Cheng +1
In this paper, we proposed Adapitch, a multi-speaker TTS method that makes adaptation of the supervised module with untranscribed data. We design two self supervised modules to tra…