2 citations · 2 across the 8 of their papers we have counts for
8 papers
COT-TTS: Audio Context-Aware Text-to-Speech with Chain-of-Thought Reasoning
Weizhen Bian, Sitong Cheng, Rongxiu Zhong +9
Recently, text-to-speech systems have made significant progress in speech expressiveness and controllability. However, the speaking style of generated speech typically relies on cl…
UniVerse: Benchmarking and Enhancing LALMs on Culturally Inclusive Low-Resource Music Understanding
Ziya Zhou, Shangda Wu, Shenyang Xu +16
Recent advances in large audio-language models (LALMs) have significantly improved performance in tasks such as music captioning, genre classification, and sound event detection. H…
B-GRPO: Unsupervised Speech Emotion Recognition based on Batched-Group Relative Policy Optimization
Yingying Gao, Shilei Zhang, Runyan Yang +2
Unsupervised speech emotion recognition (SER) focuses on addressing the problem of data sparsity and annotation bias of emotional speech. Reinforcement learning (RL) is a promising…
OneVoice: One Model, Triple Scenarios-Towards Unified Zero-shot Voice Conversion
Zhichao Wang, Tao Li, Wenshuo Ge +3
Recent progress of voice conversion~(VC) has achieved a new milestone in speaker cloning and linguistic preservation. But the field remains fragmented, relying on specialized model…
Exploring Energy-Based Models for Out-of-Distribution Detection in Dialect Identification
Yaqian Hao, Chenguang Hu, Yingying Gao +2
The diverse nature of dialects presents challenges for models trained on specific linguistic patterns, rendering them susceptible to errors when confronted with unseen or out-of-di…
On Calibration of Speech Classification Models: Insights from Energy-Based Model Investigations
Yaqian Hao, Chenguang Hu, Yingying Gao +2
For speech classification tasks, deep learning models often achieve high accuracy but exhibit shortcomings in calibration, manifesting as classifiers exhibiting overconfidence. The…
CEC: A Noisy Label Detection Method for Speaker Recognition
Yao Shen, Yingying Gao, Yaqian Hao +4
Noisy labels are inevitable, even in well-annotated datasets. The detection of noisy labels is of significant importance to enhance the robustness of speaker recognition models. In…
MFSN: Multi-perspective Fusion Search Network For Pre-training Knowledge in Speech Emotion Recognition
Haiyang Sun, Fulin Zhang, Yingying Gao +3
Speech Emotion Recognition (SER) is an important research topic in human-computer interaction. Many recent works focus on directly extracting emotional cues through pre-trained kno…