13 citations · 31 across the 55 of their papers we have counts for
11 papers · 1 filter
Attention-weighted Centered Kernel Alignment for Knowledge Distillation in Large Audio-Language Models Applied to Speech Emotion Recognition
Qingran Yang, Botao Zhao, Zuheng Kang +7
The emergence of Large Audio-Language Models (LALMs) has advanced Speech Emotion Recognition (SER), but their size limits deployment in resource-constrained environments. While Kno…
EMO-RL: Emotion-Rule-Based Reinforcement Learning Enhanced Audio-Language Model for Generalized Speech Emotion Recognition
Pengcheng Li, Botao Zhao, Zuheng Kang +4
Although Large Audio-Language Models (LALMs) have exhibited outstanding performance in auditory understanding, their performance in affective computing scenarios, particularly in e…
Generalized Audio Deepfake Detection Using Frame-level Latent Information Entropy
Botao Zhao, Zuheng Kang, Yayun He +4
Generalizability, the capacity of a robust model to perform effectively on unseen data, is crucial for audio deepfake detection due to the rapid evolution of text-to-speech (TTS) a…
CycleFlow: Leveraging Cycle Consistency in Flow Matching for Speaker Style Adaptation
Ziqi Liang, Xulong Zhang, Chang Liu +3
Voice Conversion (VC) aims to convert the style of a source speaker, such as timbre and pitch, to the style of any target speaker while preserving the linguistic content. However,…
Retrieval-Augmented Audio Deepfake Detection
Zuheng Kang, Yayun He, Botao Zhao +4
With recent advances in speech synthesis including text-to-speech (TTS) and voice conversion (VC) systems enabling the generation of ultra-realistic audio deepfakes, there is growi…
Feature-Rich Audio Model Inversion for Data-Free Knowledge Distillation Towards General Sound Classification
Zuheng Kang, Yayun He, Jianzong Wang +3
Data-Free Knowledge Distillation (DFKD) has recently attracted growing attention in the academic community, especially with major breakthroughs in computer vision. Despite promisin…
Learning Invariant Representation and Risk Minimized for Unsupervised Accent Domain Adaptation
Chendong Zhao, Jianzong Wang, Xiaoyang Qu +2
Unsupervised representation learning for speech audios attained impressive performances for speech recognition tasks, particularly when annotated speech is limited. However, the un…
DT-SV: A Transformer-based Time-domain Approach for Speaker Verification
Nan Zhang, Jianzong Wang, Zhenhou Hong +3
Speaker verification (SV) aims to determine whether the speaker's identity of a test utterance is the same as the reference speech. In the past few years, extracting speaker embedd…
Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection
Chendong Zhao, Jianzong Wang, Leilai Li +2
Sound event detection is to infer the event by understanding the surrounding environmental sounds. Due to the scarcity of rare sound events, it becomes challenging for the well-tra…
Speech2Video: Cross-Modal Distillation for Speech to Video Generation
Shijing Si, Jianzong Wang, Xiaoyang Qu +4
This paper investigates a novel task of talking face video generation solely from speeches. The speech-to-video generation technique can spark interesting applications in entertain…
Variational Information Bottleneck for Effective Low-resource Audio Classification
Shijing Si, Jianzong Wang, Huiming Sun +6
Large-scale deep neural networks (DNNs) such as convolutional neural networks (CNNs) have achieved impressive performance in audio classification for their powerful capacity and st…