19 citations · 127 across the 127 of their papers we have counts for
127 papers
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…
RUNA: Object-level Out-of-Distribution Detection via Regional Uncertainty Alignment of Multimodal Representations
Bin Zhang, Jinggang Chen, Xiaoyang Qu +5
Enabling object detectors to recognize out-of-distribution (OOD) objects is vital for building reliable systems. A primary obstacle stems from the fact that models frequently do no…
ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression
Botao Zhao, Xiaoyang Qu, Zuheng Kang +3
In deep regression, capturing the relationship among continuous labels in feature space is a fundamental challenge that has attracted increasing interest. Addressing this issue can…
IDEAW: Robust Neural Audio Watermarking with Invertible Dual-Embedding
Pengcheng Li, Xulong Zhang, Jing Xiao +1
The audio watermarking technique embeds messages into audio and accurately extracts messages from the watermarked audio. Traditional methods develop algorithms based on expert expe…
PFID: Privacy First Inference Delegation Framework for LLMs
Haoyan Yang, Zhitao Li, Yong Zhang +4
This paper introduces a novel privacy-preservation framework named PFID for LLMs that addresses critical privacy concerns by localizing user data through model sharding and singula…
Enhancing Emotion Recognition in Conversation through Emotional Cross-Modal Fusion and Inter-class Contrastive Learning
Haoxiang Shi, Xulong Zhang, Ning Cheng +4
The purpose of emotion recognition in conversation (ERC) is to identify the emotion category of an utterance based on contextual information. Previous ERC methods relied on simple…
RREH: Reconstruction Relations Embedded Hashing for Semi-Paired Cross-Modal Retrieval
Jianzong Wang, Haoxiang Shi, Kaiyi Luo +3
Known for efficient computation and easy storage, hashing has been extensively explored in cross-modal retrieval. The majority of current hashing models are predicated on the premi…
RSET: Remapping-based Sorting Method for Emotion Transfer Speech Synthesis
Haoxiang Shi, Jianzong Wang, Xulong Zhang +3
Although current Text-To-Speech (TTS) models are able to generate high-quality speech samples, there are still challenges in developing emotion intensity controllable TTS. Most exi…
Task-agnostic Decision Transformer for Multi-type Agent Control with Federated Split Training
Zhiyuan Wang, Bokui Chen, Xiaoyang Qu +3
With the rapid advancements in artificial intelligence, the development of knowledgeable and personalized agents has become increasingly prevalent. However, the inherent variabilit…
MAIN-VC: Lightweight Speech Representation Disentanglement for One-shot Voice Conversion
Pengcheng Li, Jianzong Wang, Xulong Zhang +3
One-shot voice conversion aims to change the timbre of any source speech to match that of the unseen target speaker with only one speech sample. Existing methods face difficulties…
Learning Expressive Disentangled Speech Representations with Soft Speech Units and Adversarial Style Augmentation
Yimin Deng, Jianzong Wang, Xulong Zhang +2
Voice conversion is the task to transform voice characteristics of source speech while preserving content information. Nowadays, self-supervised representation learning models are…
QLSC: A Query Latent Semantic Calibrator for Robust Extractive Question Answering
Sheng Ouyang, Jianzong Wang, Yong Zhang +5
Extractive Question Answering (EQA) in Machine Reading Comprehension (MRC) often faces the challenge of dealing with semantically identical but format-variant inputs. Our work intr…
EfficientASR: Speech Recognition Network Compression via Attention Redundancy and Chunk-Level FFN Optimization
Jianzong Wang, Ziqi Liang, Xulong Zhang +2
In recent years, Transformer networks have shown remarkable performance in speech recognition tasks. However, their deployment poses challenges due to high computational and storag…
EAD-VC: Enhancing Speech Auto-Disentanglement for Voice Conversion with IFUB Estimator and Joint Text-Guided Consistent Learning
Ziqi Liang, Jianzong Wang, Xulong Zhang +3
Using unsupervised learning to disentangle speech into content, rhythm, pitch, and timbre for voice conversion has become a hot research topic. Existing works generally take into a…
CONTUNER: Singing Voice Beautifying with Pitch and Expressiveness Condition
Jianzong Wang, Pengcheng Li, Xulong Zhang +2
Singing voice beautifying is a novel task that has application value in people's daily life, aiming to correct the pitch of the singing voice and improve the expressiveness without…
Medical Speech Symptoms Classification via Disentangled Representation
Jianzong Wang, Pengcheng Li, Xulong Zhang +2
Intent is defined for understanding spoken language in existing works. Both textual features and acoustic features involved in medical speech contain intent, which is important for…
Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning
Zuheng Kang, Yayun He, Jianzong Wang +2
Single-model systems often suffer from deficiencies in tasks such as speaker verification (SV) and image classification, relying heavily on partial prior knowledge during decision-…
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…
Value-Driven Mixed-Precision Quantization for Patch-Based Inference on Microcontrollers
Wei Tao, Shenglin He, Kai Lu +5
Deploying neural networks on microcontroller units (MCUs) presents substantial challenges due to their constrained computation and memory resources. Previous researches have explor…
Leveraging Biases in Large Language Models: "bias-kNN'' for Effective Few-Shot Learning
Yong Zhang, Hanzhang Li, Zhitao Li +4
Large Language Models (LLMs) have shown significant promise in various applications, including zero-shot and few-shot learning. However, their performance can be hampered by inhere…
Learning Disentangled Speech Representations with Contrastive Learning and Time-Invariant Retrieval
Yimin Deng, Huaizhen Tang, Xulong Zhang +3
Voice conversion refers to transferring speaker identity with well-preserved content. Better disentanglement of speech representations leads to better voice conversion. Recent stud…
ED-TTS: Multi-Scale Emotion Modeling using Cross-Domain Emotion Diarization for Emotional Speech Synthesis
Haobin Tang, Xulong Zhang, Ning Cheng +2
Existing emotional speech synthesis methods often utilize an utterance-level style embedding extracted from reference audio, neglecting the inherent multi-scale property of speech…
EmoTalker: Emotionally Editable Talking Face Generation via Diffusion Model
Bingyuan Zhang, Xulong Zhang, Ning Cheng +3
In recent years, the field of talking faces generation has attracted considerable attention, with certain methods adept at generating virtual faces that convincingly imitate human…
INCPrompt: Task-Aware incremental Prompting for Rehearsal-Free Class-incremental Learning
Zhiyuan Wang, Xiaoyang Qu, Jing Xiao +2
This paper introduces INCPrompt, an innovative continual learning solution that effectively addresses catastrophic forgetting. INCPrompt's key innovation lies in its use of adaptiv…