activity
20202024
most citedApplying Wav2vec2.0 to Speech Recognition in Various Low-resource Languages

58 citations · 150 across the 81 of their papers we have counts for

collaborators

81 papers

cs.CL2024

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…

cs.CL2024

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…

cs.IR2024

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…

cs.SD2024

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…

cs.SD2024

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…

cs.SD2024

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…