activity
20232026
most citedFine-grained Disentangled Representation Learning for Multimodal Emotion Recognition

1 citations · 2 across the 7 of their papers we have counts for

collaborators
Showing cs.SDShow all

5 papers · 1 filter

cs.SD2026

EchoEdit: Stabilizing Inversion-Free Audio Editing via Optimal Transport Geometry

Zhongyuan Fu, Yuhang Jia, Hui Wang +6

Text-guided audio editing with pretrained generative models is commonly implemented through inversion or noising. This topology induces a structural trade-off, as stronger edits re…

cs.SD2024

AudioEditor: A Training-Free Diffusion-Based Audio Editing Framework

Yuhang Jia, Yang Chen, Jinghua Zhao +4

Diffusion-based text-to-audio (TTA) generation has made substantial progress, leveraging latent diffusion model (LDM) to produce high-quality, diverse and instruction-relevant audi…

cs.SD2024

M2R-Whisper: Multi-stage and Multi-scale Retrieval Augmentation for Enhancing Whisper

Jiaming Zhou, Shiwan Zhao, Jiabei He +6

State-of-the-art models like OpenAI's Whisper exhibit strong performance in multilingual automatic speech recognition (ASR), but they still face challenges in accurately recognizin…

cs.SD2023★ 1 cited

Fine-grained Disentangled Representation Learning for Multimodal Emotion Recognition

Haoqin Sun, Shiwan Zhao, Xuechen Wang +3

Multimodal emotion recognition (MMER) is an active research field that aims to accurately recognize human emotions by fusing multiple perceptual modalities. However, inherent heter…

cs.SD2023

kNN-CTC: Enhancing ASR via Retrieval of CTC Pseudo Labels

Jiaming Zhou, Shiwan Zhao, Yaqi Liu +3

The success of retrieval-augmented language models in various natural language processing (NLP) tasks has been constrained in automatic speech recognition (ASR) applications due to…