most citedFlanEC: Exploring Flan-T5 for Post-ASR Error Correction

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2025

An Investigation on Combining Geometry and Consistency Constraints into Phase Estimation for Speech Enhancement

Chun-Wei Ho, Pin-Jui Ku, Hao Yen +3

We propose a novel iterative phase estimation framework, termed multi-source Griffin-Lim algorithm (MSGLA), for speech enhancement (SE) under additive noise conditions. The core id…

cs.CL2025★ 3 cited

FlanEC: Exploring Flan-T5 for Post-ASR Error Correction

Moreno La Quatra, Valerio Mario Salerno, Yu Tsao +1

In this paper, we present an encoder-decoder model leveraging Flan-T5 for post-Automatic Speech Recognition (ASR) Generative Speech Error Correction (GenSEC), and we refer to it as…

cs.LG2024

RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier

Pin-Yen Huang, Szu-Wei Fu, Yu Tsao

State-of-the-art (SOTA) semi-supervised learning techniques, such as FixMatch and it's variants, have demonstrated impressive performance in classification tasks. However, these me…

cs.SD2024

Exploiting Consistency-Preserving Loss and Perceptual Contrast Stretching to Boost SSL-based Speech Enhancement

Muhammad Salman Khan, Moreno La Quatra, Kuo-Hsuan Hung +3

Self-supervised representation learning (SSL) has attained SOTA results on several downstream speech tasks, but SSL-based speech enhancement (SE) solutions still lag behind. To add…

cs.SD2024★ 1 cited

An Investigation of Incorporating Mamba for Speech Enhancement

Rong Chao, Wen-Huang Cheng, Moreno La Quatra +4

This work aims to investigate the use of a recently proposed, attention-free, scalable state-space model (SSM), Mamba, for the speech enhancement (SE) task. In particular, we emplo…