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20162024
most citedKU-ISPL Language Recognition System for NIST 2015 i-Vector Machine Learning Challenge

2 citations · 3 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL2024

Speech vs. Transcript: Does It Matter for Human Annotators in Speech Summarization?

Roshan Sharma, Suwon Shon, Mark Lindsey +3

Reference summaries for abstractive speech summarization require human annotation, which can be performed by listening to an audio recording or by reading textual transcripts of th…

cs.CL2024

On the Evaluation of Speech Foundation Models for Spoken Language Understanding

Siddhant Arora, Ankita Pasad, Chung-Ming Chien +9

The Spoken Language Understanding Evaluation (SLUE) suite of benchmark tasks was recently introduced to address the need for open resources and benchmarking of complex spoken langu…

cs.CL2024

DiscreteSLU: A Large Language Model with Self-Supervised Discrete Speech Units for Spoken Language Understanding

Suwon Shon, Kwangyoun Kim, Yi-Te Hsu +3

The integration of pre-trained text-based large language models (LLM) with speech input has enabled instruction-following capabilities for diverse speech tasks. This integration re…

cs.CL20241 cited

Improving ASR Contextual Biasing with Guided Attention

Jiyang Tang, Kwangyoun Kim, Suwon Shon +3

In this paper, we propose a Guided Attention (GA) auxiliary training loss, which improves the effectiveness and robustness of automatic speech recognition (ASR) contextual biasing…

cs.CL2023

A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks

Yifan Peng, Kwangyoun Kim, Felix Wu +7

Conformer, a convolution-augmented Transformer variant, has become the de facto encoder architecture for speech processing due to its superior performance in various tasks, includi…