4 citations · 9 across the 12 of their papers we have counts for
12 papers
Attention2Probability: Attention-Driven Terminology Probability Estimation for Robust Speech-to-Text System
Yanfan Du, Jun Zhang, Bin Wang +6
Recent advances in speech large language models (SLMs) have improved speech recognition and translation in general domains, but accurately generating domain-specific terms or neolo…
NTU Speechlab LLM-Based Multilingual ASR System for Interspeech MLC-SLM Challenge 2025
Yizhou Peng, Bin Wang, Yi-Wen Chao +5
This report details the NTU Speechlab system developed for the Interspeech 2025 Multilingual Conversational Speech and Language Model (MLC-SLM) Challenge (Task I), where we achieve…
Beyond Classification: Towards Speech Emotion Reasoning with Multitask AudioLLMs
Wenyu Zhang, Yingxu He, Geyu Lin +9
Audio Large Language Models (AudioLLMs) have achieved strong results in semantic tasks like speech recognition and translation, but remain limited in modeling paralinguistic cues s…
IFEval-Audio: Benchmarking Instruction-Following Capability in Audio-based Large Language Models
Yiming Gao, Bin Wang, Chengwei Wei +2
Large language models (LLMs) have demonstrated strong instruction-following capabilities in text-based tasks. However, this ability often deteriorates in multimodal models after al…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
SSMLoRA: Enhancing Low-Rank Adaptation with State Space Model
Jiayang Yu, Yihang Zhang, Bin Wang +3
Fine-tuning is a key approach for adapting language models to specific downstream tasks, but updating all model parameters becomes impractical as model sizes increase. Parameter-Ef…
MERaLiON-TextLLM: Cross-Lingual Understanding of Large Language Models in Chinese, Indonesian, Malay, and Singlish
Xin Huang, Tarun Kumar Vangani, Minh Duc Pham +4
Multilingual large language models (MLLMs) have shown impressive capabilities across a variety of languages. However, efficacy can differ greatly between different language familie…
MERaLiON-AudioLLM: Bridging Audio and Language with Large Language Models
Yingxu He, Zhuohan Liu, Shuo Sun +5
We introduce MERaLiON-AudioLLM (Multimodal Empathetic Reasoning and Learning in One Network), the first speech-text model tailored for Singapore's multilingual and multicultural la…
Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models
Bin Wang, Xunlong Zou, Shuo Sun +6
Singlish, a Creole language rooted in English, is a key focus in linguistic research within multilingual and multicultural contexts. However, its spoken form remains underexplored,…
MoWE-Audio: Multitask AudioLLMs with Mixture of Weak Encoders
Wenyu Zhang, Shuo Sun, Bin Wang +6
The rapid advancements in large language models (LLMs) have significantly enhanced natural language processing capabilities, facilitating the development of AudioLLMs that process…
AudioBench: A Universal Benchmark for Audio Large Language Models
Bin Wang, Xunlong Zou, Geyu Lin +6
We introduce AudioBench, a universal benchmark designed to evaluate Audio Large Language Models (AudioLLMs). It encompasses 8 distinct tasks and 26 datasets, among which, 7 are new…
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar +58
Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing…