7 citations · 31 across the 24 of their papers we have counts for
37 papers
A correlation-permutation approach for speech-music encoders model merging
Fabian Ritter-Gutierrez, Yi-Cheng Lin, Jeremy H. M Wong +3
Creating a unified speech and music model requires expensive pre-training. Model merging can instead create an unified audio model with minimal computational expense. However, dire…
EASY: Emotion-aware Speaker Anonymization via Factorized Distillation
Jixun Yao, Hexin Liu, Eng Siong Chng +1
Emotion plays a significant role in speech interaction, conveyed through tone, pitch, and rhythm, enabling the expression of feelings and intentions beyond words to create a more p…
CS-Sum: A Benchmark for Code-Switching Dialogue Summarization and the Limits of Large Language Models
Sathya Krishnan Suresh, Tanmay Surana, Lim Zhi Hao +1
Code-switching (CS) poses a significant challenge for Large Language Models (LLMs), yet its comprehensibility remains underexplored in LLMs. We introduce CS-Sum, to evaluate the co…
Distilling a speech and music encoder with task arithmetic
Fabian Ritter-Gutierrez, Yi-Cheng Lin, Jui-Chiang Wei +4
Despite the progress in self-supervised learning (SSL) for speech and music, existing models treat these domains separately, limiting their capacity for unified audio understanding…
Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding
Dianwen Ng, Kun Zhou, Yi-Wen Chao +3
Achieving high-fidelity audio compression while preserving perceptual quality across diverse content remains a key challenge in Neural Audio Coding (NAC). We introduce MUFFIN, a fu…
Large Language Models Meet Contrastive Learning: Zero-Shot Emotion Recognition Across Languages
Heqing Zou, Fengmao Lv, Desheng Zheng +2
Multilingual speech emotion recognition aims to estimate a speaker's emotional state using a contactless method across different languages. However, variability in voice characteri…