From the 1 of 10 linked papers with an AI index.
10 papers
The Sound of Absence: Audio-Language Embedding Models Struggle with Negation
Chun-Yi Kuan, Hung-yi Lee
The paper reveals that audio-language embedding models like CLAP cannot distinguish between present and absent sound events, showing they treat negated captions similarly to affirm…
Steering Where to Listen: Instruction-Based Activation Steering Redirects Temporal Attention in Large Audio-Language Models
Tsung-En Lin, Hung-Yi Lee
Large Audio-Language Models (LALMs) excel at audio understanding but expose little about where in an audio signal they attend. We introduce instruction-based vector steering, which…
AQUA-Bench: Beyond Finding Answers to Knowing When There Are None in Audio Question Answering
Chun-Yi Kuan, Hung-yi Lee
Recent advances in audio-aware large language models have shown strong performance on audio question answering. However, existing benchmarks mainly cover answerable questions and o…
Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization
Tzu-Quan Lin, Wei-Ping Huang, Hao Tang +1
Fine-tuning speech representation models can enhance performance on specific tasks but often compromises their cross-task generalization ability. This degradation is often caused b…
AQAScore: Evaluating Semantic Alignment in Text-to-Audio Generation via Audio Question Answering
Chun-Yi Kuan, Kai-Wei Chang, Hung-yi Lee
Although text-to-audio generation has made remarkable progress in realism and diversity, the development of evaluation metrics has not kept pace. Widely-adopted approaches, typical…
From Alignment to Advancement: Bootstrapping Audio-Language Alignment with Synthetic Data
Chun-Yi Kuan, Hung-yi Lee
Audio-aware large language models (ALLMs) have recently made great strides in understanding and processing audio inputs. These models are typically adapted from text-based large la…