2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
MIDI-REPA: Improving Text-to-Music Generation with Symbolic Representation Alignment
Song-Ze Yu, Fang-Duo Tsai, Yi-Hsuan Yang
State-of-the-art text-to-music models increasingly rely on scaling model capacity, data, and compute, while still learning musical structure directly from dense audio. Yet melody,…
Unifying Score and Performance for Fine-Grained Music Understanding in Audio-Language Models
Milan Liessens Dujardin, Song-Ze Yu, Kevin Miao
Large audio language models (LALMs) have shown promising progress in broad music-understanding tasks such as tagging, retrieval, and captioning. Music understanding that requires f…
InstructFX2FX: A Multi-Turn Text-to-Effect System for Sequential Audio Effect Refinement
Song-Ze Yu, Milan Liessens Dujardin, Yuxuan Cai +4
We present InstructFX2FX, a system for sequential audio effect refinement through multi-turn natural-language instructions. Existing text-to-effect systems are largely single-shot,…
PitchBench: Measuring Pitch Hearing in Audio-Language Models
Milan Liessens Dujardin, Song-Ze Yu, Craver Corbyn Thomas-Smith +2
Audio-language models (ALMs) are increasingly used in real-world applications that require understanding music, from music tutoring and transcription to captioning, recommendation…
From Sound to Setting: AI-Based Equalizer Parameter Prediction for Piano Tone Replication
Song-Ze Yu
This project presents an AI-based system for tone replication in music production, focusing on predicting EQ parameter settings directly from audio features. Unlike traditional aud…