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Woosung Choi

7 accepted papers

2026

BREAK-THE-BEAT! CONTROLLABLE MIDI-TO-DRUM AUDIO SYNTHESIS

ICASSP 2026poster

Current methods for creating drum loop audio in digital music production, such as using one-shot samples or resampling, often demand non-trivial efforts of creators. While recent generative models achieve high fidelity and adhere to text, they lack the specific control needed for such a task. Existi…

Cited by 0SourcePDFScholar
2026

Concept-TRAK: Understanding how diffusion models learn concepts through concept attribution

ICLR 2026poster

While diffusion models excel at image generation, their growing adoption raises critical concerns about copyright issues and model transparency. Existing attribution methods identify training examples influencing an entire image, but fall short in isolating contributions to specific elements, such a…

Cited by 0SourcecodeScholar
2026

LLM2Fx-Tools: Tool Calling for Music Post-Production

ICLR 2026poster

This paper introduces LLM2Fx-Tools, a multimodal tool-calling framework that generates executable sequences of audio effects (Fx-chain) for music post-production. LLM2Fx-Tools uses a large language model (LLM) to understand audio inputs, select audio effects types, determine their order, and estimat…

Cited by 0SourcecodeScholar
2026

SteerMusic: Enhanced Musical Consistency for Zero-shot Text-Guided and Personalized Music Editing

AAAI 2026technical

Music editing is an important step in music production, which has broad applications, including game development and film production. Most existing zero-shot text-guided editing methods rely on pretrained diffusion models by involving forward-backward diffusion processes. However, these methods ofte

Cited by 0SourcePDFScholar
2026

TOWARDS BLIND DATA CLEANING: A CASE STUDY IN MUSIC SOURCE SEPARATION

ICASSP 2026poster

The performance of deep learning models for music source separation heavily depends on training data quality. However, datasets are often corrupted by difficult-to-detect artifacts such as audio bleeding and label noise. Since the type and extent of contamination are typically unknown, cleaning meth…

Cited by 0SourcePDFScholar
2025

Variable Bitrate Residual Vector Quantization for Audio Coding

ICASSP 2025accepted

Recent state-of-the-art neural audio compression models have progressively adopted residual vector quantization (RVQ). Despite this success, these models employ a fixed number of codebooks per frame, which can be suboptimal in terms of rate-distortion tradeoff, particularly in scenarios with simple…

Cited by 12SourceScholar
2024

Timbre-Trap: A Low-Resource Framework for Instrument-Agnostic Music Transcription

ICASSP 2024accepted

In recent years, research on music transcription has focused mainly on architecture design and instrument-specific data acquisition. With the lack of availability of diverse datasets, progress is often limited to solo-instrument tasks such as piano transcription. Several works have explored multi-in…

Cited by 0SourceScholar