activity
20242026
collaborators

13 papers

cs.SD2026

PitchIn: Natural-Language Vocal Coaching from Unstructured Community Feedback

Hayeon Bang, Hounsu Kim, Joonyong Park +2

Effective vocal coaching connects performance issues with corrective advice, but recordings paired with expert diagnoses and advice are scarce. Online singing communities provide a…

cs.SD2026

VocalCoachBench: Benchmarking Audio-Language Models on Expert Feedback for Singing

Hayeon Bang, Hounsu Kim, Wonil Kim +1

Recent audio-language models are increasingly evaluated on recognizing, describing, and reasoning about audio, but expert-facing applications require a different capability: produc…

cs.SD2026

Multi-Task Multi-Frame Visual Piano Transcription

Yonghyun Kim, Hoyeol Sohn, Juhan Nam +1

Audio-based piano transcription performs well on onset, pitch, and velocity, but the sustain pedal lets sound persist long after key release, so audio systems predict pedal-extende…

cs.SD2026

SKY-Piano: A Multimodal Piano Performance Dataset

Joonhyung Bae, Dawon Park, Taegyun Kwon +10

Music information retrieval research on piano performance increasingly involves diverse modalities of data and annotations beyond audio and MIDI. We present SKY-Piano, a multimodal…

cs.SD2026

PiAnnotate: A Web Annotation Tool for Piano Fingering, with a Diagnostic Probe

Joonhyung Bae, Kirak Kim, Hyeyoon Cho +8

Piano fingering shapes how a passage can be played, yet it is difficult to label after a performance. An annotator must decide which finger produced each note while reconciling the…

cs.AI2026

Tipiano: Cascaded Piano Hand Motion Synthesis via Fingertip Priors

Joonhyung Bae, Kirak Kim, Hyeyoon Cho +9

Synthesizing realistic piano hand motions requires both precision and naturalness. Physics-based methods achieve precision but produce stiff motions; data-driven models learn natur…

cs.SD2026

D3PIA: A Discrete Denoising Diffusion Model for Piano Accompaniment Generation From Lead sheet

Eunjin Choi, Hounsu Kim, Hayeon Bang +2

Generating piano accompaniments in the symbolic music domain is a challenging task that requires producing a complete piece of piano music from given melody and chord constraints,…

cs.MM2025

Designing a Multimodal Viewer for Piano Performance Analysis -- a Pedagogy-First Approach

Joonhyung Bae, Hyeyoon Cho, Kirak Kim +11

Abstract instructions in piano education, such as "raise your wrist" and "relax your tension," lead to varying interpretations among learners, preventing instructors from effective…

cs.SD2025

Two Web Toolkits for Multimodal Piano Performance Dataset Acquisition and Fingering Annotation

Junhyung Park, Yonghyun Kim, Joonhyung Bae +4

Piano performance is a multimodal activity that intrinsically combines physical actions with the acoustic rendition. Despite growing research interest in analyzing the multimodal n…

cs.SD2025

PianoVAM: A Multimodal Piano Performance Dataset

Yonghyun Kim, Junhyung Park, Joonhyung Bae +4

The multimodal nature of music performance has driven increasing interest in data beyond the audio domain within the music information retrieval (MIR) community. This paper introdu…

cs.SD2025

Dialogue in Resonance: An Interactive Music Piece for Piano and Real-Time Automatic Transcription System

Hayeon Bang, Taegyun Kwon, Juhan Nam

This paper presents <Dialogue in Resonance>, an interactive music piece for a human pianist and a computer-controlled piano that integrates real-time automatic music transcription…

cs.SD2025

D3RM: A Discrete Denoising Diffusion Refinement Model for Piano Transcription

Hounsu Kim, Taegyun Kwon, Juhan Nam

Diffusion models have been widely used in the generative domain due to their convincing performance in modeling complex data distributions. Moreover, they have shown competitive re…

cs.SD2024

A Real-Time Lyrics Alignment System Using Chroma And Phonetic Features For Classical Vocal Performance

Jiyun Park, Sangeon Yong, Taegyun Kwon +1

The goal of real-time lyrics alignment is to take live singing audio as input and to pinpoint the exact position within given lyrics on the fly. The task can benefit real-world app…