11 citations · 24 across the 15 of their papers we have counts for
15 papers
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…
RenCon 2025: Revival of the Expressive Performance Rendering Competition
Huan Zhang, Taegyun Kwon, Anders Friberg +7
This paper presents a comprehensive documentation of RenCon 2025, the revival of the expressive performance rendering competition which took place at ISMIR 2025 in Daejeon, Korea.…
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,…
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…
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…
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…
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…
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…
Towards Efficient and Real-Time Piano Transcription Using Neural Autoregressive Models
Taegyun Kwon, Dasaem Jeong, Juhan Nam
In recent years, advancements in neural network designs and the availability of large-scale labeled datasets have led to significant improvements in the accuracy of piano transcrip…
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…
A study of audio mixing methods for piano transcription in violin-piano ensembles
Hyemi Kim, Jiyun Park, Taegyun Kwon +2
While piano music transcription models have shown high performance for solo piano recordings, their performance degrades when applied to ensemble recordings. This study aims to ana…
YM2413-MDB: A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations
Eunjin Choi, Yoonjin Chung, Seolhee Lee +3
Existing multi-instrumental datasets tend to be biased toward pop and classical music. In addition, they generally lack high-level annotations such as emotion tags. In this paper,…
TräumerAI: Dreaming Music with StyleGAN
Dasaem Jeong, Seungheon Doh, Taegyun Kwon
The goal of this paper to generate a visually appealing video that responds to music with a neural network so that each frame of the video reflects the musical characteristics of t…
Polyphonic Piano Transcription Using Autoregressive Multi-State Note Model
Taegyun Kwon, Dasaem Jeong, Juhan Nam
Recent advances in polyphonic piano transcription have been made primarily by a deliberate design of neural network architectures that detect different note states such as onset or…
Audio-to-score alignment of piano music using RNN-based automatic music transcription
Taegyun Kwon, Dasaem Jeong, Juhan Nam
We propose a framework for audio-to-score alignment on piano performance that employs automatic music transcription (AMT) using neural networks. Even though the AMT result may cont…