4 citations · 6 across the 22 of their papers we have counts for
22 papers
On the de-duplication of the Lakh MIDI dataset
Eunjin Choi, Hyerin Kim, Jiwoo Ryu +2
A large-scale dataset is essential for training a well-generalized deep-learning model. Most such datasets are collected via scraping from various internet sources, inevitably intr…
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…
Predicting User Intents and Musical Attributes from Music Discovery Conversations
Daeyong Kwon, SeungHeon Doh, Juhan Nam
Intent classification is a text understanding task that identifies user needs from input text queries. While intent classification has been extensively studied in various domains,…
Music Discovery Dialogue Generation Using Human Intent Analysis and Large Language Models
SeungHeon Doh, Keunwoo Choi, Daeyong Kwon +2
A conversational music retrieval system can help users discover music that matches their preferences through dialogue. To achieve this, a conversational music retrieval system shou…