11 citations · 26 across the 14 of their papers we have counts for
11 papers · 1 filter
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…
Motive-level Analysis of Form-functions Association in Korean Folk song
Danbinaerin Han, Dasaem Jeong, Juhan Nam
Computational analysis of folk song audio is challenging due to structural irregularities and the need for manual annotation. We propose a method for automatic motive segmentation…
Enriching Music Descriptions with a Finetuned-LLM and Metadata for Text-to-Music Retrieval
SeungHeon Doh, Minhee Lee, Dasaem Jeong +1
Text-to-Music Retrieval, finding music based on a given natural language query, plays a pivotal role in content discovery within extensive music databases. To address this challeng…
Musical Word Embedding for Music Tagging and Retrieval
SeungHeon Doh, Jongpil Lee, Dasaem Jeong +1
Word embedding has become an essential means for text-based information retrieval. Typically, word embeddings are learned from large quantities of general and unstructured text dat…
Can Audio Reveal Music Performance Difficulty? Insights from the Piano Syllabus Dataset
Pedro Ramoneda, Minhee Lee, Dasaem Jeong +2
Automatically estimating the performance difficulty of a music piece represents a key process in music education to create tailored curricula according to the individual needs of t…
Predicting performance difficulty from piano sheet music images
Pedro Ramoneda, Jose J. Valero-Mas, Dasaem Jeong +1
Estimating the performance difficulty of a musical score is crucial in music education for adequately designing the learning curriculum of the students. Although the Music Informat…
Finding Tori: Self-supervised Learning for Analyzing Korean Folk Song
Danbinaerin Han, Rafael Caro Repetto, Dasaem Jeong
In this paper, we introduce a computational analysis of the field recording dataset of approximately 700 hours of Korean folk songs, which were recorded around 1980-90s. Because mo…
Combining piano performance dimensions for score difficulty classification
Pedro Ramoneda, Dasaem Jeong, Vsevolod Eremenko +3
Predicting the difficulty of playing a musical score is essential for structuring and exploring score collections. Despite its importance for music education, the automatic difficu…
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…
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…
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…