63 citations · 74 across the 20 of their papers we have counts for
4 papers · 1 filter
Automatic Music Mixing using a Generative Model of Effect Embeddings
Eloi Moliner, Marco A. Martínez-Ramírez, Junghyun Koo +5
Music mixing involves combining individual tracks into a cohesive mixture, a task characterized by subjectivity where multiple valid solutions exist for the same input. Existing au…
Timbre-Trap: A Low-Resource Framework for Instrument-Agnostic Music Transcription
Frank Cwitkowitz, Kin Wai Cheuk, Woosung Choi +4
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 datase…
Danna-Sep: Unite to separate them all
Chin-Yun Yu, Kin-Wai Cheuk
Deep learning-based music source separation has gained a lot of interest in the last decades. Most of the existing methods operate with either spectrograms or waveforms. Spectrogra…
Music Demixing Challenge 2021
Yuki Mitsufuji, Giorgio Fabbro, Stefan Uhlich +6
Music source separation has been intensively studied in the last decade and tremendous progress with the advent of deep learning could be observed. Evaluation campaigns such as MIR…