12 citations · 17 across the 8 of their papers we have counts for
8 papers · 1 filter
Few-Shot Musical Source Separation
Yu Wang, Daniel Stoller, Rachel M. Bittner +1
Deep learning-based approaches to musical source separation are often limited to the instrument classes that the models are trained on and do not generalize to separate unseen inst…
A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation
Rachel M. Bittner, Juan José Bosch, David Rubinstein +2
Automatic Music Transcription (AMT) has been recognized as a key enabling technology with a wide range of applications. Given the task's complexity, best results have typically bee…
vocadito: A dataset of solo vocals with , note, and lyric annotations
Rachel M. Bittner, Katherine Pasalo, Juan José Bosch +2
To compliment the existing set of datasets, we present a small dataset entitled vocadito, consisting of 40 short excerpts of monophonic singing, sung in 7 different languages by si…
Soundata: A Python library for reproducible use of audio datasets
Magdalena Fuentes, Justin Salamon, Pablo Zinemanas +6
Soundata is a Python library for loading and working with audio datasets in a standardized way, removing the need for writing custom loaders in every project, and improving reprodu…
Audio-based Musical Version Identification: Elements and Challenges
Furkan Yesiler, Guillaume Doras, Rachel M. Bittner +2
In this article, we aim to provide a review of the key ideas and approaches proposed in 20 years of scientific literature around musical version identification (VI) research and co…
Learned complex masks for multi-instrument source separation
Andreas Jansson, Rachel M. Bittner, Nicola Montecchio +1
Music source separation in the time-frequency domain is commonly achieved by applying a soft or binary mask to the magnitude component of (complex) spectrograms. The phase componen…
Neural Music Synthesis for Flexible Timbre Control
Jong Wook Kim, Rachel Bittner, Aparna Kumar +1
The recent success of raw audio waveform synthesis models like WaveNet motivates a new approach for music synthesis, in which the entire process --- creating audio samples from a s…
Multitask Learning for Fundamental Frequency Estimation in Music
Rachel M. Bittner, Brian McFee, Juan P. Bello
Fundamental frequency (f0) estimation from polyphonic music includes the tasks of multiple-f0, melody, vocal, and bass line estimation. Historically these problems have been approa…