Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models

ISMIR 2019 Late-Breaking/Demo 2019 Romain HennequinAnis KhlifFelix VoituretManuel Moussallam

We present and release a new tool for music source separation with pre-trained models called Spleeter.Spleeter was designed with ease of use, separation performance and speed in mind. Spleeter is based onTensorflow [1] and makes it possible to:•separate audio files into2,4or5stems with a single command line using pre-trained models.•train source separation models or fine-tune pre-trained ones with Tensorflow (provided you have a dataset of isolated sources).The performance of the pre-trained models are very close to the published state of the art and is, to the authors knowledge, the best performing4stems separation model on the common musdb18 benchmark [6]to be publicly released... (read more)

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#2 best model for Music Source Separation on MUSDB18 (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
LEADERBOARD
Music Source Separation MUSDB18 Spleeter (MWF) SDR (vocals) 6.86 # 2
SDR (drums) 6.71 # 3
SDR (other) 4.02 # 6
SDR (bass) 5.51 # 6