Brian McFee

resampy. Efficient sample rate conversion in python

muda. A library for augmenting annotated audio data

pyrubberband. python wrapper for rubberband

ismir2020-metric-learning. ISMIR 2020 Tutorial for Metric Learning in MIR

crema. convolutional and recurrent estimators for music analysis

pumpp. practically universal music pre-processor

ismir2017_chords. ISMIR 2017: structured training for large vocab chord recognition

mlr. Metric Learning to Rank

dstbook. Digital Signals Theory book and source materials

ismir2018-oss-tutorial. ISMIR2018 Tutorial on Open Source and Reproducibility in MIR Research

spatialtree. Python module for spatial trees

stanford-mir. Instructional material for the Music Information Retrieval Workshop at CCRMA, Stanford University, 2014-18.

lsd_viz. Laplacian structural decomposition music visualization

msd_challenge. Million Song Dataset Challenge

laplacian_segmentation. graph laplacian song segmentation

olda. Music segmentation by ordinal linear discriminant analysis

musichacks. Projects for music hack day

ml_scraps. Scraps of random machine learning code

ccrma2018_notebooks. Extra notebooks for CCRMA MIR workshop, 2018 edition

RasterFairy. The purpose of Raster Fairy is to transform any kind of 2D point cloud into a regular raster whilst trying to preserve the neighborhood relations that were present in the original cloud. A typical use case is if you have a similarity clustering of images and want to show the images in a regular table structure.

autochiptune. Automatic chiptune remixer in python

crema-features. Convolutional REpresenations for Music Analysis

ipyaudio. Bridge IPython and PortAudio for interactive realtime audio

playlist_recommender. Personalized generative playlist models

discogs-import. Import the discogs monthly XML dumps into a database (fork of http://code.google.com/p/discogs-sql-importer/)

CDL. Convolutional dictionary learning and (sparse) coding

hypergraph_playlist. Source code for hypergraph random walk playlist models

librosa. Python library for audio and music analysis

segment_hierarchy_labels. Investigating hierarchical music segmentations

dstbook-site. UNDER CONSTRUCTION

nypl-openaudio-discovery-topics. Topic modeling of audio transcripts

nonstandards. A model for generating jazz standards

audio-ml-lab. A Dockerized Jupyter notebook environment with pre-installed audio machine learning tools.

librosa_parameters. parameter optimization code for librosa

fish-conda. conda commands for fish shell

augment_music. experiments in musical data augmentation

keplerphone. Musify your exoplanets

rhythm-analysis. LabROSA rhythm and onset analysis

beat_onset. evaluation of onset functions for beat tracking

SpokenWebTutorials. A workspace for some audio processing tutorials

spokenweb. Workshop for audio analysis

pysoundfile-feedstock. A conda-smithy repository for pysoundfile.