Hearing Aid and device processing

The Free Music Archive (FMA) is a large-scale dataset for evaluating several tasks in Music Information Retrieval. It consists of 343 days of audio from 106,574 tracks from 16,341 artists and 14,854 albums, arranged in a hierarchical taxonomy of 161 genres. It provides full-length and high-quality audio, pre-computed features, together with track- and user-level metadata, tags, and free-form text such as biographies. There are four subsets defined by the authors: * Full: the complete dataset, * Large: the full dataset with audio limited to 30 seconds clips extracted from the middle of the tracks (or entire track if shorter than 30 seconds), * Medium: a selection of 25,000 30s clips having a single root genre, * Small: a balanced subset containing 8,000 30s clips with 1,000 clips per one of 8 root genres. The official split into training, validation and test sets (80/10/10) uses stratified sampling to preserve the percentage of tracks per genre. Songs of the same artists are part of one set only. Source: FMA: A Dataset For Music Analysis Audio Source: https://github.com/mdeff/fma

The MUSDB18 is a dataset of 150 full lengths music tracks (~10h duration) of different genres along with their isolated drums, bass, vocals and others stems. The dataset is split into training and test sets with 100 and 50 songs, respectively. All signals are stereophonic and encoded at 44.1kHz. Source: https://sigsep.github.io/datasets/musdb.html#musdb18-compressed-stems Image Source: https://sigsep.github.io/datasets/musdb.html#musdb18-compressed-stems