Listener metadata

The same listener metadata is used for both tasks. These characterise the hearing abilities of the listeners, so the audio signals you generate can be individualised. The same types of data are available for training, validation and evaluation. More on hearing loss and how it is measured.

Training For training, we will use the same 83 audiograms from the Clarity project.
Validation We constructed a new set of listeners to separate the training from the validation listeners. The validation audiograms are a filtered, pseudo-random, selection from the von Gablenz and Holube (2019) dataset. Additionally, we include a "normal hearing" audiogram (L5999). Results using this audiogram can be used to evaluate the performance of systems when no amplification prescription is applied.

Data file formats and naming conventions

Audiogram data is stored in a JSON file per dataset with the following format.

{
    "L0001": {
        "name"               : "L0001",
        "audiogram_cfs"      : [250, 500, 1000, 2000, 3000, 4000, 6000, 8000],
        "audiogram_levels_l" : [10, 10, 20, 30, 40, 55, 55, 60],
        "audiogram_levels_r" : [ ... ],
    },
    ...
}

Compressor params are provided for the final signal amplification. This file contains individualised compression ratios and gains per band.

 "L0001": {
        "frequencies": [250, 500, 1000, 2000, 4000, 8000],
        "cr_l": [2.1, 1.5, 1.3, 1.5, 2.4, 3.7],
        "gain_l": [9.6, 11.9, 12.9, 16.4, 19.0, 28.0],
        "cr_r": [...]
        "gain_r": [...]
    },

Data file formats and naming conventions​

Data file formats and naming conventions