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Abstract

A method for generating a sound output is based on an interaction with a data set. The data set comprises a plurality of data points. Each data point stores one or more data features. An interaction is obtained with at least a part of the data points and a sound model is used to generate a sound output based on the interaction. The sound model maps at least one of the one or more data features to one or more acoustic properties of the sound output as a function of the interaction. The data features can be one of a spatial feature, a time feature, a physical property, and a data label. The acoustic properties can be one of pitch, pulsing frequency, duty cycle, loudness, and tone colour. The method can be used to validate labels assigned to ground truth input data and to train a machine learning algorithm.

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First Claim