BWSNet: Automatic Perceptual Assessment of Audio Signals

Autor:	Veillon, Clément Le Moine, Rosi, Victor, Sarah, Pablo Arias, Salais, Léane, Obin, Nicolas
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Audio and Speech Processing Computer Science - Sound
Druh dokumentu:	Working Paper
Popis:	This paper introduces BWSNet, a model that can be trained from raw human judgements obtained through a Best-Worst scaling (BWS) experiment. It maps sound samples into an embedded space that represents the perception of a studied attribute. To this end, we propose a set of cost functions and constraints, interpreting trial-wise ordinal relations as distance comparisons in a metric learning task. We tested our proposal on data from two BWS studies investigating the perception of speech social attitudes and timbral qualities. For both datasets, our results show that the structure of the latent space is faithful to human judgements.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2309.02592 Zobrazit plný text záznamu View this record from Arxiv