Simulated Binaural Speech Source Directivity Dataset This dataset contains 96,000 simulated binaural speech recordings generated for the study of speech source directivity classification . The dataset is designed to support the binary classification of whether a speech source is oriented toward or away from a listener. The recordings were generated under controlled acoustic and spatial conditions using an acoustic simulation workflow based on RAVEN (https://www.virtualacoustics.org/). Each audio file corresponds to a binaural rendering of a speech source with associated spatial, orientation, distance, reverberation, and intensity metadata. Authors Rhoddy Viveros Muñoz¹ and Sebastian Guajardo Herrera¹ ¹ Departamento de Electrónica e Informática, Universidad Técnica Federico Santa María, Concepción, Chile. Dataset Overview The dataset addresses the problem of speech source directivity classification. Unlike conventional sound source localization tasks, which focus mainly on estimating where a sound comes from, this dataset focuses on whether the speech source is facing or not facing the listener. This distinction is relevant for spatial audio analysis, auditory scene understanding, a…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy