Year: 2023
Type: conference-paper
Abstract: Automated Audio Captioning is a multimodal task that aims to convert audio content into natural language. The performance of audio captioning systems is evaluated on quantitative metrics applied to the text representations. Previously, researchers have applied metrics from machine translation and image captioning to evaluate a generated audio caption. Inspired by cognitive neuroscience research on auditory cognition, in this paper we present a novel metric approach that evaluates captions taking into account how human listeners derive semantic information from sounds: Audio Captioning Evaluation on Semantics of Sound (ACES).
Language: English
Topic: Music and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: Representation of natural sounds in the human brain: Transforming acoustics into the semantics of sound sources in the environment, Aud2Sem: Acoustic to Semantic Transformations in Human Auditory Cortex., Brain & LANGUAGE Research Institute, ILCB: Institute of Language Communication and the Brain, G746701943, G8851550243
OpenAlex ID: W4388118619