arxiv:2409.01201

EnCLAP++: Analyzing the EnCLAP Framework for Optimizing Automated Audio Captioning Performance

Published on Sep 2

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Authors:

Jaeyoon Jung ,

Sang Hoon Woo ,

Abstract

In this work, we aim to analyze and optimize the EnCLAP framework, a state-of-the-art model in automated audio captioning. We investigate the impact of modifying the acoustic encoder components, explore pretraining with different dataset scales, and study the effectiveness of a reranking scheme. Through extensive experimentation and quantitative analysis of generated captions, we develop EnCLAP++, an enhanced version that significantly surpasses the original.

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