Automated Audio Captioning with Epochal Difficult Captions for Curriculum Learning
원문 초록
In this paper, we propose an algorithm, Epochal Difficult Captions, to supplement the training of any model for the Automated Audio Captioning task. Epochal Difficult Captions is an elegant evolution to the keyword estimation task that previous work have used to train the encoder of the AAC model. Epochal Difficult Captions modifies the target captions based on a curriculum and a difficulty level determined as a function of current epoch. Epochal Difficult Captions can be used with any model architecture and is a lightweight function that does not increase training time. We test our results on three systems and show that using Epochal Difficult Captions consistently improves performance
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video-SALMONN 2: Captioning-Enhanced Audio-Visual Large Language Models
FusionAudio-1.2M: Towards Fine-grained Audio Captioning with Multimodal Contextual Fusion
Solla: Towards a Speech-Oriented LLM That Hears Acoustic Context
Mellow: a small audio language model for reasoning
ADIFF: Explaining audio difference using natural language
LLMs can see and hear without any training
토론
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