Audio Captioning Model

Audio captioning models automatically generate textual descriptions of audio content, aiming to bridge the gap between auditory and linguistic information. Current research focuses on improving model accuracy and reliability through techniques like incorporating large language models (LLMs) for enhanced semantic understanding, developing more robust confidence measures for generated captions, and addressing issues such as object hallucination and data scarcity via synthetic data generation and transfer learning from related modalities. These advancements hold significant potential for applications ranging from accessibility tools for the hearing impaired to improved content indexing and retrieval systems, and are driving the development of more sophisticated multimodal understanding in artificial intelligence.