Audio Text Retrieval

Audio-text retrieval (ATR) focuses on developing systems that can efficiently retrieve audio clips based on textual descriptions, and vice versa. Current research emphasizes improving the accuracy and robustness of ATR by exploring advanced architectures like transformers and diffusion models, addressing challenges such as handling temporal information within audio, and mitigating the impact of noisy or misaligned training data through techniques like contrastive learning and adversarial training. ATR's advancements have significant implications for various applications, including multimedia search, content creation, and assistive technologies, by enabling more intuitive and effective interaction with audio-visual data.