Implementation of "Audio Retrieval with Natural Language Queries: A Benchmark Study".
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Updated
Jul 22, 2022 - Python
Implementation of "Audio Retrieval with Natural Language Queries: A Benchmark Study".
Web-crawl for "Audio Retrieval with WavText5K and CLAP Training"
Implementation of "Audio Retrieval with Natural Language Queries", INTERSPEECH 2021, PyTorch
This is the official codebase used for obtaining the results in the ICASSP 2024 paper: A SOUND APPROACH: Using Large Language Models to generate audio descriptions for egocentric text-audio retrieval
This repository provides the code for "Improving Query-by-Vocal Imitation with Contrastive Learning and Audio Pretraining", presented at DCASE 2024. The paper addresses the challenge of audio retrieval using vocal imitations as queries, proposing a dual encoder architecture that leverages pretrained CNNs and an adapted NT-Xent loss for fine-tuning.
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