This page includes CLAP features of three datasets used in Language-based audio moment retrieval [1]. Clotho-Moment UnAV100-subset TUT Sound Events 2017 Raw wav files are also publicly available here. [1] H. Munakata, T. Nishimura, S. Nakada, T. Komatsu, "Language-based Audio Moment Retrieval", In Proc. ICASSP, 2024. How to Use We can train/evaluate audio moment retrieval models using these features in Lighthouse.Please check the instructions of Lighthouse. Unzip the file with the following commandsClotho-moment: for file in clotho-moment_features.tar.part-*.gz; do gunzip "$file"; done clotho-moment_features.tar.part-* > clotho-moment_features.tar tar -xvf clotho-moment_features.tar UnAV100-subset, TUT Sound Events 2017: tar -xvf tut2017_features.tar.gz tar -xvf unav100-subset_features.tar.gz Set symbolic links in Lighthouseln -s features/{dataset_name} {lighthouse_dir}/features Train the modelpython training/train.py --model qd_detr --dataset clotho-moment --feature clap Evaluate the model model=qd_detr dataset=unav100-subset feature=clap model_path={lighthouse_dir}/results/qd_detr/clotho-moment/clap/best.ckpt eval_split_name=val eval_path=data/unav100-subset/unav100-subset_test_release.jsonl python training/evaluate.py \ --model $model \ --dataset $dataset \ --feature $feature \ --model_path $model_path \ --eval_split_name $eval_split_name \ --eval_path $eval_path