"This repository hosts a collection of audio datasets capturing diverse scenes, including UCSD PED 2, UMN_LAWN, and UMN_INTERIOR. These datasets serve various purposes, such as enabling audio analysis, supporting machine learning applications, and facilitating computer vision research. It's worth noting that video data for the mentioned scenes is already available, and we have painstakingly synchronized the acoustic data with these video files.
For the video data of UCSD PED 2, you can find it here.
To access the video data for the UMN dataset, please follow this link."
- Description: UCSD PED 2 is a dataset of audio recordings in outdoor environments, capturing various pedestrian activities and urban sounds.
- Dataset Location: Link to UCSD PED 2 dataset
- Citation: If you use this dataset, please cite the original source following their citation guidelines.
- Description: UMN_LAWN is a dataset of audio recordings in lawn or outdoor garden environments, containing natural ambient sounds.
- Dataset Location: Link to UMN_LAWN dataset
- Citation: If you use this dataset, please cite the original source following their citation guidelines.
- Description: UMN_INTERIOR is a dataset of audio recordings in indoor environments, capturing various room acoustics and indoor sounds.
- Dataset Location: Link to UMN_INTERIOR dataset
- Citation: If you use this dataset, please cite the original source following their citation guidelines.
- Description: UMN_PLAZA is a dataset of audio recordings in indoor environments, capturing various room acoustics and indoor sounds.
- Dataset Location: Link to UMN_PLAZA dataset
- Citation: If you use this dataset, please cite the original source following their citation guidelines.
Please follow the guidelines provided by the respective dataset creators for proper usage and citation. Make sure to respect their licensing and usage terms.
If you have additional audio datasets or improvements to existing datasets, contributions are welcome. Please follow these steps to contribute:
- Fork this repository.
- Create a new branch for your contribution.
- Add the dataset and necessary documentation.
- Create a pull request to merge your changes into this repository.
The datasets in this repository may have their own specific licenses. Refer to the individual dataset sources and their respective licenses for more information.
If you have any questions or issues related to this repository or its datasets, feel free to contact.
Happy researching and experimenting!