SAMoSA: Sensing Activities with Motion and Subsampled Audio

Research code for SAMoSA: Sensing Activities with Motion and Subsampled Audio (Ubicomp/IMWUT 2022).

Reference

Vimal Mollyn, Karan Ahuja, Dhruv Verma, Chris Harrison, and Mayank Goel. 2022. SAMoSA: Sensing Activities with Motion and Subsampled Audio. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 3, Article 132 (September 2022), 19 pages.

Download Paper Here.

BibTeX Reference:

@article{samosa,
    author = {Mollyn, Vimal and Ahuja, Karan and Verma, Dhruv and Harrison, Chris and Goel, Mayank},
    title = {SAMoSA: Sensing Activities with Motion and Subsampled Audio},
    year = {2022},
    issue_date = {September 2022},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    volume = {6},
    number = {3},
    url = {https://doi.org/10.1145/3550284},
    doi = {10.1145/3550284},
    journal = {Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.},
    month = {sep},
    articleno = {132},
    numpages = {19},
    keywords = {Sensors, Location-Aware/Contextual Computing, Artifact or System}
}

1. Clone this repository

git clone https://github.com/cmusmashlab/SAMoSA.git

2. Create a virtual environment

We recommend using conda. Tested on Ubuntu 20.04, with python 3.8.

conda create -n "samosa" python=3.8.3
conda activate samosa
conda install -c conda-forge cudatoolkit=10.2 cudnn=7.6

python -m pip install -r requirements.txt

3. Download the SAMoSA dataset

Download the Data folder from here (2.88 GB) and place in SAMoSA/Data.

Data/
└── TrainingDataset

Each file in the TrainingDataset folder contains synchronized Audio and IMU data.
The file name contains all the information regarding the contents of the file.

For example:
49---Kitchen---Chopping---1.pkl

Participant ID: 49, Context: Kitchen, Activity: Chopping, TrialNo: 1

Each pickle file has an Audio and IMU key. Speech (Other) activity files contain an additional 1kHz_Audio key.

• Audio contains a 1D array of audio data, sampled at 16kHz. We release data for all activities excluding speech at 16kHz. Speech is released at 1kHz (.
• IMU is a 2D array of (N_Samples, 9 axes) sampled at ~50Hz.
• 1kHz_Audio is a 1D array of audio data, subsampled to 1kHz. Whenever this key is present, the Audio key contains an array of zeros with the same shape as the original 16kHz array.
• Refer to this notebook and the paper for more information.

4. Download the SAMoSA models

Download the Models folder from here (2.46 GB) and place in SAMoSA/Models. It should have the following tree structure. Note, to replicate results from the paper, you must download all 20 models from here (49.5 GB).

Models/
├── Motion
│   └── 17.h5
├── MotionSound
│   ├── 1000
│   │   └── 17
│   │       ├── 17.h5
│   │       ├── lb.pkl
│   │       └── norm_params.pkl
│   └── 16000
│       └── 17
│           ├── 17.h5
│           ├── lb.pkl
│           └── norm_params.pkl
└── Sound
    ├── 1000
    │   └── 17.h5
    └── 16000
        └── 17.h5

5. Generate Predictions

Run scripts in Code/1. Generate Predictions. This will generate predictions in a new folder located at SAMoSA/Preds, with the following structure.

Preds/
├── Motion
├── MotionSound
│   ├── 1000
│   └── 16000
└── Sound
    ├── 1000
    └── 16000

6. Run Evaluation notebooks

Note, results from the paper are averaged across all 20 Leave-One-Participant-Out (LOPO) cross validation folds.

• Evaluation notebook for context wise metrics
• Evaluation notebook for frame wise metrics

Annotator Web App

The annotator app that we used during data collection can be found here.

Android WearOS App for data collection and streaming

Download the Sensor Streamer app here!

Coming Soon!

• Real-Time demos and visualizations

Disclaimer

THE PROGRAM IS DISTRIBUTED IN THE HOPE THAT IT WILL BE USEFUL, BUT WITHOUT ANY WARRANTY. IT IS PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.

IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW THE AUTHOR WILL BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF THE AUTHOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

License

The SAMoSA dataset and code can only be used for research i.e., non-commercial purposes. For a commercial license, please contact Vimal Mollyn, Karan Ahuja and Mayank Goel.

Contact

Feel free to contact Vimal Mollyn for any help, questions or general feedback!