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Code Repository for the paper Few-Shot Keyword Spotting with Prototypical Networks.

Few-Shot Keyword Spotting Pipeline

Installation

  1. Clone the repository:

    git clone https://github.com/ArchitParnami/Few-Shot-KWS

  2. Create a conda environment:

    conda create -n FS-KWS

  3. If pip not installed, install pip by:

    conda install pip

  4. Install the required packages:

    pip install -r requirements.text

  5. Install the protonets package:

    cd Few-Shot-KWS
python setup.py develop

Download & Prepare Few-Shot Keyword Spotting Dataset

cd Few-Shot-KWS/data/
python download_prepare_data.py

Train

To train a simple 2-way 1-shot experiment.

cd Few-Shot-KWS/scripts/train/few-shot/fewshotspeech
./train.sh 2 1 0 mymodel

Specify arguments to train.sh in the following manner

train.sh num_ways num_shots exp_type exp_id

  • num_ways
    • Number of classes
    • Eg. 2 or 4
  • num_shots
    • Number of samples per class.
    • Eg. 1,5
  • exp_type
    • Number indicating the type of experimental setup
      • 0 = Simple N-Way K-Shot Setup. No background, silence or unknown keywords.
      • 1 = Include Background
      • 2 = Include Silence
      • 3 = Include Unknown
      • 4 = Background + Silence
      • 5 = Background + Unkown
      • 6 = Unknown + Silence
      • 7 = Background + Silence + Unknown
  • exp_id
    • identifier = directory name
    • results are saved in Few-Shot-KWS/scripts/train/few-shot/fewshotspeech/results/[exp_id]

Evaluate

cd Few-Shot-KWS/scripts/predict/few-shot
python eval_results.py ../../train/few_shot/fewshotspeech/results/

The evaluation can be found in:

cat Few-Shot-KWS/scripts/train/few-shot/fewshotspeech/results/[exp-id]/[timestamp]/eval.txt

Results

Comaring test accuracy of different embedding networks on 4-way FS-KWS as we increase the number of support examples. The results are presented for four different cases discussed in the paper.

References

The code in this repository has been adapted from:

  1. https://github.com/jakesnell/prototypical-networks
  2. https://github.com/hyperconnect/TC-ResNet
  3. https://github.com/tensorflow/docs/blob/master/site/en/r1/tutorials/sequences/audio_recognition.md

Citation

@misc{parnami2020fewshot,
    title={Few-Shot Keyword Spotting With Prototypical Networks},
    author={Archit Parnami and Minwoo Lee},
    year={2020},
    eprint={2007.14463},
    archivePrefix={arXiv},
    primaryClass={eess.AS}
}