name: mycroft-precise
adopt-info: mycroft-precise
license: Apache-2.0
summary: A wake word listener from Mycroft AI
description: >
  A lightweight, simple-to-use, RNN wake word listener, including all the tools to train your own custom wake word.
  
  Mycroft Precise monitors an audio stream (usually a microphone) and when it recognizes a specific phrase it triggers an event. For example, by default users of the Mycroft Voice Assistant are using a Precise model trained to spot the phrase "Hey Mycroft". When Precise recognizes this phrase it puts the Mycroft Voice Assistant into command mode performing speech recognition on whatever is next said by the person using the device.
  
  Mycroft Precise is fully open source and can be trained to recognize any short-phrase or sound, from a name to a cough.
  
  The default "Hey Mycroft" model is included, to test it, try:
  `mycroft-precise.listen /snap/mycroft-precise/current/hey-mycroft/hey-mycroft.pb`
  

  **USAGE**
  
  
  Running the listener
  
    mycroft-precise - Alias for mycroft-precise.engine
    mycroft-precise.engine - Run a model on raw audio data from stdin
    mycroft-precise.listen - Run a model on microphone audio input
    mycroft-precise.listen-pocketsphinx - Run the PocketSphinx listener
  
  Data collection
  
    mycroft-precise.collect - Record audio samples for use with Precise
    mycroft-precise.add-noise - Create a duplicate dataset with added noise
  
  Training
  
    mycroft-precise.train - Train a new model on a dataset
    mycroft-precise.train-generated - Train a model on infinitely generated batches
    mycroft-precise.train-incremental - Train a model to inhibit activation by marking false activations and retraining
    mycroft-precise.train-optimize - Use black box optimization to tune model hyperparameters
    mycroft-precise.train-sampled - Train a model, sampling data points with the highest loss from a larger dataset
  
  Evaluation and analysis
  
    mycroft-precise.test - Test a model against a dataset
    mycroft-precise.test-pocketsphinx - Test PocketSphinx against a dataset
    mycroft-precise.eval - Evaluate a list of models on a dataset
    mycroft-precise.calc-threshold - Update the threshold values of a model for a dataset to make the sensitivity more accurate and linear
    mycroft-precise.graph - Show ROC curves for a series of models
    mycroft-precise.simulate - Simulate listening to long chunks of audio to find unbiased false positive metrics
  
  Model conversion
  
    mycroft-precise.convert - Convert wake-word model from Keras to TensorFlow
architectures:
  - build-on: [amd64]
base: core18
grade: stable
confinement: strict
build-packages: [python3-dev, python3-setuptools, libtool, libffi-dev, libssl-dev, autoconf, build-essential]
parts:
  alsa-mixin:
    build-packages:
    - libasound2-dev
    plugin: dump
    source: https://github.com/diddlesnaps/snapcraft-alsa.git
    source-subdir: snapcraft-assets
    stage-packages:
    - libslang2
    - libasound2
    - libasound2-plugins
    - libportaudio2
    - pulseaudio
    - alsa-utils
  mycroft-precise:
    after: [alsa-mixin]
    plugin: python
    python-version: python3
    source: .
    override-pull: |
        snapcraftctl pull
        # Set version to setup.py version if current commit is the latest
        # tag, otherwise append "-dev" to the version string.
        set +e
        if [[ git describe --exact-match --tags $(git log -n1 --pretty='%h') ]]
        then
            VERSION=$(/usr/bin/python3 setup.py --version)
        else
            VERSION="$(/usr/bin/python3 setup.py --version)-dev"
        fi
        set -e
        snapcraftctl set-version $VERSION
    build-packages:
        - python-setuptools
        - python3-pip
        - curl
        - libopenblas-dev
        - python3-scipy
        - cython
        - libhdf5-dev
        - python3-h5py
        - portaudio19-dev
        - swig
        - libatlas-base-dev
    stage-packages:
        - libopenblas-base
        - python3
        - python3-scipy
        - cython
        - libhdf5-100
        - libhdf5-cpp-100
        - python3-h5py
        - swig
        - libatlas3-base
  hey-mycroft:
    plugin: dump
    source: https://github.com/MycroftAI/precise-data/raw/models/hey-mycroft.tar.gz
    source-type: tar
    organize:
        '*': /hey-mycroft/

layout:
  /usr/lib/$SNAPCRAFT_ARCH_TRIPLET/alsa-lib:
    bind: $SNAP/usr/lib/$SNAPCRAFT_ARCH_TRIPLET/alsa-lib

apps:
  mycroft-precise:
    plugs: [home]
    command: bin/precise-engine
  add-noise:
    plugs: [home]
    command: bin/precise-add-noise
  calc-threshold:
    plugs: [home]
    command: bin/precise-calc-threshold
  collect:
    plugs: [home, audio-record, audio-playback]
    command-chain:
    - snap/command-chain/alsa-launch
    command: bin/precise-collect
  convert:
    plugs: [home]
    command: bin/precise-convert
  eval:
    plugs: [home]
    command: bin/precise-eval
  engine:
    plugs: [home]
    command: bin/precise-engine
  graph:
    plugs: [home]
    command: bin/precise-graph
  listen:
    command-chain:
    - snap/command-chain/alsa-launch
    plugs: [home, audio-record, audio-playback]
    command: bin/precise-listen
  listen-pocketsphinx:
    command-chain:
    - snap/command-chain/alsa-launch
    plugs: [home, audio-record, audio-playback]
    command: bin/precise-listen-pocketsphinx
  simulate:
    plugs: [home]
    command: bin/precise-simulate
  test:
    plugs: [home]
    command: bin/precise-test
  test-pocketsphinx:
    plugs: [home]
    command: bin/precise-test-pocketsphinx
  train:
    plugs: [home]
    command: bin/precise-train
  train-generated:
    plugs: [home]
    command: bin/precise-train-generated
  train-incremental:
    plugs: [home]
    command: bin/precise-train-incremental
  train-optimize:
    plugs: [home]
    command: bin/precise-train-optimize
  train-sampled:
    plugs: [home]
    command: bin/precise-train-sampled