WIP: Add support for multiple wakeword/vad models

[kahrendt]

What does this implement/fix?

This is still a work in progress! I'd appreciate people testing this out and letting me know about any issues. It will be a breaking change due to changes in the yaml syntax for handling multiple wake word models.

This PR adds several features/performance improvements:

• Multiple wake word models can run simultaneously
  • At most two of the current models can run simultaneously without issue
• Adds support for running a Voice Activity Detection model to potentially reduce certain false accepts
  • The current VAD model can only run with 1 model at the same time. If you try to run VAD and two models all at once, accuracy will suffer greatly
• Several memory improvements
  • Models are loaded and unloaded as mWW starts and stops to save memory when not actively running
  • All buffers (excluding the ring buffer) are freed when not actively running
  • Ring buffer size is reduced (if it filled up before, there was no chance of ever recovering and so 0.5 s of audio was dropped each time)
  • Makes the tensor arena's default allocated memory smaller. The exact space allocated can be set in the codegen stage.

Todo:

• Update the manifest format
  • Add a field for the necessary tensor arena size (currently the values are hardcoded in __init__.py)
  • Add support for a VAD helper model along with its specific parameters
• Allow users to only enable VAD instead of having to point to a specific manifest file (also requires uploading the VAD model to the appropriate default repository)
• ?Possibly better handle the VAD code? I have added a new preprocessor directive to only compile the relevant code if it is enabled, but I'm not sure if this is the best way to handle it. Warning: Enabling/disabling a VAD model will require a full recompile when rebuilding, so if you have a slow computer, this may take awhile!
• Update the documentation (see the example yaml at the end of this PR in the mean time)
• Fix any bugs people encounter in testing

Types of changes

• Bugfix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Other

Related issue or feature (if applicable): not applicable

Pull request in esphome-docs with documentation (if applicable): unfinished

Test Environment

• ESP32
• ESP32 IDF
• ESP8266
• RP2040
• BK72xx
• RTL87xx

Example entry for config.yaml:

# Example config.yaml for multiple models

micro_wake_word:
  on_wake_word_detected:
    - voice_assistant.start: 
        wake_word: !lambda return wake_word; 
  models:
    - model: okay_nabu
      sliding_window_average_size: 5
    - model: hey_jarvis
      probability_cutoff: 0.75

# Example config.yaml for VAD

micro_wake_word:
  on_wake_word_detected:
    - voice_assistant.start: 
        wake_word: !lambda return wake_word; 
  vad_model: 
    model: https://github.com/kahrendt/microWakeWord/releases/download/model/vad_model.json
    sliding_window_average_size: 2
    threshold:
      upper: 0.95
      lower: 0.5
  models:
    - model: alexa

Checklist:

• The code change is tested and works locally.
• Tests have been added to verify that the new code works (under tests/ folder).

If user exposed functionality or configuration variables are added/changed:

• Documentation added/updated in esphome-docs.

[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 54.05%. Comparing base (4d8b5ed) to head (a4886ac).
Report is 494 commits behind head on dev.

Additional details and impacted files

@@            Coverage Diff             @@
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+ Coverage   53.70%   54.05%   +0.34%     
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  Files          50       50              
  Lines        9408     9554     +146     
  Branches     1654     1687      +33     
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+ Hits         5053     5164     +111     
- Misses       4056     4066      +10     
- Partials      299      324      +25     

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