data sets #119

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1. ljj7975 commented on Nov 5, 2022

   

   ljj7975

   on Nov 5, 2022

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   positive refers to audios with target keyword (fire).
   negative are the audios without target keyword (fire).

   training on negative set helps decreasing false positive rate.

   Unfortunately, there isn't a good way of generating a dataset for custom wakeword.
   If it is made up of common word such as hey, hi, cat. Data generation using Mozilla Dataset should work.

   However, generating a dataset for non-standard word such as hakunamatata is not yet supported.
2. wwyl2000 commented on Nov 5, 2022

   

   wwyl2000

   on Nov 5, 2022

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   Hi ljj7975,
   Many thanks for your informaion.
   Best,
   wwy
3. Ruiqin-Huang commented on Jan 27, 2025

   

   Ruiqin-Huang

   on Jan 27, 2025

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   Howl is a frame-level wake word detection system. When training for a single English wake word like "fire", should the training/development/test sets:

   Option A: Contain only audio samples with the exact wake word?
   Example:

   • sample_1's transcription: "fire"
   • sample_2's transcription: "fire"

   OR

   Option B: Contain sentences that include the wake word?
   Example:

   • sample_1's transcription: "fire in the sky"
   • sample_2's transcription: "The building was on fire, with flames engulfing the upper floors"