android
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android/en/android-20201215-jarbas.tar.gz
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android/en/android-20201215-jarbas.tar.gz
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android/en/models/README.md
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android/en/models/README.md
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# Android models
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### EN
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#### android-en-0.3-20201215-jarbas.tar.gz
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Trained using a personal dataset, for not wake-word the google-commands
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dataset, false_activations-20201215.tar.gz, bg_noise-20201215.tar.gz and
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noises-20190814-elt.tar.gz were used
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Training data contained several speakers from various countries and genders,
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with about 3 samples per speaker, microphone quality and pronounciation varied
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a lot per speaker
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Added to this 64 samples of my own voice collected with mycroft-core during
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testing of the initial model available at android-20201215-jarbas.tar.gz
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=== TrainData ===
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- wake_words=114
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- not_wake_words=14444
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- test_wake_words=38
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- test_not_wake_words=14496
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=== Test set results ===
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- 14513 out of 14533
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- 99.86%
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- 0.07% false positives
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- 26.32% false negatives
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- False Positives: 10
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- True Negatives: 14485
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- False Negatives: 10
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- True Positives: 28
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android/en/models/android-en-0.3-20201215-jarbas.tar.gz
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android/en/models/android-en-0.3-20201215-jarbas.tar.gz
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licenses/license-20201215-jarbas.txt
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licenses/license-20201215-jarbas.txt
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I, JarbasAi, hereby agree to waive all claim of copyright (economic and moral) in all content contributed by me, the user, and immediately place any and all contributions by me into the public domain, unless otherwise noted.
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I grant anyone the right to use my work for any purpose, without any conditions, to be changed or destroyed in any manner whatsoever without any attribution or notification.
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No warranties are given.
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Files released into public domain:
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not-wake-words/noises/bg_noise-20201215.tar.gz
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not-wake-words/noises/false_activations-20201215.tar.gz
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android/en/models/android-en-0.3-20201215-jarbas.tar.gz
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android/en/android-20201215-jarbas.tar.gz
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not-wake-words/noises/bg_noise-20201215-readme.md
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These samples are "silence" cropped from in between wake word recordings,
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meaning a long recording contained several wake word samples and this is
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the silence in between
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not-wake-words/noises/bg_noise-20201215.tar.gz
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These samples are false activations recorded by mycroft-core with the
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"record_wake_words" flag set to True
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In northern portugal it's common to say "ó XXX" instead of "hey XXX", a
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model i was training learned to always trigger on the "ó", many of these
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samples reflect that and should be helpful for this kind of wake word.
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Other samples will contain random noises and potentially some dialog from TV
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not-wake-words/noises/false_activations-20201215.tar.gz
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