From 4fc70bffb399623e81470c1e600fab6177e66762 Mon Sep 17 00:00:00 2001 From: Josh Meyer Date: Mon, 26 Jul 2021 09:40:35 -0400 Subject: [PATCH] Fix dir structure for Model Zoo --- english/coqui/yesno-v0.0.1/LICENSE | 202 +++++++++++++++++++++++ english/coqui/yesno-v0.0.1/MODEL_CARD.md | 79 +++++++++ english/coqui/yesno-v0.0.1/alphabet.txt | 6 + 3 files changed, 287 insertions(+) create mode 100644 english/coqui/yesno-v0.0.1/LICENSE create mode 100644 english/coqui/yesno-v0.0.1/MODEL_CARD.md create mode 100644 english/coqui/yesno-v0.0.1/alphabet.txt diff --git a/english/coqui/yesno-v0.0.1/LICENSE b/english/coqui/yesno-v0.0.1/LICENSE new file mode 100644 index 0000000..d645695 --- /dev/null +++ b/english/coqui/yesno-v0.0.1/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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This model has been trained to only recognize the two words "yes" and "no" in English. + +## Performance Factors + +Factors relevant to Speech-to-Text performance include but are not limited to speaker demographics, recording quality, and background noise. Read more about STT performance factors [here](https://stt.readthedocs.io/en/latest/DEPLOYMENT.html#how-will-a-model-perform-on-my-data). + +## Metrics + +STT models are usually evaluated in terms of their transcription accuracy, deployment Real-Time Factor, and model size on disk. + +#### Transcription Accuracy + +The model was trained and evaluted on the Common Voice Target Segments Corpus, specifically, only on "yes" and "no" audio clips. + +|Test Corpus|Word Error Rate| +|-------|----------| +|Common Voice 6.1 (Target Segments Corpus "yes" and "no") | 1.6\% | + +#### Model Size + +`yesno.pbmm`: 319K +`yesno.scorer`: 1.7K + +### Approaches to uncertainty and variability + +Confidence scores and multiple paths from the decoding beam can be used to measure model uncertainty and provide multiple, variable transcripts for any processed audio. + +## Training data + +The model was trained and evaluted on the Common Voice Target Segments Corpus, specifically, only on "yes" and "no" audio clips. + +## Evaluation data + +The model was trained and evaluted on the Common Voice Target Segments Corpus, specifically, only on "yes" and "no" audio clips. + +## Ethical considerations + +Deploying a Speech-to-Text model into any production setting has ethical implications. You should consider these implications before use. + +### Demographic Bias + +You should assume every machine learning model has demographic bias unless proven otherwise. For STT models, it is often the case that transcription accuracy is better for men than it is for women. If you are using this model in production, you should acknowledge this as a potential issue. + +### Surveillance + +Speech-to-Text may be mis-used to invade the privacy of others by recording and mining information from private conversations. This kind of individual privacy is protected by law in may countries. You should not assume consent to record and analyze private speech. + +## Caveats and recommendations + +Machine learning models (like this STT model) perform best on data that is similar to the data on which they were trained. Read about what to expect from an STT model with regard to your data [here](https://stt.readthedocs.io/en/latest/DEPLOYMENT.html#how-will-a-model-perform-on-my-data). + +In most applications, it is recommended that you [train your own language model](https://stt.readthedocs.io/en/latest/LANGUAGE_MODEL.html) to improve transcription accuracy on your speech data. diff --git a/english/coqui/yesno-v0.0.1/alphabet.txt b/english/coqui/yesno-v0.0.1/alphabet.txt new file mode 100644 index 0000000..04c9235 --- /dev/null +++ b/english/coqui/yesno-v0.0.1/alphabet.txt @@ -0,0 +1,6 @@ +y +e +s +n +o +#