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--- |
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language: "rw" |
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thumbnail: |
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pipeline_tag: automatic-speech-recognition |
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tags: |
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- Coqui |
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- Deepspeech |
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- LSTM |
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license: "apache-2.0" |
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datasets: |
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- commonvoice |
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metrics: |
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- wer |
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--- |
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**Model card - Kinyarwanda coqui STT model** |
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**Model details** |
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- Kinyarwanda Speech to text model |
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- Developed by [Digital Umuganda](digitalumuganda.com) |
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- Model based from: Baidu Deepspeech end to end RNN model |
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- paper: [deepspeech end to end STT](https://arxiv.org/pdf/1412.5567.pdf) |
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- Documentation on model: [deepspeech documentation](https://deepspeech.readthedocs.io/) |
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- License: Mozilla 2.0 License |
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- Feedback on the model: samuel@digitalumuganda.com |
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**Intended use cases** |
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- Intended to be used for |
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- simple keyword spotting |
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- simple transcribing |
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- transfer learning for better kinyarwanda and african language models |
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- Intended to be used by: |
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- App developpers |
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- various organizations who want to transcribe kinyarwanda recordings |
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- ML researchers |
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- other researchers in Kinyarwanda and tech usage in kinyarwanda (e.g. Linguists, journalists) |
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- Not intended to be used as: |
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- a fully fledged voice assistant |
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- voice recognition application |
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- Multiple languages STT |
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- language detection |
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**Factors** |
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- Anti-bias: these are bias that can influence the accuracy of the model |
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- Gender |
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- accents and dialects |
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- age |
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- Voice quality: factors that can influence the accuracy of the model |
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- Background noise |
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- short sentences |
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- Voice format: voices must be converted to the wav format |
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- wav format |
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**Metrics** |
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- word error rate on the Common Voice Kinyarwanda test set |
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|Test Corpus|WER| |
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|-----------|---| |
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|Common Voice|39.1\%| |
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**Training data** |
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- [common voice crowdsource website](https://commonvoice.mozilla.org/en/datasets) |
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**Evaluation data** |
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- [common voice crowdsource website](https://commonvoice.mozilla.org/en/datasets) |
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