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