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The Speech to Text WTH hack will help hackers understand how to use Azure's Cognitive Speech services. The hack will take call center data and navigate through challenges to learn the tools to transcribe the audio files, improve the accuracy of these transcriptions, determine the intent of the calls, assess sentiment and PII redaction. Finally, we will be able to run the model in their own environment.
Abstract/Learning Objectives
Data Cleaning + Preprocess Ground Truth Files
Train a standard model
Train a custom acoustic model
Test and evaluate the accuracy of the models
Deploy and containerize the models
Delivery Date
3/10/23
Authors
Lauren Tran , GitHub: laurentran
Jason Virtue, GitHub: DataSciNAll
Israel Ekpo, GitHub: izzymsft
Ellie Nosrat, GitHub: EllieNosrat
Other
Natural Language Processing is a common hero offering by Microsoft. Documentation is limited on how to setup and process audio data (unstructured) and this WTH will help developer readiness. This will be the first WTH on NLP.
Code of Conduct
I agree to follow this project's Code of Conduct
The text was updated successfully, but these errors were encountered:
Topic
The Speech to Text WTH hack will help hackers understand how to use Azure's Cognitive Speech services. The hack will take call center data and navigate through challenges to learn the tools to transcribe the audio files, improve the accuracy of these transcriptions, determine the intent of the calls, assess sentiment and PII redaction. Finally, we will be able to run the model in their own environment.
Abstract/Learning Objectives
Delivery Date
3/10/23
Authors
Other
Natural Language Processing is a common hero offering by Microsoft. Documentation is limited on how to setup and process audio data (unstructured) and this WTH will help developer readiness. This will be the first WTH on NLP.
Code of Conduct
The text was updated successfully, but these errors were encountered: