This can be both general, as well as course specific.
Improve recognition accuracy on industry-specific vocabulary and grammar, like medical terminology or IT jargon
This takes in text input. We can scrape slides/syllabus/textbooks for better transcription of CS specific terms.
Define the phonetic and displayed form of a word or term that has nonstandard pronunciation, like product names or acronyms
This probably won't be too often, but maybe some words like Sequel -> SQL can be fixed.
Improve recognition accuracy on speaking styles, accents, or specific background noises
This is audio+text input. For standard American accents, the baseline models are fine, but for specific professors we can fine tune the model. Generally there might be some captioned classes from previous semester (via DRES or similar) that can be put in as trained datasets.
WilliamFoster3
commented
2 years ago
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-custom-speech-train-model
This can be both general, as well as course specific.
This takes in text input. We can scrape slides/syllabus/textbooks for better transcription of CS specific terms.
This probably won't be too often, but maybe some words like Sequel -> SQL can be fixed.
This is audio+text input. For standard American accents, the baseline models are fine, but for specific professors we can fine tune the model. Generally there might be some captioned classes from previous semester (via DRES or similar) that can be put in as trained datasets.