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Improve ASR accuracy - Recognise slide content; Upload local taxonomy/dictionary; AI learning
We use Panopto in medical education. ASR is good but struggles with any technical language (drugs, anatomy, biology) - we're getting less than 50% accuracy, which is really not good enough and is causing great concern among our faculty (they are asking if there are better providers!).
Please could you improve the accuracy of ASR. We suggest three avenues:
- Slide text recognition - often the spoken words are included in the PowerPoint slide. Can ASR harvest/recognise this text and add it to the lexicon to reference its translation algorithm?
- Upload local taxonomy - could the institution (or school or user) upload a text file of technical terminology to add to the ASR lexicon to reference its translation algorithm?
- AI learning - does the ASR system actually learn from corrections that are made? Are new terms added to the ASR lexicon for reference? Colleagues are not seeing this happen but surely this is a key feature of machine translation technology.