The document discusses using IBM Watson for voice recognition in a language learning app. It notes that Watson supports custom keywords, does not stick to brand names, and has good language variety. Testing found an accuracy of about 60% for non-native speakers, even with a low 20% keywords threshold, which was deemed terrible. The document considers using other providers like Amazon LEX, Google Voice, or building their own solution instead of Watson.

1. IBM Watson
As a tutor, not just a voice interface

2. About me
● Backend engineer with 7+ years in web development
● Basic ML knowledge
● Have Alexa at home

3. 01 February 2017GoogleSlide Master Flash
Hallo!
Привет!

4. About product
Language learning app, adaptive
Adding voice recognition support, evaluating different ideas

5. Providers
● Amazon LEX
● Google Voice
● Siri
● IBM Watson
● Own solution

6. IBM Watson
● The product is built focused on different areas (like Education, Health etc.)
● Support custom keywords to search for in the speech
● Does not stick to the brand names during the recognition
● Has good variety of languages

7. Integration
● API :)

8. Integration
● API, which is extremely easy to integrate with
● Few models of interaction: sessionless, websocket, async

9. An issue
Non-native speakers

10. Result
Accuracy is about 60%

11. Result
Accuracy is about 60%
Even on 20% keywords threshold

12. Result
Accuracy is about 60%
Even on 20% keywords threshold
Terrible

13. This feeling

14. Questions
Kirill Zonov
http://zonov.me/
Babbel Senior Engineer