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I also tried and failed here. We ran our own speech engine with a custom model- but it's extremely expensive as a cloud service, and incredibly tough to reach a
by skoocda 5y ago
I also tried and failed here. We ran our own speech engine with a custom model- but it's extremely expensive as a cloud service, and incredibly tough to reach acceptably high accuracy in different environments. Adding NLP on top of error-prone transcripts will multiply the error rate and lead to all sorts of weird actions.
I really think on-device models like we see in Android's Live Caption tool are a major privacy boon, and they're starting to reach an acceptable level of performance in Google's case. The main pathway to better performance is loading ever-more-massive models into memory, which isn't feasible for mobile devices but could be done on people's laptops in a meeting.
- toyg 5y ago"Privacy", "on-device", and "Google", all in the same sentence...? Sounds unrealistic.
- deadmutex 5y agoPichai: "Yes, we use data to make products more helpful for everyone. But we also protect your information." https://www.nytimes.com/2019/05/07/opinion/google-sundar-pichai-privacy.html https://www.nytimes.com/2019/05/07/opinion/google-sundar-pic...
- ai_ia 5y agoI believe you ought to check out Federated Machine Learning techniques.[1] [1]: https://ai.googleblog.com/2017/04/federated-learning-collaborative.html https://ai.googleblog.com/2017/04/federated-learning-collabo...