picheny

6 ms·

1.
by picheny 11y ago
Great news! A lot of improvements relative to the beta service!
2.
by picheny 12y ago
Yeah, you are right we should be filtering this sort of stuff out. The algorithms are robust in that they ignore words not in the system's vocabulary (rather than, say, crash) but we did not trap the case in which none of the "wor
3.
by picheny 12y ago
It is understandable; different people may see different performance depending on what speech service is used. In addition, please keep in mind this is just a beta service; we have only been out there less than a week and know we still have
4.
by picheny 12y ago
We are flattered by the interest and will look into it; obviously given no one has looked at this for years, it is not a likely possibility.
5.
by picheny 12y ago
It's an obvious extension of what we put out; keep watching the Watson Developer Cloud announcements.
6.
by picheny 12y ago
Beta is certainly beta but if you find problems we will try to fix them as quickly as we can. Real users of technologies tend to find issues with the technology much faster than the actual developers...
7.
by picheny 12y ago
Sorry, I missed the question at the bottom. We were very proud of ViaVoice at the time but to make an obvious point, the technology has moved on a lot over the past ten or so years...
8.
by picheny 12y ago
We only gave up the shrinkwrap product; the core technology stayed with IBM.
9.
by picheny 12y ago
We really appreciate the comments and will try to fix the problems. To be honest, sometimes developers can't see even the most obvious flaws in documentation. If you can highlight even one incomprehensible point it would help a lot to
10.
by picheny 12y ago
We did some work on applying NNs to prosody prediction; see Fernandez, Raul, et al. "Prosody contour prediction with long short-term memory, bi-directional, deep recurrent neural networks." Proceedings of the Annual Conference of
11.
by picheny 12y ago
SSML is a speech synthesis markup language that has some degree of popularity in the field. The specific section on markup for emphasis is http://www.w3.org/TR/speech-synthesis11/#S3.2
12.
by picheny 12y ago
One thing a machine learning system can do that any one human cannot do is ingest lots of data. For example, for some tasks in which I have tried to compare human vs machine speech recognition performance the machine actually does better be
13.
by picheny 12y ago
Yeah, Chrome currently seems to have the best support for audio capture.....
14.
by picheny 12y ago
We want feedback on all our services. If you are speaking about using data to update the service, I know the speech services do not yet have this capability.
15.
by picheny 12y ago
Yeah it was. At the risk of waxing about old history, when we demoed the first large vocabulary speech recognition system back in 1984 it ran on a bunch of IBM mainframes. Within two years it was running on a PC with some special purpose ca
16.
by picheny 12y ago
honestly we have not gotten that far yet - at least on the speech technology side. Good discussion to have.
17.
by picheny 12y ago
you mean ibms service?
18.
by picheny 12y ago
Well, I don't think the technology is that bad :-). But I agree with you. We have to solve the problem of poorer quality audio input, and the sooner the better! But there are also many scenarios where good audio input is feasible and w
19.
by picheny 12y ago
As a speech technologist, I am amazed and proud about how far long the technology has progressed, especially over the last few years. Even my wife now uses speech input on mobile devices (and may finally think I may be doing something produ
20.
by picheny 12y ago
We know we have strong core speech technology based on various comparisons we have done in the context of competitive evaluations done in conjunction with various government funded speech programs. However, our service is still very new. We
21.
by picheny 12y ago
We have worked on audio analytics in the past for things such as outdoor sound detection and vehicle identification. We are currently focusing on speech-based analytics such as language ID and affect recognition. The statistical methodologi