Probably the patent portfolio that Nuance aggressively asserts[1]. They also went on a 51-company (!!!) acquisition spree up to 2018[2] after ScanSoft acquired Nuance[3] (but kept the name) in 2005, when both of them were #1 and #2 in the speech recognition space.
While Nuance may have failed to embrace DL approaches, Apple has been willing to license Nuance technology to power Siri for many years[4].
EDIT: They recently acquired another company in February 2021.[5]
[1] https://www.ft.com/content/dd908d81-4859-4d19-a1e8-e5f7b4f01...
[2] https://en.wikipedia.org/wiki/Nuance_Communications
[3] https://www.computerworld.com/article/2556291/scansoft-to-bu...
[4] https://www.forbes.com/sites/rogerkay/2014/03/24/behind-appl...
[5] https://www.fiercehealthcare.com/practices/nuance-acquires-s...
I got to see inside the beast and it www just out of control growth from acquisition. The IBM voice patent had eclipsed scansoft was.
Kind of strange MS wanting it for anything but their patents. The business was shit. As a side benefit they can shut down Siri since the apple deal was such a linchpin.
As someone who works professionally in this space, I can say that most commenters thus far have completely missed it. The angle here is Conversational AI in the Enterprise Call Center market. This is a market worth hundreds of billions of dollars annually. This announcement is almost certainly a reaction to the partnership between Genesys and Google to create Google Cloud Contact Center AI. I know a lot of people hate customer service chatbots, doesn't matter, companies are spending a fortune on them to replace agents and Microsoft/Google/Amazon want a slice of that pie.
I even wrote a VoiceXML interface to Zork that used Nuance. The user could say stuff like, 'Go east', 'use axe', etc. It was pretty silly but you could play original Zork via the telephone :)
20 years ago people were talking about the big money in voice recognition being in enterprise call centers. And so it's interesting to me that this is still the big market force.
This may be a feature, not a bug. Explainability is very difficult with deep learning systems, and that often makes deep learning less suitable for some compliance applications like government usage. Microsoft may also still be feeling more conservative after their twitter bot learned so well a few years ago.
And if you use it to control medical devices, then transparency is not what matters. A protocol matters, like the machine repeating the commands and asking for confirmation.
The main difference in voice for these apps is an intentionally limited and specialised vocabulary, where you have to be pretty certain that they said aberrant rather than apparent, or anuresis rather than enuresis. A lack of humeral would mean you are lacking a particular fluid, while a lack of humerous would mean you are missing a bone. The difference between an apparent mole and an aberrant mole is pretty huge, so you want to be sure your AI isn't over-fitting.
Also the wider ecosystem of this is that you have to have a full software for editing and checking the notes that is compliant to local healthcare regulations, and standard interfaces into medical software. Also penetration into the healthcare market is notoriously hard.
I would imagine synergies in this space include things like Microsoft Teams being in a good place to take on remote consultations compared to Zoom et al, as you could have a seamless flow from consultation to record in the healthcare system and medically-accurate transcription.
Aberrant mole apparent mole. Works like a charm. Now let me blow your mind with another speech to text: ganglioneuralgia.
I think this acquisition has anything to do with DL vs traditional. We're running opaque DL models transparency at a major academic hospital to help treat patients. This is a cake walk by comparison. Specialized vocabulary? Just pay a few people to read some medical textbooks and your done.
I think they just want the reputation customers and product suite.
Also they're making integrations out the wazoo with ehrs. I actually can't believe it, but epoc let Microsoft integrate teams. Integrating and licensing voice is easily a next step.
So it's the most "modern" solution they can offer their company without having to do any real additional security work.
Or alternatively, no other solution offers similar price/performance - They are having success because for most corporate subscriptions it is free. Also it's the most commonly used solution for business in the UK, so I have less problems with people joining teams calls than any other provider.
I don't think it's small mindedness - what other solution should they offer?
* Zoom - Awful internal messaging capability. A full office 365 subscription costs almost the same as a standalone zoom licence.
* Slack - No support for external conference calling without integration to another service.
* Google Meet - Makes sense if you use google suite, but not really if you use 365. Other than that not too bad.
* Webex - Awful client requires downloading which causes people to have issues half the time.
2. You generally don't gain more confidence in the accuracy of a particular word by looking at less context. This is neither how human nor machine recognition works.
I've not got direct experience in healthcare, but do have experience in industrial voice, and this is an area where Apple/Google generalised libraries perform significantly worse than specialised software (Dragon is also big in this industry, albeit at the SDK level). In industrial voice the main requirements are high levels of background noise, restricted vocabulary (20-30 words) and people speaking very quickly.
Nuance has very strong presence in medical transcription, retail and a few other areas. Microsoft can move them to Azure and their own speech to text technology.