Peter, Thanks for the insights. I just tried out Twilio's Speech to Text API and played the same message as Yext Demo. It worked out pretty well so I am very impressed. It's likely that Twilio uses SpinVox in the back-end anyway.. By the way, I think Yext records the call and sends the recorded file for transcription. This saves the hassle of mixing and transcribing two different audio files.
Yes, Yext has a fairly impressive solution indeed and I could think of so many applications that are vertical specific (e.g. Automotive). I could imagine Yext building a lot of library relevant to each category (e.g. Doctor, Mechanic, Finance etc) and then doing a close/guess association of the returned text to white/blacklist certain terms and then splitting them into different sub-categories (e.g. Year built, Make/Model etc). This is hard work (hence barrier to entry) and they seem to have raised $17M in recent round in addition to running a (self asserted) $20M and growing business. Hard to play the catch up game... Another interesting fact is that Yext solution would improve with time much like wine. Given the call/customer flow and lack of competition, Yext could continue to improve the keyword filtering and categorizing over time creating a fairly accurate solution. Ritesh On Wed, Sep 30, 2009 at 9:31 AM, Peter Beckman <[email protected]> wrote: > On Wed, 30 Sep 2009, Ritesh A wrote: > > Folks, >> >> Does anyone have a clue on how Yext transcribes the calls (almost) on the >> fly? >> I am pretty sure they are using asterisk at the heart and perhaps using >> some >> neat APIs for call transcription. >> If you are know of any outfit there that provides similar APIs, please >> ping >> me... >> >> If anyone is interested in learning more about Yext, here is the video >> demo >> of their interesting demo at TC50 >> >> http://www.ustream.tv/recorded/2163590 >> > > I am extremely impressed with Yext. Thanks for the link and your post! > > Here's my take on how they do it. > > * recording both ends of the call separately (Asterisk can do this) > * pass both audio files to a voice processing API (SpinVox) > * integrate the relating text into a conversation flow (very cool, not > sure how, depends on the API) > * parse resulting text into keywords matching categories (maybe scoring > them somehow), then if the score is high enough, using a higher level > matching (if a year (2007), make (Porche) and model (911) are mentioned, > put them together in the right order and put it in the inbox, > searchable). > > Both the merging of the two sides of conversation and The keyword matching > is where they really did some cool stuff. While I can think of how they > did it in theory, it probably took a lot of work to pull that off. > "Automotive" is likely a set of related keywords, and then another set of > keyword combinations. One of the combos combine the matches on keywords > found, then matches those to "[year] [make] [model]" as a relevant > keyphrase if Automotive is selected. > > Beckman > --------------------------------------------------------------------------- > Peter Beckman Internet Guy > [email protected] > http://www.angryox.com/ > --------------------------------------------------------------------------- > _______________________________________________ > --Bandwidth and Colocation Provided by http://www.api-digital.com-- > > AstriCon 2009 - October 13 - 15 Phoenix, Arizona > Register Now: http://www.astricon.net > > asterisk-biz mailing list > To UNSUBSCRIBE or update options visit: > http://lists.digium.com/mailman/listinfo/asterisk-biz > _______________________________________________ > --Bandwidth and Colocation Provided by http://www.api-digital.com-- > > AstriCon 2009 - October 13 - 15 Phoenix, Arizona > Register Now: http://www.astricon.net > > asterisk-biz mailing list > To UNSUBSCRIBE or update options visit: > http://lists.digium.com/mailman/listinfo/asterisk-biz >
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