For far too long, speech recognition just hasn’t worked well enough to be usable for everyday purposes. Even simple command and control by voice had been barely functional and unreliable…but times, they are a changing! Today speech recognition works quite well and is widely used in computer and smart phone applications…and I believe we are rapidly converging on the Holy Grail of Speech – making a recognition and response system that can be virtually indistinguishable from a human (a really smart human with immaculate spelling skills and fluency in many languages!)
I think there are 4 important components to what I’d call the Holy Grail in Speech:
- No Buttons Necessary. OK here I’m tooting my own whistle, but Sensory has really done something amazing in this area. For the first time in history there is a technology that can be always-on and always-listening, and it consistently works when you call out to it and VERY rarely false-fires in noise and conversation! This just didn’t exist before Sensory introduced the Truly Handsfree™ Voice Control, and it is a critical part of a human-like system. Users don’t want to have to learn how to use a device, Open Apps, and hold talk buttons to use! People just want to talk naturally, like we do to each other! This technology is HERE NOW and gaining traction VERY rapidly.
- Natural Language Interactions. This is a bit tricky, because it goes way beyond just speech recognition; there has to be “meaning recognition”. Today, many of the applications running on smart phones allow you to just say what you want. I use SIRI (Nuance), Google and Vlingo pretty regularly, and they are all very good. But what’s impressive to me isn’t just how good they are, it’s the rate at which they seem to be improving. Both the recognition accuracy and the understanding of intent seem to be gaining ground very rapidly.
I just did a fun test…I asked each engine (in my nice quiet office) “How many legs does an insect have?”…and all three interpreted my request perfectly. Google and Vlingo called up the right website with the question and answer…and SIRI came back with the answer – six! Pretty nice! My guess is the speech recognition is still a bit ahead of the “meaning recognition”…
Just tried another experiment. I asked “Where can I celebrate Cinco de Mayo?” SIRI was smart enough to know I wanted a location, but tried to send me off to Sacramento (sorry – too far away for a margarita!) Vlingo and Google both rely on Google search, and did a general search which didn’t seem to associate my location… (one of them mis-recognized, but not so badly that they didn’t spit out identical results!) Anyways, I’d say we are close in this category, but this is where the biggest challenge lies. - Accurate Translation and Transcription. I suppose this is ultimately important in achieving the Holy Grail. I don’t do much of this myself, but it’s an important component to Item 2 above, and also necessary for dictating emails and text messages. When I last tested Nuance’s Dragon Dictate I was blown away by how well it performed. It’s probably the Nuance engine used in Apple’s Siri (you know, Nuance has a lot of engines to choose from!), and it’s really quite good. I think Nuance is a step ahead in this area.
- Human Sounding TTS. The TTS (text-to-speech) technology in use today is quite remarkable. There are really good sounding engines from ATT, Nuance, Acapela, Neospeech, SVOX, Ivona, Loquendo and probably others! They are not quite “human”, but come very close. As more data gets thrown at unit selection (yes, size will not matter in the future!), they will essentially become intelligently spliced-together recordings that are indistinguishable from live performance.
Anyways, reputable companies are starting to combine and market these kinds of functions today, and I’d guess it’s a just a matter of five to ten years until you can have a conversation with a computer or smartphone that’s so good, it is difficult to tell whether it’s a live person or not!