The baseline configurations all note <2s and <3s times. I haven't tried any voice AI stuff yet but a 3s latency waiting on a reply seems rage inducing if you're actually trying to accomplish something.
Please don't. I had a talk with a shitty AI bot on a Fedex line. It's absolute crap. Just give me a 'Type 1 for x, type 2 for y'. Then I don't need to guess what are the possibilities.
One problem is once you’re in deep building a phone IVR workflow beyond X or Y (yes, these are intentional), callers don’t care about some deep and featured input menu. They just mash 0 or pick a random option and demand a human finish the job and transfer them - understandably.
When you’re committed to phone intent complexity (hell), the AI assisted options are sort of less bad since you don’t have to explain the menu to callers, they just make demands.
Voice-controlled phone systems are hugely rage-inducing for me. I am often in loud setting with background chatter. Muting my audio and using a touchtone keypad is so much more accurate and easy than having to find a quiet place and worrying that somebody is going to say something that the voice response system detects.
One easy way to build voice agents and connect them to Twilio is the Pipecat open source framework. Pipecat supports a wide variety of network transports, including the Twilio MediaStream WebSocket protocol so you don't have to bounce through a SIP server. Here's a getting started doc.[1]
(If you do need SIP, this Asterisk project looks really great.)
Pipecat has 90 or so integrations with all the models/services people use for voice AI these days. NVIDIA, AWS, all the foundation labs, all the voice AI labs, most of the video AI labs, and lots of other people use/contribute to Pipecat. And there's lots of interesting stuff in the ecosystem, like the open source, open data, open training code Smart Turn audio turn detection model [2], and the Pipecat Flows state machine library [3].
Disclaimer: I spend a lot of my time working on Pipecat. Also writing about both voice AI in general and Pipecat in particular. For example: https://voiceaiandvoiceagents.com/
I’m honestly surprised it hasn’t been more prevalent yet. I still get call centre type spam calls where you can hear all the background noise of the rest of the call centre.
Is that really where SOTA is right now?
When you’re committed to phone intent complexity (hell), the AI assisted options are sort of less bad since you don’t have to explain the menu to callers, they just make demands.
(If you do need SIP, this Asterisk project looks really great.)
Pipecat has 90 or so integrations with all the models/services people use for voice AI these days. NVIDIA, AWS, all the foundation labs, all the voice AI labs, most of the video AI labs, and lots of other people use/contribute to Pipecat. And there's lots of interesting stuff in the ecosystem, like the open source, open data, open training code Smart Turn audio turn detection model [2], and the Pipecat Flows state machine library [3].
[1] - https://docs.pipecat.ai/guides/telephony/twilio-websockets [2] - https://github.com/pipecat-ai/pipecat-flows/ [3] - https://github.com/pipecat-ai/smart-turn
Disclaimer: I spend a lot of my time working on Pipecat. Also writing about both voice AI in general and Pipecat in particular. For example: https://voiceaiandvoiceagents.com/