I don't mind music-on-hold as much except when they break with a human voice at intervals saying inane things such as "your call is important to us. Thank you for holding" Which makes me think the call has been answered.
If there's not actual call queue information, just play music so I can ignore it and continue working without that NOP interrupt.
I guess the comment was just about how much Asterisk deployments are out there because you can often hear its default music-on-hold? But maybe I'm wrong.
thats funny, i interpreted this as "Hosted Asterisk People Sell a Default Experience" (and probably charge for custom messages) so its cool to see something different and marketable
My local dealership adopted one of these for their service department. Prior to the AI assistant, you would call and immediately be placed on hold because the same people serving customers at the desk were answering the phone. The AI picks up right away and can schedule an oil change. It's fantastic and I'd love to see more of this. Of course it also has the ability to escalate to a human for the things it doesn't have capabilities for.
For narrow use cases like this I personally don't mind these tools.
If they have the ability to hook an llm up to a system that can schedule an oil change why can’t they provide a form on their website to do the same thing and save everyone the hassle?
Just ask your LLM to call the dealership. The only downside is spoken word is a bit slow for computers. Maybe we can even work out a protocol where the LLM voices talk faster and faster until they can't hear tokens clearly
At that point we’ll have to convert the voices into a form more amenable to machine to machine communication. Perhaps a system based on high and low signals.
They do, via the manufacturer's app. It works fine as well.
Situational context matters though, sometimes you get in the vehicle and get the alert. Just say "Hey Siri, call dealership" and away you go hands free. No messing with apps.
They do offer the ability to schedule an oil change via the website and yet some people still prefer to call. User preference and multi-channel servicing options are nice to support
Unsure about whether the specific dealership in question supports online booking, but there existing consumers whose preference is for a phone call over a web-based experience is definitely the case, at least in the US.
For example, even with the (digital-only) SAAS company I work at, we have a non-trivial amount of customers who with strong preferences to talk on the phone, ex to provide their credit card number, rather than enter it in the product. This is likely more pronounced if your product serves less tech-savvy niches.
That said, a strong preference for human call > website use doesn't necessarily imply even a weak preference for AI call > website use (likely customer-dependent, but I'd be surprised if the number with that preference was exactly 0)
how about the plainly obvious fact that every call tree system first spends 1-8 minutes going through all the things that you can actually do on the website instead of calling: do you really think they would bother with that if people aren’t calling about stuff that is easily done on the website? sure, we all agree that it is partly designed to get people to hang up in disgust and give up, but that is an obviously insufficient explanation compared to the simpler and more comprehensive explanation that people simply do, as a matter of fact, prefer to use the phone despite it being clearly less useful for easily-computer-able tasks.
How? Businesses will use this to justify removing what few actual human support staff they have left. Nobody, and I mean it, nobody calls customer support because they want to talk to a computer. It’s the last resort for problems that usually can’t be accomplished via the already existing technical flows available via computer.
That's not true. I recently called to make an appointment. I don't care if it's an AI. I would actually prefer it, because I wouldn't feel bad about taking a long time to pick the best time. Don't you think you're being a bit dogmatic about this?
I have to feel that an online booking system is substantially lower tech than an ai voice assitant chatbot, and makes it even easier to ruminate as you pick the time that works for you.
In my case, the business did have human support assistants, but didn't do reservations via the phone. I had to switch to the web app for that, which was annoying (I was driving?). I guess doing user identification over the phone and scheduling the appointment are time-consuming for the human assistant, while these are some of the few things an app can do well. I presume the logic is to preserve human assistants for actually complicated or dynamic assistance, for the sake of cost-efficiency. A voice llm can bring down the cost of these basic-but-time-consuming interactions.
I wonder what Amazon's goals are, as an example. Currently, at least on the .ca website, there is no way to even get to chat to fix problems. All their spider text of help options, now always lead back to the return page.
So it's call them (which you can only find the number via Google.)
I suspect they're so disfunctional, that they don't understand why the massive uptick in calls, so then they slap AI in via phone too.
And so now that's slow and AI drivel. I guess soon I'll just have to do chargebacks!? Eg, if a package is missing or whatever.
Interesting, I regularly use chat-based support on amazon.ca to speak with (what I presume is) a real human after none of the control flow paths adequately resolve my issue. I've always found the support quick to reply and very helpful.
Granted, it's been 1-2 weeks since I had an issue, so it may have changed since then, or it could be only released to a subset of users.
Amazon is generally good at 1) resolving an issue in your favor and 2) getting you to a human if needed but gosh does it feel like I've taken a different path to do so every single time I'ever needed support.
The expectation of customer support lines is that customers want to speak to humans. It isn't just the fact that these are semantics that aren't written anywhere and are open to change, because by using a human-like voice agent on a customer support line, you are pretending that that is a human, which is a scam or fraud.
If you really believe that the support can be good, then use a robotic text to speech, don't pretend it's a human. And make it clear to users that they are talking to a human, phone is a protocol that has the semantic that you speak to a human. Use something else.
The bottom line is that you have clients that registered under the belief that they could call a phone number and speak to a human, businesses are performing a short-term switcheroo at the expense of their clients, it's a scam.
> The expectation of customer support lines is that customers want to speak to humans.
Not really. The expectation is to be able to express their need in a natural language, maybe because their issue is not covered by a fixed-form web form (pun not intended).
This might be good for Back-office hands-free tool access, for employees who are on the road. (they shouldn't be looking at the screen, and they might be limited to voice calling due to coverage issues besides). Aka: really weird terminal.
It is funny you mention Microsoft s customer support because it is a publicly known issue at this point that I'd you are a Microsoft employee or a v dash, the first level of support you talk to is basically something you have to overcome to get any help at all.
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.
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.
I hate those, too. Especially when others are around.
The interface is so inconsistent between different implementations that they're always terribly awkward to navigate at best, and completely infuriating at worst. I don't like presenting the image of an progressively-angrier man who is standing around and speaking incongruous short phrases that are clearly directed towards nobody at all.
But I've found that many of them still accept DTMF. Just mash a button instead of utter a response, and a more-traditional IVR tree shows up with a spoken list of enumerated options. Things get a lot better after that.
Like pushing buttons at the gas pump to try to silence the ad-roll, it's pretty low-cost to try.
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.
The problem here is that if it's something a voice assistant can solve, I can solve it from my account. I'm calling because I need to speak to an actual human.
Im in this business, and used to think the same. It turns out this is a minority of callers. Some examples:
- a client were working does advertising in TV commercials, and a few percent of their calls is people trying to cancel their TV subscriptions, even though they are in healthcare
- in the troubleshooting flow for a client with a physical product, 40% of calls are resolved after the “did you try turning it off and on again” step.
- a health insurance client has 25% of call volume for something that is available self-service (and very visible as well), yet people still call.
- a client in the travel space gets a lot of calls about: “does my accommodation include X”, and employees just use their public website to answer those questions. (I.e., it’s clearly available for self-service)
One of the things we tend to prioritize in the initial conversation is to determine in which segment you fall and route accordingly.
(reposting because something ate your newlines, I've added comments in line)
Im in this business, and used to think the same. It turns out this is a minority of callers. Some examples:
- a client were working does advertising in TV commercials, and a few percent of their calls is people trying to cancel their TV subscriptions, even though they are in healthcare
I guess these are probably desperate people who are trying to get to someone, anyone. In my opinion, the best thing people can do is get a really good credit card and do a charge back for things like this.
- in the troubleshooting flow for a client with a physical product, 40% of calls are resolved after the “did you try turning it off and on again” step.
I bought a Chinese wifi mesh router and it literally finds a time between two am and five am and reboots itself every night, by default. You can turn this behavior off but it was interesting that it does this by default.
- a health insurance client has 25% of call volume for something that is available self-service (and very visible as well), yet people still call.
In my defense, I've been on the other side of this. I try to avoid calling but whenever I use self service, it feels like ny settings never stick and always switch back to what they want the next billing cycle. If I have to waste time each month, you have to waste time each month.
- a client in the travel space gets a lot of calls about: “does my accommodation include X”, and employees just use their public website to answer those questions. (I.e., it’s clearly available for self-service)
These public websites are regularly out of date. Someone who is actually on site confirm that yes, they have non smoking rooms or ice machines that aren't broken is valuable.
One of the things we tend to prioritize in the initial conversation is to determine in which segment you fall and route accordingly.
Independent of any feelings about the use of AI, I find that specific style of formatting to be extremely visually distracting and tend to click away because of that. Emoji, imo, are very information dense per character so it makes the rest of the info hard to parse.
When I see this style first thing that comes to mind is that the whole text was generated and maybe not even read by the author. And I am not yet confident to trust AI in writing the docs without supervision. So I have troubles in trusting the whole thing I see because of that.
Yep, and the number of commits is insane. In early commits there are cursor rules and reports about task complexity made by AI. So it's really interesting, how was the project created.
Yes, developers on my teams have started submitting PRs exactly like this and the content of the PR is similar. Still need to figure out how to put a stop to it.
Long shot, if anyone here is an Asterisk wizard. I would like to correlate CDRs to voicemail recording locations. I am building an integrated dashboard for call recordings, and want voicemails to be included, but that's been surprisingly difficult.
If you are using AGI or ARI, you can log it somewhere useful so you can correlate later.
If you are using a more vanilla configuration I’d say use the voicemail metadata .txt file that will be in the same folder as the recording to get info to find the CDR. It has things like callerid, origmailbox, origdate (or maybe it’s origtime), and duration. origmailbox should match the CDR destination and the orig time should also match. Haven’t done this specifically. But, I’m hoping I’m pointing you in the right direction.
I work with Freeswitch almost exclusively these days. But, my first experience with VoIP was Asterisk and a huge Perl AGI file keeping everyone talking to each other. Those were good time!
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.
I've generally observed latency of 500ms to 1s with modern LLM-based voice agents making real calls. That's good enough to have real conversations.
I attended VAPI Con earlier this year, and a lot of the discussion centered on how interruptions and turn detection are the next frontier in making voice agents smoother conversationalists. Knowing when to speak is a hard problem even for humans, but when you listen to a lot of voice agent calls, the friction point right now tends to be either interrupting too often or waiting too long to respond.
The major players are clearly working on this. Deepgram announced a new SOTA (Flux) for turn detection at the conference. Feels like an area where we'll see even more progress in the next year.
I think interruptions had better be the top priority. I find text LLMs rage inducing with their BS verbiage that takes multiple prompts to reduce, and they still break promises like one sentence by dropping punctuation. I can't imagine a world where I have to listen to one of these things.
I wonder if it’s possible to do the apple trick of hiding latency using animations. The audio equivalent can be the chime that Siri does after receiving a request.
Been experimenting with having a local Home Assistant agent include a qwen 0.5B model to provide a quick response to indicate that the agent is "thinking" about the request. It seems to work ok for the use case, but it feels like it'd get really repetitive for a 2 way conversation. Another way to handle this would be to have the small model provide the first 3-5 words of a (non-commital) response and feed that in as part of the prompt to the larger model.
From my personal experience building a few AI IVR demos with Asterisk in early 2025, testing STT/TTS/inference products from a handful of different vendors, a reliable maximum latency of 2-3 seconds sounds like a definite improvement. Just a year ago I saw times from 3 to 8 seconds even on short inputs rendering short outputs. One half of this is of course over-committed resources. But clearly the executional performance of these models is improving.
Very randomly and personally I appear to have experimented with that few months ago, based on a Japanese advent calendar project[1] - the code is all over the place and only works with Japanese speeches, but the gist is as follows. Also in [2].
The trick is to NOT wait for the LLM to finish talking, but:
1 at end of user VAD, call LLM, stream response into a buffer(simple enough)
2 chunk the response at [commas, periods, newlines], and queue sentence-oid texts
3 pipe queued sentence-oid fragments into a fast classical TTS and queue audio snippets
4 play queued sentence-oid-audio-snippets, maintaining correspondence of consumed audio and text
5 at user VAD, stop and clear everything everywhere, undoing queued unplayed voice, nuking unplayed text from chat log
6 at end of user VAD, feed the amended transcripts that are canonical to user's ears to step 1
7 (make sure to parallelize it all)
This flow (hypothetically)allow such interactions as:
user: "what's the date today"
sys: "[today][is thursday], [decem"
user: "sorry yesterday"
sys: "[...uh,][wednesday?][Usually?]"
1: https://developers.cyberagent.co.jp/blog/archives/44592/
2: https://gist.github.com/numpad0/18ae612675688eeccd3af5eabcfdf686
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/
Yes DO let you handle long lived websocket connections.
I think this is unique to Cloudflare. AWS or Google Cloud don't seem to offer these things (statefulness basically).
Same with TTS: some like Deepgram and ElevenLabs let you stream the LLM text (or chunks per sentence) over their websocket API, making your Voice AI bot really really low latency.
The integrated developer experience is much better on Vapi, etc.
The goal of the Pipecat project is to provide state of the art building blocks if you want to control every part of the multimodal, realtime agent processing flow and tech stack. There are thousands of companies with Pipecat voice agents deployed at scale in production, including some of the world's largest e-commerce, financial services, and healthtech companies. The Smart Turn model benchmarks better than any of the proprietary turn detection models. Companies like Modal have great info about how to build agents with sub-second voice-to-voice latency.[1] Most of the next-generation video avatar companies are building on Pipecat.[2] NVIDIA built the ACE Controller robot operating system on Pipecat.[3]
I developed a stack on Cloudflare workers where latency is super low and it is cheap to run at scale thanks to Cloudflare pricing.
Runs at around 50 cents per hour using AssemblyAI or Deepgram as the STT, Gemini Flash as LLM and InWorld.ai as the TTS (for me it’s on par with ElevenLabs and super fast)
I am not using speech to speech APIs like OpenAI, but it would be easy to swap the STT + LLM + TTS to using Realtime (or Gemini Live API for that matter).
OpenAI realtime voices are really bad though, so you can also configure your session to accept AUDIO and output TEXT, and then use any TTS provider (like ElevenLabs or InWord.ai, my favorite for cost) so generate the audio.
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.
I assume it's to make it seem like an actual call center rather than a scam. I recently got two phone scam attempts (credit card related) that sounded exactly like this.
I built a voice AI stack and background noise can be really helpful to a restaurant AI for example. Italian background music or cafe background is part of the brand. It’s not meant to make the caller believe this is not a bot but only to make the AI call on brand.
You can call it what ever you like, but to me this is deceptive.
Where is the difference between this and Indian support staff pretending to be in your vicinity by telling you about the local weather? Your version is arguably even worse because it can plausibly fool people more competently.
It doesn't have to be. You can configure your bot to great the user.
E.g. "Aleksandra is not available at the moment, but I'm her AI assistant to help you book a table. How may I help you?"
So you're telling the caller that it is an AI, and yet you can have a pleasant background audio experience.
Also, it only takes one legitimate collect call from a jail from a loved one and now I'm all in favor of reform in our jail system.
No, it does not cost over thirty dollars to allow someone accused to call their loved ones. We pay taxes. I want my government to use the taxes and provide these calls for free.
Nice to see Asterisk on the home page of HN. It’s been a while…
Even if the focus is now on hosted telephony, my experience is that everywhere you can hear the default nusic-on-hold
I don't mind music-on-hold as much except when they break with a human voice at intervals saying inane things such as "your call is important to us. Thank you for holding" Which makes me think the call has been answered. If there's not actual call queue information, just play music so I can ignore it and continue working without that NOP interrupt.
I guess the comment was just about how much Asterisk deployments are out there because you can often hear its default music-on-hold? But maybe I'm wrong.
thats funny, i interpreted this as "Hosted Asterisk People Sell a Default Experience" (and probably charge for custom messages) so its cool to see something different and marketable
What is the application of this that makes anything better for anyone? All I can think of is more spammers, scammers, horrible customer support lines.
My local dealership adopted one of these for their service department. Prior to the AI assistant, you would call and immediately be placed on hold because the same people serving customers at the desk were answering the phone. The AI picks up right away and can schedule an oil change. It's fantastic and I'd love to see more of this. Of course it also has the ability to escalate to a human for the things it doesn't have capabilities for.
For narrow use cases like this I personally don't mind these tools.
If they have the ability to hook an llm up to a system that can schedule an oil change why can’t they provide a form on their website to do the same thing and save everyone the hassle?
Just ask your LLM to call the dealership. The only downside is spoken word is a bit slow for computers. Maybe we can even work out a protocol where the LLM voices talk faster and faster until they can't hear tokens clearly
At that point we’ll have to convert the voices into a form more amenable to machine to machine communication. Perhaps a system based on high and low signals.
Seriously what is the point of all this.
Pretty sure rebelgecko was using [Sarcasm] in order to increase his [Satire] enjoyment
Some people just like to call over navigate to a site and fill out a form. Sometimes just speaking is easier.
Both can be true. They might have those web forms, while also having enough customers that prefer phone calls to justify it.
Not everyone wants to use a form on their website?
You and I certainly do, but a ton of people prefer calling on the phone.
In Brazil, multiple companies are offering a call and WhatsApp, both through automated messages with menus and in the end escalate to humans.
They do, via the manufacturer's app. It works fine as well.
Situational context matters though, sometimes you get in the vehicle and get the alert. Just say "Hey Siri, call dealership" and away you go hands free. No messing with apps.
They do offer the ability to schedule an oil change via the website and yet some people still prefer to call. User preference and multi-channel servicing options are nice to support
They do? How do you know?
Unsure about whether the specific dealership in question supports online booking, but there existing consumers whose preference is for a phone call over a web-based experience is definitely the case, at least in the US.
For example, even with the (digital-only) SAAS company I work at, we have a non-trivial amount of customers who with strong preferences to talk on the phone, ex to provide their credit card number, rather than enter it in the product. This is likely more pronounced if your product serves less tech-savvy niches.
That said, a strong preference for human call > website use doesn't necessarily imply even a weak preference for AI call > website use (likely customer-dependent, but I'd be surprised if the number with that preference was exactly 0)
how about the plainly obvious fact that every call tree system first spends 1-8 minutes going through all the things that you can actually do on the website instead of calling: do you really think they would bother with that if people aren’t calling about stuff that is easily done on the website? sure, we all agree that it is partly designed to get people to hang up in disgust and give up, but that is an obviously insufficient explanation compared to the simpler and more comprehensive explanation that people simply do, as a matter of fact, prefer to use the phone despite it being clearly less useful for easily-computer-able tasks.
>sure, we all agree that it is partly designed to get people to hang up in disgust and give up
actually, as someone who works in this area - no, it's not. it designed to help people to do things and metrics of success are closely monitored
It is often both.
not in my experience and it will be more expensive to company
Have you never worked in customer service?
because a lot of people still prefer voice communication over navigating the internet and filling out a form
Good customer support lines? Is there a reason why it can't provide good support. I often use chatgpt's voice function.
How? Businesses will use this to justify removing what few actual human support staff they have left. Nobody, and I mean it, nobody calls customer support because they want to talk to a computer. It’s the last resort for problems that usually can’t be accomplished via the already existing technical flows available via computer.
That's not true. I recently called to make an appointment. I don't care if it's an AI. I would actually prefer it, because I wouldn't feel bad about taking a long time to pick the best time. Don't you think you're being a bit dogmatic about this?
I have to feel that an online booking system is substantially lower tech than an ai voice assitant chatbot, and makes it even easier to ruminate as you pick the time that works for you.
In my case, the business did have human support assistants, but didn't do reservations via the phone. I had to switch to the web app for that, which was annoying (I was driving?). I guess doing user identification over the phone and scheduling the appointment are time-consuming for the human assistant, while these are some of the few things an app can do well. I presume the logic is to preserve human assistants for actually complicated or dynamic assistance, for the sake of cost-efficiency. A voice llm can bring down the cost of these basic-but-time-consuming interactions.
Beyond true.
I wonder what Amazon's goals are, as an example. Currently, at least on the .ca website, there is no way to even get to chat to fix problems. All their spider text of help options, now always lead back to the return page.
So it's call them (which you can only find the number via Google.)
I suspect they're so disfunctional, that they don't understand why the massive uptick in calls, so then they slap AI in via phone too.
And so now that's slow and AI drivel. I guess soon I'll just have to do chargebacks!? Eg, if a package is missing or whatever.
Interesting, I regularly use chat-based support on amazon.ca to speak with (what I presume is) a real human after none of the control flow paths adequately resolve my issue. I've always found the support quick to reply and very helpful.
Granted, it's been 1-2 weeks since I had an issue, so it may have changed since then, or it could be only released to a subset of users.
Amazon is generally good at 1) resolving an issue in your favor and 2) getting you to a human if needed but gosh does it feel like I've taken a different path to do so every single time I'ever needed support.
I wonder if I'm stuck on the (A)wseome/(B)ad side of A/B testing.
The expectation of customer support lines is that customers want to speak to humans. It isn't just the fact that these are semantics that aren't written anywhere and are open to change, because by using a human-like voice agent on a customer support line, you are pretending that that is a human, which is a scam or fraud.
If you really believe that the support can be good, then use a robotic text to speech, don't pretend it's a human. And make it clear to users that they are talking to a human, phone is a protocol that has the semantic that you speak to a human. Use something else.
The bottom line is that you have clients that registered under the belief that they could call a phone number and speak to a human, businesses are performing a short-term switcheroo at the expense of their clients, it's a scam.
> The expectation of customer support lines is that customers want to speak to humans.
Not really. The expectation is to be able to express their need in a natural language, maybe because their issue is not covered by a fixed-form web form (pun not intended).
So yeah AI might be a good fit in that scenario.
It's a protocol and network that has backwards compatibility with 19th century telegram wire networks that later were voice lines for a full century.
If that isn't the channel to speak to a human, nothing is. You can speak to a bot with an app or whatever.
At least make it sound robotty instead of pretending to be a human.
This might be good for Back-office hands-free tool access, for employees who are on the road. (they shouldn't be looking at the screen, and they might be limited to voice calling due to coverage issues besides). Aka: really weird terminal.
> What is the application of this?
spammers, scammers and horrible customer support lines.
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It is funny you mention Microsoft s customer support because it is a publicly known issue at this point that I'd you are a Microsoft employee or a v dash, the first level of support you talk to is basically something you have to overcome to get any help at all.
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.
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.
I hate those, too. Especially when others are around.
The interface is so inconsistent between different implementations that they're always terribly awkward to navigate at best, and completely infuriating at worst. I don't like presenting the image of an progressively-angrier man who is standing around and speaking incongruous short phrases that are clearly directed towards nobody at all.
But I've found that many of them still accept DTMF. Just mash a button instead of utter a response, and a more-traditional IVR tree shows up with a spoken list of enumerated options. Things get a lot better after that.
Like pushing buttons at the gas pump to try to silence the ad-roll, it's pretty low-cost to try.
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.
What if the goal is to keep gaslighting you until you give up your demands?
Most voice agents for large companies are a calculated game to deter customers from expensive humans as we know, but not always.
Sort of like how Jira can be a streamlined tool or a prison of 50-step workflows, it's all up to the designer.
you bought something from the wrong company, and you arent gonna get helped by phone, bot, or person
The problem here is that if it's something a voice assistant can solve, I can solve it from my account. I'm calling because I need to speak to an actual human.
Im in this business, and used to think the same. It turns out this is a minority of callers. Some examples:
- a client were working does advertising in TV commercials, and a few percent of their calls is people trying to cancel their TV subscriptions, even though they are in healthcare - in the troubleshooting flow for a client with a physical product, 40% of calls are resolved after the “did you try turning it off and on again” step. - a health insurance client has 25% of call volume for something that is available self-service (and very visible as well), yet people still call. - a client in the travel space gets a lot of calls about: “does my accommodation include X”, and employees just use their public website to answer those questions. (I.e., it’s clearly available for self-service)
One of the things we tend to prioritize in the initial conversation is to determine in which segment you fall and route accordingly.
(reposting because something ate your newlines, I've added comments in line)
Im in this business, and used to think the same. It turns out this is a minority of callers. Some examples:
- a client were working does advertising in TV commercials, and a few percent of their calls is people trying to cancel their TV subscriptions, even though they are in healthcare
I guess these are probably desperate people who are trying to get to someone, anyone. In my opinion, the best thing people can do is get a really good credit card and do a charge back for things like this.
- in the troubleshooting flow for a client with a physical product, 40% of calls are resolved after the “did you try turning it off and on again” step.
I bought a Chinese wifi mesh router and it literally finds a time between two am and five am and reboots itself every night, by default. You can turn this behavior off but it was interesting that it does this by default.
- a health insurance client has 25% of call volume for something that is available self-service (and very visible as well), yet people still call.
In my defense, I've been on the other side of this. I try to avoid calling but whenever I use self service, it feels like ny settings never stick and always switch back to what they want the next billing cycle. If I have to waste time each month, you have to waste time each month.
- a client in the travel space gets a lot of calls about: “does my accommodation include X”, and employees just use their public website to answer those questions. (I.e., it’s clearly available for self-service)
These public websites are regularly out of date. Someone who is actually on site confirm that yes, they have non smoking rooms or ice machines that aren't broken is valuable.
One of the things we tend to prioritize in the initial conversation is to determine in which segment you fall and route accordingly.
Thx, forgot to double enter.
Well, the future is here: https://www.youtube.com/watch?v=HbDnxzrbxn4
Looked at a repo and it seems this project was heavily AI generated. Would be interesting to hear from the author of the project how it was built.
> Looked at a repo and it seems this project was heavily AI generated
That's the first thing that I noticed too.
It's gotten to the point that my body subconsciously rejects bullet lists and headings that start with emojis.
Independent of any feelings about the use of AI, I find that specific style of formatting to be extremely visually distracting and tend to click away because of that. Emoji, imo, are very information dense per character so it makes the rest of the info hard to parse.
When I see this style first thing that comes to mind is that the whole text was generated and maybe not even read by the author. And I am not yet confident to trust AI in writing the docs without supervision. So I have troubles in trusting the whole thing I see because of that.
That's also a totally fair take!
Yep, and the number of commits is insane. In early commits there are cursor rules and reports about task complexity made by AI. So it's really interesting, how was the project created.
Yes, developers on my teams have started submitting PRs exactly like this and the content of the PR is similar. Still need to figure out how to put a stop to it.
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Long shot, if anyone here is an Asterisk wizard. I would like to correlate CDRs to voicemail recording locations. I am building an integrated dashboard for call recordings, and want voicemails to be included, but that's been surprisingly difficult.
So, there is no straight forward way that I can think of. But, what I would do is set a channel variable and log it somewhere:
exten => s,n,Set(VM_UNIQUEID=${UNIQUEID}) exten => s,n,VoiceMail(${EXTEN}@default)
If you are using AGI or ARI, you can log it somewhere useful so you can correlate later.
If you are using a more vanilla configuration I’d say use the voicemail metadata .txt file that will be in the same folder as the recording to get info to find the CDR. It has things like callerid, origmailbox, origdate (or maybe it’s origtime), and duration. origmailbox should match the CDR destination and the orig time should also match. Haven’t done this specifically. But, I’m hoping I’m pointing you in the right direction.
I work with Freeswitch almost exclusively these days. But, my first experience with VoIP was Asterisk and a huge Perl AGI file keeping everyone talking to each other. Those were good time!
You are awesome!
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.
Is that really where SOTA is right now?
I've generally observed latency of 500ms to 1s with modern LLM-based voice agents making real calls. That's good enough to have real conversations.
I attended VAPI Con earlier this year, and a lot of the discussion centered on how interruptions and turn detection are the next frontier in making voice agents smoother conversationalists. Knowing when to speak is a hard problem even for humans, but when you listen to a lot of voice agent calls, the friction point right now tends to be either interrupting too often or waiting too long to respond.
The major players are clearly working on this. Deepgram announced a new SOTA (Flux) for turn detection at the conference. Feels like an area where we'll see even more progress in the next year.
I think interruptions had better be the top priority. I find text LLMs rage inducing with their BS verbiage that takes multiple prompts to reduce, and they still break promises like one sentence by dropping punctuation. I can't imagine a world where I have to listen to one of these things.
I wonder if it’s possible to do the apple trick of hiding latency using animations. The audio equivalent can be the chime that Siri does after receiving a request.
Sesame was the fastest model for a bit. Not sure what that team is doing anymore, they kind of went radio silent.
https://app.sesame.com/
Absolutely not.
500-1000ms is borderline acceptable.
Sub-300ms is closer to SOTA.
2000ms or more means people will hang up.
play "Just a second, one moment please <sounds of typing>".wave as soon as input goes quiet.
ChatGPT app has a audio version of the spinner icon when you ask it a question and it needs a second before answering.
I haaaaate the fake typing noises.
Alternate between that and
160ms is essentially optimal and you can get down to about 200ms AFAIK.
With what system?
Been experimenting with having a local Home Assistant agent include a qwen 0.5B model to provide a quick response to indicate that the agent is "thinking" about the request. It seems to work ok for the use case, but it feels like it'd get really repetitive for a 2 way conversation. Another way to handle this would be to have the small model provide the first 3-5 words of a (non-commital) response and feed that in as part of the prompt to the larger model.
From my personal experience building a few AI IVR demos with Asterisk in early 2025, testing STT/TTS/inference products from a handful of different vendors, a reliable maximum latency of 2-3 seconds sounds like a definite improvement. Just a year ago I saw times from 3 to 8 seconds even on short inputs rendering short outputs. One half of this is of course over-committed resources. But clearly the executional performance of these models is improving.
Very randomly and personally I appear to have experimented with that few months ago, based on a Japanese advent calendar project[1] - the code is all over the place and only works with Japanese speeches, but the gist is as follows. Also in [2].
The trick is to NOT wait for the LLM to finish talking, but:
This flow (hypothetically)allow such interactions as:Microsoft Foundry's realtime voice API (which itself is wrapping AI models from the major players) has response times in the milliseconds.
No, there are models with sub-second latency for sure
Just try Gemini Live on your phone. That's state of the art
Perhaps you didnt read that these are "production-ready golden baselines validated for enterprise deployment."
How does their golden nature not dissuade these concerns for you?
I (and most people I ask) definitely don’t answer calls from robots or watch videos with robot voice. I’m not sure what value the customer gets here.
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This opens up new possibilities for interactive phone services. Retro-futuristic for sure.
That seems like bad news for Allison. Though I know she already had some TTS voices available, so many not.
She seems to be doing well
https://m.youtube.com/watch?v=wairnc-2Hyo
I've created Asterisk Codex Skill, but turns out there is ten seconds timeout for scripts
Can I connect this to Twilio
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].
[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/
The problem with PipeCat and LiveKit (the 2 major stacks for building voice ai) is the deployment at scale.
That’s why I created a stack entirely in Cloudflare workers and durable objects in JavaScript.
Providers like AssemblyAI and Deepgram now integrate VAD in their realtime API so our voice AI only need networking (no CPU anymore).
let me get this straight, you are storing convo threads / context in DOs?
e.g. Deepgram (STT) via websocket -> DO -> LLM API -> TTS?
Yes DO let you handle long lived websocket connections. I think this is unique to Cloudflare. AWS or Google Cloud don't seem to offer these things (statefulness basically).
Same with TTS: some like Deepgram and ElevenLabs let you stream the LLM text (or chunks per sentence) over their websocket API, making your Voice AI bot really really low latency.
This is good stuff.
In your opinion, how close is Pipecat + OSS to replacing proprietary infra from Vapi, Retell, Sierra, etc?
It depends on what you mean by replacing.
The integrated developer experience is much better on Vapi, etc.
The goal of the Pipecat project is to provide state of the art building blocks if you want to control every part of the multimodal, realtime agent processing flow and tech stack. There are thousands of companies with Pipecat voice agents deployed at scale in production, including some of the world's largest e-commerce, financial services, and healthtech companies. The Smart Turn model benchmarks better than any of the proprietary turn detection models. Companies like Modal have great info about how to build agents with sub-second voice-to-voice latency.[1] Most of the next-generation video avatar companies are building on Pipecat.[2] NVIDIA built the ACE Controller robot operating system on Pipecat.[3]
[1] https://modal.com/blog/low-latency-voice-bot - [2] https://lemonslice.com/ = [3] https://github.com/NVIDIA/ace-controller/
Is there a simple, serverless version of deploying Pipecat stack, without: - me having to self host on my infra
I just want to provide: - business logic - tools - configuration metadata (e.g. which voice to use)
I don't like Vapi due to 1) extensive GUI driven experience, 2) cost
Check out something like LayerCode (Cloudflare based).
Or PipeCat Cloud / LiveKit cloud (I think they charge 1 cent per minute?)
I developed a stack on Cloudflare workers where latency is super low and it is cheap to run at scale thanks to Cloudflare pricing.
Runs at around 50 cents per hour using AssemblyAI or Deepgram as the STT, Gemini Flash as LLM and InWorld.ai as the TTS (for me it’s on par with ElevenLabs and super fast)
Is AssemblyAI or Deepgram compatible with OpenAI Realtime API, esp. around voice activity detection and turn taking? How do you implement those?
I am not using speech to speech APIs like OpenAI, but it would be easy to swap the STT + LLM + TTS to using Realtime (or Gemini Live API for that matter).
OpenAI realtime voices are really bad though, so you can also configure your session to accept AUDIO and output TEXT, and then use any TTS provider (like ElevenLabs or InWord.ai, my favorite for cost) so generate the audio.
Do you have anything written up about how you're doing this? Curious to learn more...
I don't but I should open source this code. I was trying to sell to OEM though, that's why. Are you interested in licensing it?
Technically yes, twilio has sip trunks.
I welcome the spam calls from our asterisk overlords.
I was more thinking I could add it to my Asterisk server to honey-pot the spam callers into an infinite time waster cycle.
"Hello, this is Lenny" - well known Asterisk configuration from 20 years ago.
And, “They have been carried away by monkeys!”
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 the background noise real, or is it also AI-generated to make you think that it's a human?
The background noise is a recording for sure, no AI needed, just a background noise audiofile in a loop would do.
Why though? It adds nothing positive, it only makes me sure it is a scam call.
I assume it's to make it seem like an actual call center rather than a scam. I recently got two phone scam attempts (credit card related) that sounded exactly like this.
I built a voice AI stack and background noise can be really helpful to a restaurant AI for example. Italian background music or cafe background is part of the brand. It’s not meant to make the caller believe this is not a bot but only to make the AI call on brand.
You can call it what ever you like, but to me this is deceptive.
Where is the difference between this and Indian support staff pretending to be in your vicinity by telling you about the local weather? Your version is arguably even worse because it can plausibly fool people more competently.
It doesn't have to be. You can configure your bot to great the user. E.g. "Aleksandra is not available at the moment, but I'm her AI assistant to help you book a table. How may I help you?"
So you're telling the caller that it is an AI, and yet you can have a pleasant background audio experience.
you actually answer unknown callers?
Yes. I own a business.
Also, it only takes one legitimate collect call from a jail from a loved one and now I'm all in favor of reform in our jail system.
No, it does not cost over thirty dollars to allow someone accused to call their loved ones. We pay taxes. I want my government to use the taxes and provide these calls for free.
Yes. Sometimes it's a legit call. Not often, though.
Example of legit calls: the pizza delivery guy decided to call my phone instead of ringing the bell, for whatever reason.
I worked door dash for a couple of days and there were multiple people who wrote in all caps to not ring the door bell. Why? I have no idea.
Probably because it make their dogs go nuts.
Sleeping children or shift workers, too.