Twelve questions, in the order people ask them.
The short answer: old detection listens to how the call sounds, new detection reads what was said. Everything below is that difference, and why it costs money when you get it wrong.
What is answering machine detection, in one sentence?
Software that decides whether a person or a machine answered, before your agent starts talking.
Every dialer has some version of it. The cheap ones do one trick. The expensive ones stack all of them.
How does the old method decide?
It measures sound, in four ways:
| Method | How it decides | Where it breaks |
|---|---|---|
| No detection | Connects every answer | Agents talk to machines all day |
| Beep detection | Listens for the tone | Many networks never send one |
| Greeting length | Long greeting means machine | Short greetings, long hellos |
| Silence pattern | Waits for a gap in speech | People who pause, hold music |
Notice what all four have in common. None of them knows what the person said. They measure timing and tone, then guess.
So why does it get it wrong so often?
Because length and silence do not tell you who answered.
A person who picks up with “Hello, Dave speaking, who is this?” sounds exactly like a long greeting. A voicemail that says “Hi, leave a message” sounds exactly like a short hello. The old method has no way to separate those.
Everyone talks about a slider. What is that?
Because the old method measures one thing, it has one control. Turn it stricter and you hang up on more machines. Turn it looser and you hang up on fewer machines, and on more people.
Here is the part people miss. Both mistakes come from the same measurement. So the slider does not reduce errors. It moves them.
| Short answer | Long answer | |
|---|---|---|
| A person | “Hello?” | “Hello, Dave speaking, who is this?” |
| A machine | “Hi, leave a message.” | “You have reached the office. Please leave a message after the tone.” |
Top right and bottom left are the problem cells. A person with a long, formal greeting looks like a machine. A short voicemail looks like a person.
No setting separates them, because the thing being measured is not the thing that differs. Length is not meaning. Words are meaning.
Which mistake is worse?
Hanging up on a real person, by a wide margin. Roughly thirty times worse.
Take 1,000 answered calls and an error rate of one in ten. That is 100 mistakes each way.
Why is it thirty times worse?
Because one costs a conversation and the other costs an opening.
A lost conversation is about three minutes of talk time. An agent produces roughly thirty minutes of talk per paid hour, so the other thirty minutes go to notes, callbacks and waiting. That means ten paid hours to produce five hours of conversation, which is why 100 lost calls cost about ten agent-hours.
A wasted opening is twelve seconds. One hundred of them is twenty minutes.
Ten agent-hours is roughly $40 in Manila and $180 in Ohio. The wasted openings cost about a dollar.
So most systems are tuned the wrong way round. They protect the agent’s patience because that mistake is loud and annoying, and they pay for the expensive mistake because it is silent.
This is the sentence worth remembering: the call you dropped looks exactly like a no-answer in your report. Same row, same zero. You will never see it.
What does the new method do instead?
It turns the first few seconds into text and reads it. That is the whole trick.
Once you have words, length stops mattering. Once you have words, categories that never existed become possible.
| What answers | Old verdict | What it should be |
|---|---|---|
| A person | human | human |
| Voicemail | machine | voicemail |
| Screening assistant | machine, so it hangs up | a real person is behind it |
| “Please hold while I transfer you” | machine, so it hangs up | wait for the transfer |
| Phone menu | machine | phone menu |
Two right, one right by accident, two wrong.
The two wrong ones are the interesting ones. A screening assistant is a guard standing in front of a live prospect, and the dialer hangs up on the guard. A transfer message is the phone system saying “hold on, I am fetching the person you called”, and the dialer hangs up on that too.
You cannot fix either with a slider, because the old method has no word for “screening assistant”. It only has human and machine.
Is it really just reading words?
Yes. Rules look for phrases — “leave a message”, “you have reached”, “who is calling”, “please hold” — and the first match wins.
There is no mystery in the logic. The hard part is doing it fast and locally, on the same PC that is running the calls.
Does it still get things wrong?
Yes, and here is the list I would want if I were buying.
- It waits about three seconds before your agent speaks. You cannot classify speech you have not heard.
- One-word answers are hard. A bare “Hello?” gives the model almost nothing.
- Phone audio is narrowband. 8 kHz, compressed, often noisy. That limits the input, not the model.
- Accents and rare languages are weaker, especially with the small default model.
- People can sound like voicemail. A receptionist reading a script will do it.
- It uses CPU. On a slow machine, calls queue and classification slows down.
None of that is a reason to keep the slider. All of it is a reason to test before you trust it.
How do I measure my own in twenty minutes?
Do not take a vendor’s accuracy number, mine included. Measure your list.
- Pick 50 numbers you can identify in advance: 20 that a person will answer, 20 that go to voicemail, 10 with a menu.
- Dial them with the detector on.
- Write down four counts: humans connected, voicemails caught, voicemails missed, humans wrongly dropped.
- Look at the last one first. If humans are dropped, the detector is costing you money however good the other three look.
What is bad about Ecsow’s version?
- Three seconds of delay on every answered call, by default. Faster means less to read, and less to read means more guessing.
- It eats CPU. Beep detection runs on almost nothing. This runs a speech model.
- Six workers is the ceiling in the 32-bit build. Beyond that, calls queue.
- Everything is local. No cloud fallback when the machine is busy, and no bigger model unless you install one.
- You can edit the rules, which means you can also break them.
And the biggest one: better detection does not fix a bad list. If most of your numbers are wrong, you now reach voicemail more efficiently. That is not the same as selling more.
Should I turn it on?
If you run five agents and your list is reasonable, yes. The three seconds are annoying for a day and then nobody notices.
If the machine is old, or you dial thirty lines from one desktop, test it at peak first. Queueing calls is worse than a wrong guess.
And if you are still on a dialer whose only control is a slider, at least point the slider the other way. Protect the live person, not the agent’s patience. The wasted opening costs a dollar. The lost call costs a customer.
How to turn it on, and what each setting does is the companion piece. For why saved time matters at all, the talk-time arithmetic is the place to start.
Anything else?
Can it tell a Google screening assistant from voicemail?
Yes. Screening assistants ask who is calling and why, which is a different sentence from a voicemail greeting. Ecsow can play a short recorded reply and wait for the call to be put through.
Does it work on mobile numbers?
Yes, and mobile is where most of the value is. Mobile greetings are short, which was the hardest case for the old duration-based method.
What is the difference between AMD and AI detection?
AMD measures sound: greeting length, beeps, silences. AI detection transcribes the first seconds and reads the words. AMD has two outcomes. This has five.
How long before my agent can speak?
About three seconds by default. That is the cost of listening first. Shorten the initial listen and the agent speaks sooner, but it has read less, so it guesses more.