On 27/10/03 21:57, DUSTIN WILDES wrote:
Does anyone have any recommendations on implementing Answering Machine detection for call generation programs?
There's obviously no nice way of doing this.
If you're doing telemarketing, and you're playing pre-recorded audio, which of course is a nasty thing to do, the algorithm is something like:
1. Dial out. 2. Wait for answer. 3. Start playing audio. 4. If you hear something that sounds like a beep, either hang up and try again later, or stop the audio, pause for two seconds and start playing it again. 5. Hang up when finished playing audio.
Step 4 is accomplished by doing a FFT on the incoming audio into frequency buckets and taking a rolling average of the mean and standard deviation, such that you can detect when a fixed monotone beep occurs at the other end.
How very inefficient. Looking for peaks in the autocorrelation function requires much less compute.
If you don't want to play audio files and wait for beeps, and want to connect real humans to each other, then there's no decent way to do this, as the only difference between humans and arbitrary answering machines is that the answering machines give you a beep prompt to record your message.
Right. Dialogic and others make a big fuss of the super detection algorithms, and quote 90+% accuracy. In the real world they are utterly useless. Call answering just doesn't fall into a sufficient redular patterm.
Regards, Steve
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