Concepts / Algorithms for recognising words in the Time-Domain I'm currently working on a project that involves in Speech and recognising Phonemes (in kind of real-time). 

The current algorithm works by always listening for input from the Mic, and input that is above a specific threshold then this is recorded to a .wav file and sent to the server for processing. E.g.

listening...
listening...
listening.. (max &gt; threshold)
recording..
recording..
etc..


What I want to do is therefore have it recording when a specific name has been said. Someone basically speaks to it.. I.e. (let's assume it's called iris) so the algorithm would therefore work like the following:

listening...
listening..
listening.. (max &gt; threshold)
  // determine if the input is "iris"
  // if true: 
     begin recording the sentence 
  // else:
listening..


I want to do this in the time-domain, then, process the sentences in the frequency domain. I've read an article, and, a paper that describes this process using Total number of Zero-crossings (using a specific threshold) my questions is whether or not this would be a good measure? I only need to identify one word, that is "Iris" and then everything else can be done using algorithms such as: MFCC, HMM's etc.. 

Any ideas? :)
I highly doubt that something as complex as recognizing a word can be done directly in the time domain using features as basic as zero-crossing rate.