Recognition of markes in long audio recording
You can use DTMF tones which are very easily decodable with resonator banks. Brief explanation at http://en.m.wikipedia.org/wiki/Dual-tone_multi-frequency_signaling

If you are in a reverberant room then something like a mobile phone will not put too much energy in it and consequently the recording will not be affected too much by the reverberation. Also, DTMFs are relatively high pitch and would stand out from the background.

There are 16 combinations in a typical keypad but then you can alter symbols (e.g. 1213), possibly in a recording, to build more complex phrases or markers. Altering the symbols quicker than the time constant of the room will reduce the effect of reverberation.

If you are using the starter gun to obtain impulse responses from the room, you can play a sequence in the beginning and just after the end of the recording to roughly identify a particular response but I wouldn't recommend relying on the markers for absolute syncing. You can add a mic close to the gun to obtain the pulse start and end and use the room mics to estimate the dynamics of the room (attack, decay and others)

Hope this helps

Updated part of this answer:

The general idea remains the same, tag a point in time by playing a sound and detect its presence later. The question now is, which sounds and how to detect them. Here is an example using DTMF codes.

1) Get a DTMF generator (for example, a DTMF android app such as this one, https://play.google.com/store/apps/details?id=hu.soska.dtmf&amp;hl=en )

2) In a "clean" (non-reverberant) room, record a sequence of sounds, for example "1928". This is the "tag". Please make sure that each number is keyed in for at least 1 second.

3) In the room under measurement, start your recording. When you want to tag a point, have the "1928" sound reproduced and recorded along with the main recording.

4) Build a filter bank of 8 filters at the DTMF frequencies. The resonators are dead simple filters, here is some example code to get your coefficients: http://lifeorange.com/MATLAB/MATLAB_FD.htm

5) Open the file, run the recording through the filters. Their output will vary depending on the power of the tone in the signal. During the reproduction of DTMF tones, the output of the filters will be increasing. Apply a very simple rule: To maintain a "correct match" you would have to see pairs of filters (representing numbers) going "high" and staying high for at least 1 second. Look for this rule in the outputs of your filters. You now have the matches.

Why single tones and resonators? Because they are very easy and fast to decode.

Alternatives? 

Record a Pseudorandom generator signal at step 4 and use cross correlation for step 5. Cross correlation though will be much slower because it would have to run repeatedly in a "sliding window" fashion (please see http://en.wikipedia.org/wiki/Overlap%E2%80%93add_method).

An alternative for step 5 could be multimon (please see http://manpages.ubuntu.com/manpages/gutsy/man1/multimon.1.html ), but that would not give you the offset.

These are all approximate solutions though, they will not give you a dead accurate point in time that your "event" occurs, only a rough approximation (which also depends from the length of your recording).

Hope this helps.