2. A method according to claim 1 comprising: devising an error metric which indicates how much a speech block length deviates from the target speech block length; calculating the error value for the speech data in a file; detecting the most significant pause in the speech data; calculating the average error value for the speech blocks on either side of the speech block boundary at the pause and retaining the speech block boundary in the speech data if said average error value is less than the current error value; iteratively detecting the next most significant pause, calculating the average error value for the speech blocks on either side of the speech block boundary at the next most significant pause and retaining the speech block boundary in the speech data if this further reduces the error value.
2. A method according to claim 1 comprising: devising an error metric which indicates how much a speech block length deviates from the target speech block length; calculating the error value for the speech data in a file; detecting the most significant pause in the speech data; calculating the average error value for the speech blocks on either side of the speech block boundary at the pause and retaining the speech block boundary in the speech data if said average error value is less than the current error value; iteratively detecting the next most significant pause, calculating the average error value for the speech blocks on either side of the speech block boundary at the next most significant pause and retaining the speech block boundary in the speech data if this further reduces the error value. 6. A method according to claim 2, wherein the significance of a pause is proportional to the duration of the pause.