The text should be as close as possible to the kind of text the recognizer is supposed to decode. Typically, it comes in the form of transcriptions of speech samples collected in some task scenario close to the envisioned application of the speech recognition system.
Case is important.
Usually, one can get quite some improvment by carefully examining the transcriptions and applying some normalizations. This may be necessary, if the transcription is sloppy, or there are certain things, which need to be modeled seperately, e.g. noises or dialectic variants of words. Most of the boring basic work for each task is done here. Given a text, a vocabulary must be defined. An easy and close to optimal way is to select the most common words in the corpus.