I worked on Sphinx 3 a lot. In these days, it was generally regarded as an "old-style" recognizer as compared to Sphinx 4 and PocketSphinx. It is also not support officially by the SF's guys.
Coders of speech recognition think a little bit different. They usually stick to a certain codebase which they feel comfortable with. For me, it is not just a personal preference, it also reflects how much I know about a certain recognizer. For example, I know quite a bit of how Sphinx 3 performs. In these days, I tried to learn how Sphinx 4 fare as well. So far, if you ask me to choose an accurate recognizer, I will still probably choose Sphinx 3, not because the search technology is better (Sphinx 4 is way superior), but because it can easily made to support several advanced modeling types. This seems to be how the 2010 developer meeting concluded as well.
But that was just me. In fact, I am bullish on all Sphinx recognizers. One thing I want to note is the power of Sphinx 4 in development. There are many projects are based on Sphinx 4. In these days, if you want to get a job on speech recognizer, knowing Sphinx 4 is probably a good ticket. That's why I am quite keen on learning it more so hopefully I can write on both recognizers more.
In any case, this is a Sphinx 3's article. I will probably write more on each components. Feel free to comments.
How Sphinx3 is initialized:
-> kbcore_init (*)
-> set operation mode
-> Look for feat.params very early on.
-> s3_am_init (*)
-> misc. models init
mgau_init such as
-> dict2pid_build <- Should put into search
-> read in mdef.
-> depends on -senmgau type
.semi or .s3cont.
- -hmmdir override all other sub-parameters.