Hi,
I'm trying to implement a speech recognizer client using Sphinx II, my goal is to have the someone reading a written sentence in a text and have a confidence score for each word.
So for that I'm using Finite State Grammars and limited dictionary.
I got something working, but the confidence score are very low (< 0.30). I'm using the same settings as the simple Reco example of Sphinx 2.
Since there is only one possibility for each word pronounced (each word is one state in the grammar), I should normally have high score and time efficient recognition, but the hypothesis take time to be computed. Also I get the hypothesis as soon as the word as been pronounced.
So now I don't actually know where to go to improve this. Am i using the right solution for this kind of problem? Should I instead use Language Models, and if yes how to restrict the context to a given sentence in a story?
Also do I need to use the sphinx trainer? So far I've generated the language models/dictionary using the web tool.
Your help would be much appreciated. Thanks, Boris Gougeon