Speech Recognizer

In the above given commands we also provide sample audio clips as a guide of how to pronounce them. These audio clips were successfully reognized when passed in the Sphinx-4 recognizer.

Creating the Language Model

The next step is to list the plausible list of ROILA sentences in a text file. Once you have written out the ROILA sentences you can already construct a language model by going to the Language Modelling Tool provided by Sphinx. Upload your sample sentences text file in their tool and it will generate a language model when you press the compile knowledge base button. At this point download the language model file only, it will be a file with a .lm extension (a sample .lm file of the afore mentioned scenario).

Creating the Pronounciation Dictionary

Do not download or use the pronounciation dictionary generated by the Language Modelling Tool, we will go ahead and specify our own pronounciation dictionary which basically would suggest how we want the words to be pronounced. Here is our sample. Sphinx requires every word of the dictionary to be broken down into ARPABET symbols. Most linguists are familiar with the International Phonetic Aplhabet (IPA) standard, ARPABET is basically an ASCII representation of the IPA and a conversion is quite helpful.

For example the word FOSIT in ARPABET would be written as F AA S IH T

Note that by specifying our own dictionary we are provided with the freedom of defining our own pronounciations.

Setting up the XML Configuration file

So now you have two files that are ready and whose paths can be inserted in a configuration XML file that Sphinx uses while recognition is going on. For the afore mentioned scenario you are welcome to use our configuration file. You will have to change the following two paths in the XML file:

The Dictionary configuration
<component name=”dictionary” type=”edu.cmu.sphinx.linguist.dictionary.FastDictionary”>
<property name=”dictionaryPath” value=”file:YOUR .6D FILE PATH”/>

In The Language Model configuration
<component name=”trigramModel” type=”edu.cmu.sphinx.linguist.language.ngram.SimpleNGramModel”>
<property name=”location” value=”file:YOUR .LM FILE PATH”/>

Other than that the file can remain as it is and is hence a standard XML file for ROILA recognition. These three files will now be the crux of the recognition. Note that still no recognition has taken place and to accomplish that we can move towards writing Java code.

Executing speech recognition within Java

Create a normal Java project in Eclipse and use the following sample java code as the heart of your source file. Remember to follow the settings mentioned earlier on this page in reference to adding the relevant .jar files. You should be able to get some recognition going with this, note that the program runs forever with the microphone constantly on listening for input. The result of the recognition is returned as a string which you could use as you desire.

String resultText = result.getBestResultNoFiller();

In addition, there is no parsing being done by Sphinx or by our sample program.You could do some parsing on the result returned by Sphinx and determine if it matches to any of the plausible sentences.

To communicate with a NXT Mindstorms robot we recommend using bluetooth where the recognition result is sent over the bluetooth as bytes. For more details about communicating with your NXT robot we have provided a brief tutorial.