Voice Recognition - Android

VDK features three different ASR libraries: CSDK, TNL and our very own: VASR.

Basics

You will need to manipulate 2 concepts: Recognizers & Models. Both need to be conﬁgured but ﬁrst let's explain who's who.

Models are fed to the Recognizer and describe the range of words and utterances that can be recognized. They will either be pre-compiled by the provider (like “free speech” models), or compiled from a grammar that you've written beforehand in the VDK Studio.

There are 3 types of models:

Type	Description
static	Static models embed all possible vocabulary inside a single ﬁle or folder.
dynamic	Dynamic models have “holes” where you can plug new vocabulary at runtime. These need to be prepared and compiled at runtime before installing it on a recognizer.
free-speech	Free-Speech models are very large vocabulary static models. They often require additional ﬁles and are not supported by all engines.

Conﬁguration

Each engine has its own conﬁguration quirks and tweaks, but here is a common (though incomplete) pattern using VSDK-CSDK, which supports all 3 types of models:

JSON

{
    "version": "2.0",
    "csdk": {
        "paths": {
            "data_root": "../data"
        },
        "asr": {
            "recognizers": {
                "rec": { ... }
            },
            "models": {
                "static_example": {
                    "type": "static",
                    "file": "<model_name>.fcf"
                },
                "dynamic_example": {
                    "type": "dynamic",
                    "file": "<base_model_name>.fcf",
                    "slots": {
                    "firstname": { ... },
                    "lastname": { ... }
                },
                ...
                },
                "free-speech_example": {
                    "type": "free-speech",
                    "file": "<base_model_name>.fcf",
                    "extra_models": { ... }
                }
            }
        }
    }
}

Starting the engine

JAVA

com.vivoka.vsdk.Vsdk.init(mContext, "config/main.json", vsdkSuccess -> {
    if (vsdkSuccess)
    {
        com.vivoka.csdk.asr.Engine.getInstance().init(mContext, engineSuccess -> {
            if (engineSuccess)
            {
                // at this point the AsrEngine has been correctly initialized
            }
        });
    }
});

You can't create two separate instances of the same engine! Attempting to create a second one will get you another pointer to the existing engine.

Each engine has its own conﬁguration document, check it out for further details, as well as the ASR samples to get started with actual, production-ready code.

Creating a Recognizer

JAVA

// First you have to create a recognizer listener to subscribe to the recognizer events
IRecognizerListener recognizerListener = new IRecognizerListener()
{
    @Override
    public void onEvent(RecognizerEventCode eventCode, int timeMarker, String message) {}

    @Override
    public void onResult(String result, RecognizerResultType resultType, boolean isFinal) {}

    @Override
    public void onError(RecognizerErrorCode error, String message) {}

    @Override
    public void onWarning(RecognizerErrorCode error, String message) {}
};

// Then you can create a recognizer
recognizer = Engine.getInstance().makeRecognizer("rec", recognizerListener);

And ﬁnally, apply a model to actually recognize vocabulary:

JAVA

recognizer.setModel("static_example"); // same call whether the model is static, dynamic or free- speech!

Also, don't forget to insert it in the pipeline or nothing's going to happen by itself:

JAVA

pipeline.pushBackConsumer(recognizer);

Dynamic Models

Only dynamic models need to be manipulated explicitely to add the missing data at runtime:

JAVA

DynamicModel model = Engine.getInstance().getDynamicModel("dynamic_example");
model.addData("firstname", "André");
model.addData("lastname", "Lemoine");
model.compile();

// We can now apply it to a recognizer!
recognizer.setModel("dynamic_example");