Integrating voice commands into a Java application has been a traditionally daunting task. While JDK provides a Speech API, it is unfortunately only an interface to a collection of outdated products and third-party cloud providers. Let's leave all this behind and add some modern, offline speech recognition to our Java application. By keeping it offline we can ensure our user's data is kept on-device, thereby prioritizing their privacy and security. The Picovoice SDK provides a class that encapsulates both the Porcupine wake word engine and the Rhino Speech-to-Intent engine.

As part of my project I need to implement offline speech recognition in a Raspberry Pi 3. Doing some research I have found the CMUSphinx project (http://cmusphinx.sourceforge.net/wiki/tutorial) I tried it for simple command and control and it is awesome, however, when I move to real conversations, I found it to perform very bad. I have a small corpus of about 500K utterances, and trained ARPA models with it. With some parameter tuning I can get some improvement but very far from good. Notice that I am using the pre-packaged acoustic models and I am just tinkering with the language models.