Dragonfire

After approximately 3 years of development, now we are finally ready to release version 1.0 of Dragonfire open-source virtual assistant.

Changelog:

* Post-installation scripts are fixed
* An API implemented
* The project is turned into more of a server-side application although it's continuing to preserve the features of its desktop application aspect
* The package is now Python 3 only
* Universal Python wheel generation disabled
* Basic Analyzer (done in `dragonfire/__init__.py`) is heavily pruned and improved. Now it's purely spaCy based
* Omniscient and Learner classes are refactored
* Learning ability now can store data (that comes from many different Android users) on MySQL database seamlessly
* Gspeech alternative added

The long waited [Mozilla's DeepSpeech](https://github.com/mozilla/DeepSpeech) project finally released a pre-trained model on [Jan 31, 2018](https://github.com/mozilla/DeepSpeech/releases/tag/v0.1.1) and we are proud to announce that Dragonfire is the first virtual assistant project that is successfully integrated Mozilla DeepSpeech into its speech recognition system. By gaining the advantage of DeepSpeech, Dragonfire is now able to understand your words with a much higher success rate ([low WER results](https://hacks.mozilla.org/2017/11/a-journey-to-10-word-error-rate/)).

Changelog:

* Migrated from Kaldi Speech Recognition Toolkit to Mozilla DeepSpeech
* Python3 compatibility improved
* System tray icon is now GTK+ based instead of wxPython

With this release, Dragonfire is stable, reliable and more human-like than ever. Q&A and Learning capabilities are dramatically increased. So you will experience a more natural conversation with her.

Changelog:

* Python3 support added
* Omniscient Q&A Engine success rate is improved by ~40%
* The learning capabilities are improved by including the inverted case
* Wikipedia connection and disambiguation errors are fixed
* Several minor bugs are fixed
* Missing package dependencies are added
* Post-installation scripts are fixed

With the migration to [Kaldi Speech Recognition Toolkit](https://github.com/kaldi-asr/kaldi), Dragonfire is now truly independent from any kind of web service. That means she will be able recognize your speech without the need to an internet access.

Changelog:

* Migrated from PyPI SpeechRecognition package to Kaldi Speech Recognition Toolkit
* Migrated from festival cmu_us_clb_arctic voice to flite slt voice
* Kaldi GStreamer English model is added
* Google Search built-in commands are added
* Several minor bugs are fixed
* A number of experimental(non-functional) scripts are added

This Debian (`.deb`) package is compiled on Ubuntu 16.04. If you face with a problem then please consider to [file an issue](https://github.com/DragonComputer/Dragonfire/issues/new).