This demo gives a brief presentation of a program package for continuous speech recognition, which is, so far, successful with small and medium dictionaries. The package  is very large because it contains both modules for training and recognition. Each of these modules consists of several submodules and a variety of classes and functions. It includes two libraries developed in the last two years by the same authors. Those are slib library for digital signal processing and general purpose an_misc library. These are available at  www.alfanum.com. The program package is a product of several years of work on the automatic speech recognition topic, starting from isolated words recognition, through  connected words recognition, to continuous speech recognition using phonemes in context, which this system is based on. Since the system is based on phoneme-in-context recognition, it supports recognition of any set of words (grammar) which needs to be recognized. Changing grammar requires no additional training or speech database recording, but only building of a new trellis, which does not take more than a few seconds. The entire program is written in C++ programming language, it is fully developed by the authors, which means that it does not rely on any third party specialized library. Software is mostly independent of the platform or the operating system (except for the part which requires communication with hardware).
For the purpose of ASR engine demonstration, a  small GUI application was made. This application simply prints out recognized words in a text box. Of course, these words and their transitions must be defined in a grammar file stated in the command line.  Beside grammar file, it needs file containing HMM models, and a pronunciation dictionary. If all the files are provided, application will initialize structures in several  seconds, and will stand by for recognition. Recognition can be started and stopped by clicking appropriate  buttons.
The system  is trained to be speaker independent, so anyone can address it with similar accuracy. Although text is printed out with some delay, the engine is fast and can process more than ten recognitions in parallel, depending on grammar complexity.

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