Kastytis Ratkevicius

Recognition of Voice Commands Using Hybrid Approach

Computerized systems with voice user interfaces could save time and ease the work of healthcare practitioners. To achieve this goal voice user interface should be reliable (to recognize the commands with high enough accuracy) and properly designed (to be convenient for the user). The paper deals with hybrid approach implementation issues for the voice commands recognition. By the hybrid approach we assume the combination of several different recognition methods to achieve higher recognition accuracy. The experimental results show that most voice commands are recognized good enough but there is some set of voice commands which recognition is more complicated. In this paper the novel method is proposed for the combination of several recognition methods based on the Ripper algorithm. Experimental evaluation showed that this method allows achieve higher recognition accuracy than application of blind combination rule.

DfA implementations for people with vision and hearing disabilities: application and development for information society

This paper presents activities and challenges when implementing information processing technologies for people with hearing and visual impairments. Other than keyboard based input and monitor based for output modalities should be employed for this category of users. More important is that these modalities are crucial element for successful implementation of complex systems designed for disabled people. Some activities carried on in Lithuania implementing applications oriented for disabled people or using speech technologies and targeted to impaired people are presented too.

Hybrid Recognition Technology for Isolated Voice Commands

The paper deals with two elements of the artificial intelligence methods—the natural language processing and machine learning. Hybrid recognition technology for isolated Lithuanian voice commands is described. By the hybrid approach we assume the combination of two different recognition methods to achieve higher recognition accuracy. The method which is based on the machine learning algorithm to combine the recognition results provided by two different recognizers is described. The first recognizer was HTK-based Lithuanian recognizer, the second one—the Spanish language recognizer adapted to the Lithuanian language. The experimental results show that a hybrid decision-making rule learned by “random forest” classifier works with 99.46 % accuracy and exceeds the accuracy of the “blind” decision-making rule (96.12 %). The average hybrid operation accuracy reaches 99.24 %, when the recognizer recognizes voice commands out of 12 known speakers, and is equal to 99.18 %, when it is applied to the unknown speaker.

On the Adaptation of Foreign Language Speech Recognition Engines for Lithuanian Speech Recognition

This paper presents some of our activities trying to adapt the foreign language based speech recognition engines for the recognition of the Lithuanian speech commands. In recent years several quiet successful speech recognition engines became available for the most popular languages (such as English, French, Spanish, German, etc.). The speakers of a less widely used languages (such as Lithuanian) have several choices: to develop own speech recognition engines or to try adapting speech recognition models developed and trained for the foreign languages to the task of recognition of their native spoken language. First approach is expensive in time, financial and human resources sense. Second approach can lead to faster implementation of Lithuanian speech recognition modules into some practical tasks but proper adaptation and optimization procedures should be found and investigated.

Voice Controlled Interface for the Medical-Pharmaceutical Information System

This paper describes our efforts developing the voice controlled interface for the medical- pharmaceutical information system. It is well known that voice controlled interfaces are of particular importance and may provide significant convenience for healthcare professionals. Many international IT companies provide speech processing by using tools oriented at the physicians or at other professionals working in the related areas. Lithuanian professionals feel a significant lack of speech processing since there are still no attempts to integrate Lithuanian speech processing into medical information systems in this country. The paper presents several IS under development for the use in Lithuanian healthcare institutions. The experimental evaluation shows that it is possible to achieve recognition accuracy (at least 95% of correct recognition) acceptable for the practitioners. The evaluation of system prototypes shows that voice interfaces may lead to the increased convenience of IT systems at the healthcare practitioners.

Hmi Modelling for Multimodal Lithuanian Applications

Spoken dialogue based human-machine interfaces (HMI) are becoming more and more widely integrated in computer applications. Speech allows doing some task easier and faster. The combination with a more traditional means of input and out – i.e. the multimodality factor becomes more and more important allowing wider accessibility. It is important to model and design spoken language dialog trees to mimic the natural conversations in the human-computer interactions, especially in information retrieval systems and applications. The paper presents three algorithms of HMI dialogs and the results of their experimental evaluation. The results showed that it is possible to achieve about 97% recognition accuracy in simple phrase based dialog conversations and about 93% in a very naturally sounding keyword spotting based dialogs. DOI: http://dx.doi.org/10.5755/j01.itc.41.2.909