Speech recognition has been an important area of research during the past decades. The usage of automatic speech recognition systems is rapidly increasing among different areas, such as mobile telephony, automotive, healthcare, robotics and more. However, despite the existence of many speech recognition systems, most of them use platform specific and non-publicly available software. Nevertheless, it is possible to develop speech recognition systems using already existing open source technology. The aim of this master's thesis is to develop an interactive and speaker independent speech recognition system. The system shall be able to identify predetermined keywords from incoming live speech and in response, play audio files with related information. Moreover, the system shall be able to provide a response even if no keyword was identified. For this project, the system was implemented using PocketSphinx, a speech recognition library, part of the open source Sphinx technology by the Carnegie Mellon University. During the implementation of this project, the automation of different steps of the process, was a key factor for a successful completion. This automation consisted on the development of different tools for the creation of the language model and the dictionary, two important components of the system. Similarly, the audio files to be played after identifying a keyword, as well as the evaluation of the system's performance, were fully automated. The tests run show encouraging results and demonstrate that the system is a feasible solution that could be implemented and tested in a real embedded application. Despite the good results, possible improvements can be implemented, such as the creation of a different phonetic dictionary to support different languages.

O objetivo do presente trabalho de pesquisa é reduzir o nível de atenção requerido para o uso do sistema Borboleta por meio de reconhecimento de fala na navegação através das funcionalidades do sistema, permitindo ao profissional dar maior atenção ao paciente. A metodologia de desenvolvimento do projeto inclui uma revisão bibliográfica para definir o estado da arte da área, uma pesquisa sobre o software disponível para reconhecimento de fala, uma coleta de dados dos comandos do sistema em português brasileiro para treinar e testar o sistema, uma etapa de projeção e desenvolvimento para definir a arquitetura de integração com o Borboleta, e uma fase de testes para medir a precisão do sistema e seus níveis de usabilidade e aceitação por parte do usuário. / The current document presents research that addresses the goal of reducing the user attention level required by Borboleta operation by providing speech recognition capabilities to augment navigation through the software functions, allowing the professional to pay more attention to the patient. The project methodology is composed of a bibliography revision to establish the state-of-the-art of the field, a review of available speech recognition software, data collection of Brazilian utterances to train and test the system, a design and development stage that defined the system architecture and integration with Borboleta and a testing process to measure the system accuracy, its usability and acceptance level.

O objetivo do presente trabalho de pesquisa é reduzir o nível de atenção requerido para o uso do sistema Borboleta por meio de reconhecimento de fala na navegação através das funcionalidades do sistema, permitindo ao profissional dar maior atenção ao paciente. A metodologia de desenvolvimento do projeto inclui uma revisão bibliográfica para definir o estado da arte da área, uma pesquisa sobre o software disponível para reconhecimento de fala, uma coleta de dados dos comandos do sistema em português brasileiro para treinar e testar o sistema, uma etapa de projeção e desenvolvimento para definir a arquitetura de integração com o Borboleta, e uma fase de testes para medir a precisão do sistema e seus níveis de usabilidade e aceitação por parte do usuário. / The current document presents research that addresses the goal of reducing the user attention level required by Borboleta operation by providing speech recognition capabilities to augment navigation through the software functions, allowing the professional to pay more attention to the patient. The project methodology is composed of a bibliography revision to establish the state-of-the-art of the field, a review of available speech recognition software, data collection of Brazilian utterances to train and test the system, a design and development stage that defined the system architecture and integration with Borboleta and a testing process to measure the system accuracy, its usability and acceptance level.