Task and Context Aware Isolated Word Recognition

Speech recognition is encountering a new perspective due to technological developments leading to the design of smart living spaces, assisted living for the disabled, ambient intelligence for increased comfort and natural human - computer interfaces. Isolated word recognition is a subset of the overall speech recognition problem, where only a small number of words need to be recognized. Speaker dependent or independent small vocabulary recognition can find significant applications in the context of living areas or workspaces where functionality is controlled by a small number of commands that need to be given quickly and accurately understood, under conditions where delicate manual operations are difficult to achieve. This type of application could hence significantly benefit by the use of heavily context and task aware feature extraction and classification algorithms, as they would facilitate the interaction with their users and render it much more reliable in times of crisis. This paper presents current challenges involved in attaining efficient and robust small vocabulary speech recognition. A contextual awareness approach is presented that may quantify application and context aware feature selection, classification techniques, useful for the voice guidance of different equipment in a variety of situations.