Speech recognition results for voice-controlled assistive applications

Abstract

Until recently, controlling a “smart home” consisted in setting up a series of applications and automation tools: scheduling when the air conditioning system could cool the room, turn on the lighting system at sunset, or just use ones phone to control several TV appliances or the garage door. Recent advances in speech recognition technology have made voice-controlled smart homes attainable, and many companies and communities are providing interfaces or home boxes to make this voice control available. However, they lack customization ability, and interoperability with appliances or applications is not guaranteed. Moreover, most of these systems are not focused in supporting specific voice recognition scenarios, such as assistive applications for elder or disabled people or consider a triggered close talking voice interaction. Although state of the art speech processing has achieved great performance for most widely used languages, little to no efforts were made for under-resourced languages, such as Romanian. This paper focuses on a set of experiments in building a series of acoustic and grammar models for Romanian language, to be used in distant speech recognition scenarios, for voice driven speech applications in intelligent homes or buildings, using previously acquired speech databases in Romanian language, in real life conditions, by our research group.