Design of a phoneme based voice controlled home automation system

Speech recognition has found a variety of applications in consumer electronics, such as smart phones, laptops, speech to text converters, live subtitling on television, dictation tool and many more. In this paper, design of a Voice Controlled Home Automation System using phoneme based speech recognition is proposed. The proposed system uses Mel Frequency Cepstral Coefficients for feature extraction and a two stage Support Vector Machine for classification. In order to assess the performance of system designed, voice samples were recorded in the laboratory to train the system. 86.00–100.0% recognition accuracy is obtained on using the proposed system with a recognition time of 0.9063s. The proposed work can be easily extended for various other voice controlled pattern recognition applications.