On Distant Speech Recognition for Home Automation

Abstract : In the framework of Ambient Assisted Living, home automation may be a solution for helping elderly people living alone at home. This study is part of the Sweet-Home project which aims at developing a new home automation system based on voice command to improve support and well-being of people in loss of autonomy. The goal of the study is vocal order recognition with a focus on two aspects: distance speech recognition and sentence spotting. Several ASR techniques were evaluated on a realistic corpus acquired in a 4-room flat equipped with microphones set in the ceiling. This distant speech French corpus was recorded with 21 speakers who acted scenarios of activities of daily living. Techniques acting at the decoding stage, such as our novel approach called Driven Decoding Algorithm (DDA), gave better speech recognition results than the baseline and other approaches. This solution which uses the two best SNR channels and a priori knowledge (voice commands and distress sentences) has demonstrated an increase in recognition rate without introducing false alarms.
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Chapitre d'ouvrage
Andreas HOLZINGER, Martina ZIEFLE & Carsten ROECKER. Lecture Notes in Computer Science, 8700, Springer, pp.161-188, 2015, Smart Health: Open Problems and Future Challenges, 978-3-319-16225-6. 〈10.1007/978-3-319-16226-3_7〉
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Michel Vacher, Benjamin Lecouteux, François Portet. On Distant Speech Recognition for Home Automation. Andreas HOLZINGER, Martina ZIEFLE & Carsten ROECKER. Lecture Notes in Computer Science, 8700, Springer, pp.161-188, 2015, Smart Health: Open Problems and Future Challenges, 978-3-319-16225-6. 〈10.1007/978-3-319-16226-3_7〉. 〈hal-01002819〉

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