Distant Speech Recognition in a Smart Home: Comparison of Several Multisource ASRs in Realistic Conditions

While the smart home domain has become a major field of application of ICT to improve support and wellness of people in loss of autonomy, speech technology in smart home has, comparatively to other ICTs, received limited attention. This paper presents the SWEET-HOME project whose aim is to make it possible for frail persons to control their domestic environment through voice interfaces. Several state-of-the-art and novel ASR techniques were evaluated on realistic data acquired in a multiroom smart home. This distant speech French corpus was recorded with 21 speakers playing scenarios including activities of daily living in a smart home equipped with several microphones. Techniques acting at the decoding stage and using a priori knowledge such as DDA give better results (WER=8.8%, Domotic F-measure=96.8%) than the baseline (WER=18.3%, Domotic F-measure=89.2%) and other approaches.