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Multimodal interaction system for home appliances control
Fakhrurroja H.a, Machbub C.a, Prihatmanto A.S.a, Purwarianti A.a
a Bandung Institute of Technology, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020 International Association of Online Engineering.This paper proposes a way to control home appliances using a multimodal interaction system such as speech, gestures, and smartphone applications. The Kinect sensor used to capture Indonesian speech and gestures from users. Dialogue system, speech and gesture recognition process with finite state machine, Google Cloud Speech and K-Means Clustering, respectively. Users can also use the smartphone application to remotely control home appliances through mobile devices that are connected directly to the real-time database. There are two output responses from this system, namely the audio response generator to provide feedback to the user through the sound of the computer speaker and also provide an action to control home appliances use Esp8266. The average level of accuracy testing of interaction using dialogue systems and gesture are 92.5% and 79,25%. Interaction using dialogue systems is better than gesture. Smartphone applications can control home appliances properly.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Gesture recognition,Home appliances,Multimodal interaction,Smartphone application,Speech recognition[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][{‘$’: ‘The first author acknowledges support from the Lembaga Pengelola Dana Pendidikan (Indonesia Endowment Fund for Education) scholarship, Ministry of Finance, The Republic of Indonesia.’}, {‘$’: ‘The first author acknowledges support from the Lembaga Pengelola Dana Pendidi-kan (Indonesia Endowment Fund for Education) scholarship, Ministry of Finance, The Republic of Indonesia.’}][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.3991/IJIM.V14I15.13563[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]