TY - GEN
T1 - Modular Design of a Front-End and Back-End Speech-to-Speech Translation Application for Psychiatric Treatment of Refugees
AU - Ugan, Enes Yavuz
AU - Mediani, Mohammed
AU - Al Jawabra, Omar
AU - Khader, Aya
AU - Liu, Yining
AU - Waibel, Alexander
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - One of the inevitable impacts happening in areas with political conflicts is the significant influx of displaced individuals. The psychological consequences on individuals enduring such events are profound. Therefore, the imperative of providing adequate mental health care to refugees coming from conflict areas becomes apparent. However, providing this necessary care faces two obstacles. On the one hand, not all this target population is expected to have an acceptable level of proficiency of the hosting country's local language. On the other hand, finding enough number of suitable interpreters is a very challenging task. Moreover, even when the availability of the human interpreters is no problem, the refugees may hesitate to share their experiences with interpreters due to the associated stigma. To address these challenges and enhance mental health care for refugees, we propose the design of a modular front-end and back-end Speech-to-Speech translation system, with a focus on safeguarding patient data privacy. As our system is Speech-to-Speech, it also enables dialogue with dyslexic people and removes barriers for their treatment as well.
AB - One of the inevitable impacts happening in areas with political conflicts is the significant influx of displaced individuals. The psychological consequences on individuals enduring such events are profound. Therefore, the imperative of providing adequate mental health care to refugees coming from conflict areas becomes apparent. However, providing this necessary care faces two obstacles. On the one hand, not all this target population is expected to have an acceptable level of proficiency of the hosting country's local language. On the other hand, finding enough number of suitable interpreters is a very challenging task. Moreover, even when the availability of the human interpreters is no problem, the refugees may hesitate to share their experiences with interpreters due to the associated stigma. To address these challenges and enhance mental health care for refugees, we propose the design of a modular front-end and back-end Speech-to-Speech translation system, with a focus on safeguarding patient data privacy. As our system is Speech-to-Speech, it also enables dialogue with dyslexic people and removes barriers for their treatment as well.
KW - application
KW - artificial intelligence
KW - machine translation
KW - mental health
KW - speech recognition
KW - speech synthesis
KW - speech-to-speech system
UR - http://www.scopus.com/inward/record.url?scp=85182730913&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85182730913&partnerID=8YFLogxK
U2 - 10.1109/GHTC56179.2023.10354809
DO - 10.1109/GHTC56179.2023.10354809
M3 - Conference contribution
AN - SCOPUS:85182730913
T3 - 2023 IEEE Global Humanitarian Technology Conference, GHTC 2023
SP - 128
EP - 131
BT - 2023 IEEE Global Humanitarian Technology Conference, GHTC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th Annual IEEE Global Humanitarian Technology Conference, GHTC 2023
Y2 - 12 October 2023 through 15 October 2023
ER -