Project homeChanges for page Social Robot
Last modified by Sofia Vlachopanou on 2025/04/24 23:04
From version 3.1
edited by Nikolaos Soumpeniotis
on 2025/03/01 20:28
on 2025/03/01 20:28
Change comment:
Uploaded new attachment "1740857323532-304.png", version {1}
To version 4.3
edited by Nikolaos Soumpeniotis
on 2025/03/01 20:34
on 2025/03/01 20:34
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There is no comment for this version
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... ... @@ -1,0 +1,31 @@ 1 + 2 +(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)The application will use the Pepper robot which has a built-in tablet device. More specifically, this is a humanoid robot(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 700; font-style: normal; text-decoration: none" %)** ,**(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 700; font-style: normal; text-decoration: none; font-weight: 400; font-style: normal; text-decoration: none" %)commonly used, because it offers interactive services such as welcoming visitors, providing information, and even dancing. Its ability to recognize faces and interpret emotions enables it to create more natural connections, making it particularly effective in healthcare.Pepper was used before with older adults, including as a coach for those with psychiatric disorders. A lot of studies have proved that the interaction of the elderly people with the Pepper robot is efficient and helps the patient to improve the quality of their lives. [1] 3 + 4 + 5 +(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(0, 0, 0); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Pepper is equipped with a lot of advanced sensors that enable it to interact with its environment effectively. It features four microphones, two RGB cameras, and a 3D sensor on its head, along with touch sensors on its hands and chest. Additionally, Pepper's legs are equipped with sonar, laser, and bumper sensors, along with a gyro sensor for balance. These sensors work together to allow Pepper to recognize faces, interpret emotions, and navigate its surroundings with precision [2]. 6 + 7 +[[image:1740857394953-812.png]] 8 + 9 + 10 + 11 +(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %) 12 +(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Another important technology to consider is Cloud Computing, which enables access to external libraries, enhancing the robot’s ability to interact by enriching dialogues. Additionally, cloud computing allows for real-time monitoring of the robot’s interactions and facilitates adaptive decision-making when needed [1]. 13 + 14 +(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %) 15 +(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Equally important aspect of our system is speech recognition, which begins with signal processing through feature extraction. Feature extraction transforms raw audio into a format that machines can process, typically using spectrograms. Spectrograms provide a visual representation of sound frequency over time. 16 + 17 +(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %) 18 +(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)After the feature extraction, Deep Neural Networks (DNNs) play a crucial role in mapping these features to words.Additionally, Convolutional Neural Networks (CNNs) are often utilized to process spectrograms, helping to extract meaningful spatial patterns from the data [3]. 19 + 20 +(% style="line-height:1.38; margin-top:16px; margin-bottom:16px" %) 21 +(% style="font-size: 11pt; font-variant: normal; white-space: pre-wrap; font-family: Arial, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %) After the neural network processes the speech, a language model is applied to improve recognition accuracy by selecting the most probable word sequence. Traditional approaches relied on n-gram models. 22 + 23 +**References:** 24 + 25 +[1] Neerincx, M.A., van Vught, W., Blanson Henkemans, O., Oleari, E., Broekens, J., Peters, R., Kaptein, F., Demiris, Y., Kiefer, B., Fumagalli, D. and Bierman, B. (2019). Socio-Cognitive Engineering of a Robotic Partner for Child’s Diabetes Self-Management. //Frontiers in Robotics and AI//, 6. doi:https:~/~/doi.org/10.3389/frobt.2019.00118. 26 + 27 +[2] (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Abdel-Hamid, O., Mohamed, A., Jiang, H., & Penn, G. (2014). Convolutional neural networks for speech recognition. (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: italic; text-decoration: none" %)//IEEE/ACM Transactions on Audio, Speech, and Language Processing//(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %), 22(10), 1533-1545. 28 + 29 +[3] (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)Faisal, M., Alharbi, A., Alhamadi, A., Almutairi, S., Alenezi, S., Alsulaili, A., Khan, M., & Khan, F. (2024). Robot-based solution for helping Alzheimer patients. (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: italic; text-decoration: none" %)//SLAS technology//(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %), (% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: italic; text-decoration: none" %)//29//(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(33, 33, 33); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: none" %)(3), 100140. (%%)[[(% style="font-size: 12pt; font-variant: normal; white-space: pre-wrap; font-family: Ubuntu, sans-serif; color: rgb(17, 85, 204); background-color: rgb(255, 255, 255); font-weight: 400; font-style: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none" %)https:~~/~~/doi.org/10.1016/j.slast.2024.100140>>url:https://doi.org/10.1016/j.slast.2024.100140||style="text-decoration:none"]] 30 + 31 +
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