Innovative Personal Assistance: Speech Recognition and NLP-Driven Robot Prototype
Main Article Content
Keywords
Personal Assistance, Text Conversion, Speech Recognition, Natural Language Processing, Google Drive
Abstract
This paper presents the development and evaluation of a personal assistant robot prototype with advanced speech recognition and natural language processing (NLP) capabilities. Powered by a Raspberry Pi microprocessor, it is the core component of the robot's hardware. It is designed to receive commands and promptly respond by performing the requested actions, utilizing integrated speech recognition and NLP technologies. The prototype aims to enhance meeting efficiency and productivity through audio-to-text conversion and high-quality image capture. Results show excellent performance, with accuracy rates of 100% in Indonesian and 99% in English. The efficient processing speed, averaging 9.07 seconds per minute in Indonesian and 15.3 seconds per minute in English, further enhances the robot's functionality. Additionally, integrating a high-resolution webcam enables high-quality image capture at 1280 x 720 pixels. Real-time integration with Google Drive ensures secure storage and seamless data management. The findings highlight the prototype's effectiveness in facilitating smooth interactions and effective communication, leveraging NLP for intelligent language understanding. Integrating NLP-based speech recognition, visual documentation, and data transfer provides a comprehensive platform for managing audio, text, and image data. The personal assistant robot prototype presented in this research represents a significant advancement in human-robot interaction, particularly in meeting and collaborative work settings. Further refinements in NLP can enhance efficiency and foster seamless human-robot interaction experiences.
References
A. de Barcelos Silva et al., “Intelligent personal assistants: A systematic literature review,” Expert Syst. Appl., vol. 147, p. 113193, 2020, doi: 10.1016/j.eswa.2020.113193.
A. Tur and D. Traum, “Comparing Approaches to Language Understanding for Human-Robot Dialogue: An Error Taxonomy and Analysis,” in Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022, pp. 5813–5820.
M. Omar, S. Choi, D. Nyang, and D. Mohaisen, “Robust natural language processing: Recent advances, challenges, and future directions,” IEEE Access, 2022.
L. Riccioli, “Artificial Intelligence: Innovation for Society 5.0,” Available SSRN 4457016, 2023.
C. Lakshmi Chandana et al., “Voice-Enabled Virtual Assistant,” in Sustainable Communication Networks and Application: Proceedings of ICSCN 2021, Springer, 2022, pp. 335–346.
B. G. Mark, E. Rauch, and D. T. Matt, “Worker assistance systems in manufacturing: A review of the state of the art and future directions,” J. Manuf. Syst., vol. 59, pp. 228–250, 2021.
A. Michalsen et al., “Interprofessional Shared Decision-Making in the ICU: A Systematic Review and Recommendations From an Expert Panel*,” Crit. Care Med., vol. 47, no. 9, 2019, [Online]. Available: https://journals.lww.com/ccmjournal/Fulltext/2019/09000/Interprofessional_Shared_Decision_Making_in_the.13.aspx
A. J. Farringer and S. M. Manchak, “Communication and collaboration in a drug court team.,” Psychol. Serv., p. No Pagination Specified-No Pagination Specified, 2022, doi: 10.1037/ser0000735.
A. C. Khumalo and B. T. Kane, “Perspectives on record-keeping practices in MDT meetings and meeting record utility,” Int. J. Med. Inform., vol. 161, p. 104711, 2022.
W. Villegas-Ch, R. Amores-Falconi, and E. Coronel-Silva, “Design Proposal for a Virtual Shopping Assistant for People with Vision Problems Applying Artificial Intelligence Techniques,” Big Data Cogn. Comput., vol. 7, no. 2, p. 96, 2023.
G. Dilip et al., “Artificial intelligence-based smart comrade robot for elders healthcare with strait rescue system,” J. Healthc. Eng., vol. 2022, 2022.
P. Abtahi et al., “Understanding physical practices and the role of technology in manual self-tracking,” Proc. ACM Interactive, Mobile, Wearable Ubiquitous Technol., vol. 4, no. 4, pp. 1–24, 2020.
A. El-Komy, O. R. Shahin, R. M. Abd El-Aziz, and A. I. Taloba, “Integration of computer vision and natural language processing in multimedia robotics application,” Inf. Sci, vol. 7, no. 6, 2022.
L. Seero, J. Burge, A. M. Soria, and A. Van Der Hoek, “Exploring a Research Agenda for Design Knowledge Capture in Meetings,” in 2023 IEEE/ACM 16th International Conference on Cooperative and Human Aspects of Software Engineering (CHASE), 2023, pp. 37–42.
J. A. W. Rainey, “Designing digital qualitative research workflows: enabling stakeholder participation across all research stages.” Newcastle University, 2021.
N. Chervyakov, M. Babenko, A. Tchernykh, N. Kucherov, V. Miranda-López, and J. M. Cortés-Mendoza, “AR-RRNS: Configurable reliable distributed data storage systems for Internet of Things to ensure security,” Futur. Gener. Comput. Syst., vol. 92, pp. 1080–1092, 2019.
S. Jacques, A. Ouahabi, and T. Lequeu, “Remote knowledge acquisition and assessment during the COVID-19 pandemic,” Int. J. Eng. Pedagog., vol. 10, 2020.
J. Kurjenniemi and N. Ryti, “Designing remote employee experience in knowledge work to attract talent,” 2020.
V. Ravindran, R. Ponraj, C. Krishnakumar, S. Ragunathan, V. Ramkumar, and K. Swaminathan, “IoT-Based Smart Transformer Monitoring System with Raspberry Pi,” in 2021 Innovations in Power and Advanced Computing Technologies (i-PACT), 2021, pp. 1–7.
B. Sudharsan, S. P. Kumar, and R. Dhakshinamurthy, “Ai vision: Smart speaker design and implementation with object detection custom skill and advanced voice interaction capability,” in 2019 11th International Conference on Advanced Computing (ICoAC), 2019, pp. 97–102.
R. Martinek, J. Vanus, J. Nedoma, M. Fridrich, J. Frnda, and A. Kawala-Sterniuk, “Voice communication in noisy environments in a smart house using hybrid LMS+ ICA algorithm,” Sensors, vol. 20, no. 21, p. 6022, 2020.
V. S. Abhijith and A. A. B. Raj, “Robot operating system based charging pad detection for multirotors,” in 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), 2020, pp. 1151–1155.
R. Beniwal, S. Patidar, R. Tomar, Shekhar, and R. Khatta, “Comparative Study of Cooling Solutions of a Drone Based on Raspberry Pi Deducing the Most Efficient Cooling Method,” in Computer Networks and Inventive Communication Technologies: Proceedings of Third ICCNCT 2020, 2021, pp. 269–281.
T. Yue et al., “A contact-triggered adaptive soft suction cup,” IEEE Robot. Autom. Lett., vol. 7, no. 2, pp. 3600–3607, 2022.
M. A. Afandi, I. Hikmah, and C. Agustinah, “Microcontroller-based Artificial Lighting to Help Growth the Seedling Pakcoy,” J. Nas. Tek. Elektro, vol. 10, no. 3, 2021, doi: 10.25077/jnte.v10n3.943.2021.
S.-Y. Zhang et al., “Molecule-based nonlinear optical switch with highly tunable on-off temperature using a dual solid solution approach,” Nat. Commun., vol. 11, no. 1, p. 2752, 2020.
Y. Liang et al., “A review of rechargeable batteries for portable electronic devices,” InfoMat, vol. 1, no. 1, pp. 6–32, 2019.
E. Billing, J. Rosén, and M. Lamb, “Language models for human-robot interaction,” in ACM/IEEE International Conference on Human-Robot Interaction, March 13–16, 2023, Stockholm, Sweden, 2023, pp. 905–906.
S. Hawi, J. Alhozami, R. AlQahtani, D. AlSafran, M. Alqarni, and L. El Sahmarany, “Automatic Parkinson’s disease detection based on the combination of long-term acoustic features and Mel frequency cepstral coefficients (MFCC),” Biomed. Signal Process. Control, vol. 78, p. 104013, 2022.
Z. E. Fitri, A. Baskara, A. Madjid, and A. M. N. Imron, “Comparison of Classification for Grading Red Dragon Fruit (Hylocereus Costaricensis),” J. Nas. Tek. Elektro, vol. 11, no. 1, pp. 43–49, 2022, doi: 10.25077/jnte.v11n1.899.2022.
A. Koduru, H. B. Valiveti, and A. K. Budati, “Feature extraction algorithms to improve the speech emotion recognition rate,” Int. J. Speech Technol., vol. 23, no. 1, pp. 45–55, 2020.
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
The authors declare that:
1. This paper has not been published in the same form elsewhere.
2. It will not be submitted anywhere else for publication prior to acceptance/rejection by this Journal.
3. A copyright permission is obtained for materials published elsewhere and which require this permission for reproduction.