Speech-Driven Academic Records Delivery System
Keywords:
N\AAbstract
An Interactive Voice Response System (IVRS) is a computerized system employing pre-recorded or dynamically synthesized voice for interaction with users via speech recognition or DTMF (Dual-Tone Multi-Frequency) input offered through a phone keypad. In this project, we have a robust automation system for the issuing of academic records and certificates through IVRS technology. The users can place orders and pay for academic documents through simple voice commands or keypad inputs. The system conveys live academic information and intelligently forwards the caller to the appropriate department or service depending on their input. DTMF tones uttered over telephone keypads and speech recognition systems are utilized to accurately interpret user decisions and instructions. Furthermore, text-to-speech (TTS) technology is employed to render complex and dynamic text-based academic information into voice. This IVRS system reduces human effort to a significant extent while enhancing the user experience by making sure the callers reach exactly what they need. Once configured, the system operates without human intervention and can deliver 24/7 service to the users. Overall, this voice system is an affordable, effective, and scalable means for schools to provide a personalized and automated service experience.
Downloads
Metrics
References
Priscilla Manatsa, An Analysis of the impact of implementing a new Interactive Voice Response System (IVR) on Client experience in the canadian Banking Industry, International Economics and Finance, Ryerson University, 2019
Itorobong A. Inam et al.,Comparative Analysis and Review of Interactive Voice Response Systems,Conference on Information Communications Technology and Society,2018
Samarth Agarwal et al., Personalized Digital Customer Services for Consumer Banking Call Centre using Neural Networks,
University of Western Ontario,2020
Polyna Khudyakov et al., Designing a call center with an IVR (Interactive Voice Response),2018
Esra Ben Ismail et al., IVR System Use by Patients with Heart Failure: Compliance and Services Utilization Patterns, Journal of Medical Systems (2022)
Priscilla Manatsa, An Analysis of the impact of implementing a new Interactive Voice Response System (IVR) on Client experience in the canadian Banking Industry, International Economics and Finance, Ryerson University, 2019
Next Generation IVR Using Twilio Speech Recognition and Chatbots
https://www.linkedin.com/pulse/next-generation-ivr-using- twilio-speech-recognition-chatbots-badri/?trk=v-feed
Interactive voice response https://en.wikipedia.org/wiki/Interactive_voice_response
D Shanthi, "Smart Water Bottle with Smart Technology", Handbook of Artificial Intelligence, Benthem Science Publishers, Pg. no: 204-219, 2023
D Shanthi , Smart Healthcare for Pregnant Women in Rural Areas, Medical Imaging and Health Informatics, Wiley Publishers,ch-17, pg.no:317-334, 2022
D. Shanthi, R. K. Mohanty and G. Narsimha, "Application of machine learning reliability data sets", Proc. 2nd Int. Conf. Intell. Comput. Control Syst. (ICICCS), pp. 1472-1474, 2018.
D Shanthi, N Swapna, Ajmeera Kiran and A Anoosha, "Ensemble Approach Of GPACOTPSOAnd SNN For Predicting Software Reliability", International Journal Of Engineering Systems Modelling And Simulation, 2022.
D. Shanthi, "Ensemble Approach of ACOT and PSO for Predicting Software Reliability", 2021 Sixth International Conference on Image Information Processing (ICIIP), pp. 202-207, 2021.
D Shanthi, CH Sankeerthana and R Usha Rani, "Spiking Neural Networks for Predicting Software Reliability", ICICNIS 2020, January 2021, [online] Available: https://ssrn.com/abstract=3769088.
Shanthi, D. (2023). Smart Water Bottle with Smart Technology. In Handbook of Artificial Intelligence (pp. 204-219). Bentham Science Publishers.
D. Shanthi, P. Kuncha, M. S. M. Dhar, A. Jamshed, H. Pallathadka and A. L. K. J E, "The Blue Brain Technology using Machine Learning," 2021 6th International Conference on Communication and Electronics Systems (ICCES), Coimbatre, India, 2021, pp. 1370-1375, doi: 10.1109/ICCES51350.2021.9489075.
Shanthi, D., Aryan, S. R., Harshitha, K., & Malgireddy, S. (2023, December). Smart Helmet. In International Conference on Advances in Computational Intelligence (pp. 1-17). Cham: Springer Nature Switzerland.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
