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Journal : International Journal of Artificial Intelligence Research

Optimizing Text Correction For Voice Based IoT Smart Building Virtual Assistants Shidiqi, Maulana Ahmad As; Hadi, Mokh Sholihul; Wibawa, Aji Prasetya; Mhd. Irvan, Mhd. Irvan
International Journal of Artificial Intelligence Research Vol 8, No 2 (2024): December 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1085

Abstract

The integration of Virtual Assistants (VAs) within Smart Building Internet of Things (IoT) ecosystems is increasingly critical, particularly for interpreting user commands via Automatic Speech Recognition (ASR). This paper presents an in-depth performance analysis of text correction algorithms on a Raspberry Pi 4—a cost-effective and widely used computing solution in smart building applications. Due to the absence of GPU acceleration for Python on ARM architecture, a specialized dataset was developed to benchmark algorithmic performance, focusing on correction times and accuracy. Our study utilized a near-real-world experimental setup, deploying Docker containers to simulate IoT MQTT brokers, a Smart Building Platform, and Rasa for dialogue management. Among the algorithms tested—Edit distance, Jaccard, FuzzPartialRatio, FuzzSortRatio, MLE, and Norvig Spell—the Edit distance and Norvig Spell emerged as leaders in accuracy, achieving an 84% success rate in text correction. Notably, the Edit distance algorithm demonstrated superior speed, vital for real-time processing demands. The Fuzz Sort Ratio algorithm distinguished itself with the fastest correction time at 31.6 milliseconds, albeit with a slight compromise on accuracy, attaining a 79% success rate. Consequently, the Edit distance algorithm is recommended for applications where accuracy and response time are paramount, while the Fuzz Sort Ratio is preferable for scenarios where speed is the overriding priority. This research paves the way for future exploration into the computational impacts of these algorithms and the exploration of neural network-based methods to further enhance text correction capabilities in smart building automation systems.
Co-Authors A.N. Afandi Achmad Safii Adi Izhar Che Ani Agung Witjoro Ahmad Fuadi Ahmad Sariful Anwar Ahmad Shukri Firdhaus Kamaruzaman Ahmad, Sharaf Aji Prasetya Wibawa Alfin Firmansyah Andriana Kusuma Dewi Anik Nur Handayani Annisa Firly Aprilia Putri Arfienda Miawa Tyassilva Arfiyansyah, Rizky Argeshwara, Dityo Kreshna Aripriharta - Arisatya Bharotoyakti Arrohman, Maulana Ludfi Aswin Rosadi Busaeri, Siti Rahbiah Che Ani, Adi Izhar Choirul Tri Fandiansyah Deva Putri Lestari Dito Valentino Dityo Kreshna Argeshwara Dityo Kreshna Argeshwara Dwi Arini Mufarichah Dwi Puri Fatmala Dyah Lestari Faidzin, Ilham Fatma Cahyaningrum Fattah, Muhammad Hattah Febryan, Febryan Fido Arya Kusuma Firdhaus Kamaruzaman, Ahmad Shukri Hamdani Mohammad Farid, Mohammad Afiq Hari, Nirwana Haidar Hasanuddin, Tasrif I Made Wirawan Irvan, Mhd Joumil Aidil Saifuddin Julfikar Mawansyah Lisma Hafifatul Aprilia M Syamsul Huda M. Alfian Mizar M. Farrel Akbar Firzatullah M. Rodzi Faiz Mhd. Irvan, Mhd. Irvan Moh. Zainul Falah Mohammad Afiq Hamdani Mohammad Farid Mohd Ikmal Fitri Maruzuki Muhammad Afnan Habibi Muhammad Yazid Muhiban Syabani Muladi Pradipta Adi Nugroho Ramdan Satra Ratna Juwita Resi Sari Dwijayanti Kartikasari Riski Achmad Fauzi Rizky Asillia P Sari Rosnani Rosnani Ryan Harris Abdillah Samsul Setumin Satia Nur Maharani Setumin, Samsul Shidiqi, Maulana Ahmad As Shidiqi, Maulana As Siti Juliana Abu Bakar Siti Sendari Siti Zubaidah Soenar Soekopitojo Soraya Norma Mustika Sugiono, Bhima Satria Rizki Sugiono, Bhima Satria Rizky Sujito Sujito Sujito Sujito Sumarno . Sunaryono Susilo, Suhiro Wongso Syaad Patmanthara Syafiq Ubaidilah Syaiful Anwar Tiara Windrias Putri Yandhika Surya Akbar Gumilang Yuli Agustina, Yuli Zaeni, Ilham Ari Elbaith Zulkham Umar Rosyidin Zulkham Umar Rosyidin