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Comparative Analysis of Speech-to-Text APIs for Supporting Communication of the Deaf Community Handayani, Anik Nur; Hariyono, Hariyono; Nasih, Ahmad Munjin; Rochmawati, Rochmawati; Hitipeuw, Imanuel; Ar Rosyid, Harits; Ardiansah, Jevri Tri; Praja, Rafli Indar; Nurdiansyah, Ahmad; Azizah, Desi Fatkhi
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.327

Abstract

Hearing impairment can have a profound impact on the mental and emotional state of sufferers, as well as hinder communication and delay in accessing information directly that relies on interpreters. Advances in assistive technology, especially speech recognition systems that are able to convert spoken language into written text (speech-to-text). However, its implementation faces various challenges related to the level of accuracy of each speech-to-text Application Programming Interface (API), thus requiring an appropriate deep learning model. This study serves to analyze and compare the performance of speech-to-text API services (Deepgram API, Google API and Whisper AI) based on Word Error Rate (WER) and Words Per Minute (WPM), to determine the most optimal API in a web-based real-time transcription system using the JavaScript programming language and Glitch.com. The three API services were tested by calculating their error rates and transcription speeds, then evaluated to see how low the error accuracy rate was and how high the transcription speed was. On average, Whisper AI had a WER of 0% across all word categories, but its speed was lower than the other two APIs. Deepgram API displayed the best balance between accuracy and speed, with an average WER of 13.78% and 67 WPM. Google API performed stably, but its WER value was slightly higher than Deepgram API. In conclusion, based on the results, Deepgram API was deemed the most optimal for live transcription, as it is capable of producing fast and error-free transcriptions, significantly increasing the accessibility of information for the deaf community.
Co-Authors Abdullah, Dzulkifli Achmad Iffad Adhilaga, Hanif Aditya Galih Sulaksono, Aditya Galih Agung Bella Putra Utama Agusta Rakhmat Taufani Ahmad Adi Prasetyo Ahmad Munjin Nasih Ahmad Nurdiansyah, Ahmad Aji Prasetya Wibawa Akmal Vrisna Alzuhdi Ali M. Mohammad Salah Alqahtani, Mohammed S. Amalia Amalia Anie Yulistyorini Anik Nur Handayani Ardi Anugerah Wicaksana Aripriharta - Asa Luki Setiawan Asfani, Khoirudin Ashar, Muhammad Aulia Yahya Harindra Putra Aya Sofia Mufti Azhar Ahmad Smaragdina Azizah, Desi Fatkhi Brillianta Zayyan Muhammad Danang Rahmat Bachtiar Denny Kurniawan Diederik Rousseau Dyah Lestari Edwin Meinardi Trianto Elfonda Daffa Risqullah Elmiyadi Novia Farma Esther Irawati Setiawan Fajariani, Erna Fatma Yuniardini Fauzi, Rochmad Febrianto Alqodri Felix Andika Dwiyanto Ferdinand, Miftakhul Anggita Bima Gunawan Gunawan Gunawan Hakkun Elmunsyah Hariyono Hariyono Hartarto Junaedi Hendrawan Armanto Herman Thuan To Saurik Heru Wahyu Herwanto Imanuel Hitipeuw Jevri Tri Ardiansah Joumil Aidil Saifuddin Khoiruddin Asfanie Khurin Nabila Kumalasari, Ira Kusuma Refa Haratama Liang, Yeoh Wen Lucyta Qutsyaning Rosydah M Baharuddin Yusuf Mohammad Musthofa Al Ansyorie Mohammad Yasser Chuttur Mokhtar , Norrima Binti Muchamad Andis Setiawan Muhammad Akbar Muhammad Iqbal Akbar Muhammad Naufal Farras Muladi Mursyit, Mohammad Mutyara Whening Aniendya Nastiti Susetyo Fanany Putri Novian Dwi syahrizal Hilmi Nur A’yuni Ramadhani Nur Hidayatullah Nur Sa’ida Kismurdiani Praja, Rafli Indar Prasetyo, Ahmad Adi Prawidya, Della Murbarani Rahadyan Fannani Arif Rochmawati, Rochmawati Sari, Tenty Luay Setumin , Samsul Shah Nazir Siti Sendari Suparman Syaad Patmanthara Teguh Andriyanto, Teguh Theodora Monica Timothy John Pattiasina Tinesa Fara Prihandini Utomo Pujianto Wahyu Irianto Wako Uriu Wiryawan, Muhammad Zaki Yudhistira, Moch Rajendra Yusmanto, Yunan Zaeni, Ilham Ari Elbaith