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Journal : Indonesian Journal of Data and Science

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 Abdul Huda Abdul Huda, Abdul Adi Atmoko Adi Sutanto Ahmad Munjin Nasih Ahmad Nurdiansyah, Ahmad Alimul Muniroh Andi Mappiare Anik Nur Handayani Anjarie Dharmastuti Apriliyanti , Fressi Arbin Janu Setiyowati, Arbin Arfan Triwiratman Asep Sunandar Astriyani Astriyani Azizah, Desi Fatkhi Bambang Budi Wiyono Caecilia Binanda Rucitra Herestusiwi Carolina Ligya Radjah, Carolina Ligya Danardana Murwani Denny Bernardus DIRGANTORO, AJAR Ediyanto Efendy, Mamang Eva, Nur Faizah, Siti Fitri Wahyuni Fulgentius Danardana Murwani Gani, Suriati Abdul Hanurawan, Fattah Hanurrawan, Fattah Hariddha Yuni Sulistyaningrum Harits Ar Rosyid Hariyono Hariyono Henny Indreswari Herestusiwi, Caecilia Binanda Rucitra Hetti Rahmawati I Nyoman Sudana Degeng Ihdan Nizar Aza Ika Andrini Farida Ikma Ni’ma Qoni’ Imanuel Deny Krisna Aji Isrida Yul Arifiana Jatiperwira, Stefan Yudana Jevri Tri Ardiansah Kiftiyah, Kiftiyah Lia Yuliati Liestya Padmawidjaja Maghfiroh, Nasruliyah Hikmatul Margaretta Erna Setianingrum Marpaung, Julia Vika Andriani Marthen Pali Marthen Pali Marthen Pali, Marthen Mika Nur Cahyanti Mika Nur Cahyanti, Mika Nur Muhammad Syamsun Mukti, Fajar Dwi Muslihati Muthia Aryuni Nasruliyah Hikmatul Maghfiroh Norma Gupita Novia Nuril Firdaus Nur Hidayah Nurhusna Nurrokhmatulloh, Nurrokhmatulloh Praja, Rafli Indar Prio Utomo Rifqi Syahrul Azizah Rochmawati, Rochmawati Sa'dun Akbar Septin Anggraini Suharni Suharni Syaipul Pahru Toto Nusantara Triyono Triyono Valdez, Anabelie V. Valdez, V. Wahyu Widodo Wahyu Widodo Wiwik Dwi Hastuti Yohanes Subasno Yuniwati, Esy Suraeni Yurni yurni Zamzami Sabiq