Transcriber: An Android application that automates the transcription of interviews in Indonesian
Rahman Adianto, Cil Hardianto Satriawan, Dessi Puji Lestari · 2017
In this paper, a Transcriber that can be used to automatically transcribe interviews in Indonesian using speech-to-text and speaker diarization technology is described. The main feature of the software is generating interview transcription automatically and providing an option if grouping by group of speakers is required. Transcriber is designed to work in two modes that give users the freedom to provide recording file input or perform live recording. Automatic Speech Recognition (ASR) used in Transcriber was developed by utilizing KALDI and the ASR model developed in the previous research, while the speaker diarization was developed with LIUM Speaker Diarization and successfully optimized for Indonesian with DER 35.10%. These technologies are integrated into a whole system that has client-server architecture and is capable of transcribing interviews for 1.10 times the duration of input recordings excluding connection latency. Transcriber has also managed to gain positive feedback on the usability testing.