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SpeechToText: An open-source software for automatic detection and transcription of voice recordings in digital forensics
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Orientador(es)
Resumo(s)
Voice is the most natural way for humans to communicate with each other, and more recently, to interact with voice controlled digital machines. Although text is predominant in digital platforms, voice and video are becoming increasingly important, with communication applications supporting voice messages and videos. This is relevant for digital forensic examinations, as content held in voice format can hold relevant evidence for the investigation. In this paper, we present the open source SpeechToText software, which resorts to state-of-the art Voice Activity Detection (VAD) and Automatic Speech Recognition (ASR) modules to detect voice content, and then to transcribe it to text. This allows integrating voice content into the regular flow of a digital forensic investigation, with transcribed audio indexed by text search engines. Although SpeechToText can be run independently, it also provides a Jython-based software module for the well-known Autopsy software. The paper also analyzes the availability, storage location and audio format of voice-recorded content in 14 popular Android applications featuring voice recordings. SpeechToText achieves 100% accuracy for detecting voice in unencrypted audio/video files, a word error rate (WER) of 27.2% when transcribing English voice messages by non-native speakers and a WER of 7.80% for the test-clean set of LibriSpeech. It achieves a real time factor of 0.15 for the detection and transcription process in a medium-range laptop, meaning that 1 min of speech is processed in roughly 9 s.
Descrição
Article number - 301223
Palavras-chave
Android applications Automatic speech recognition Automatic speech transcription Digital forensics Voice recordings
Contexto Educativo
Citação
Miguel Negrão, Patricio Domingues, SpeechToText: An open-source software for automatic detection and transcription of voice recordings in digital forensics, Forensic Science International: Digital Investigation, Volume 38, 2021, 301223, ISSN 2666-2817, https://doi.org/10.1016/j.fsidi.2021.301223.
Editora
Elsevier
Licença CC
Sem licença CC