Audio to Text

This tool converts spoken content in audio files into editable text for analysis, publication, and accessibility. It supports multiple languages, variable transcription modes, and flexible exports to fit editorial pipelines.
Under the hood, automatic speech recognition models generate time-aligned tokens, followed by post-processing for punctuation and casing. Users can enable speaker diarization to label segments by speaker and choose between verbatim or cleaned transcripts. Timestamps can be included to produce SRT or VTT files for video captions. This combination enables researchers, journalists, and educators to turn interviews, lectures, and podcasts into searchable text quickly, with options to export to TXT, DOCX, SRT, or VTT for integration with other tools.
The tool prioritizes accuracy, with language selection (or auto-detect) to improve recognition. It also supports batch processing for long-form content and glossary terms to preserve jargon or brand names. Outputs include the plain transcript, optional timestamped segments, and counts such as word and duration metrics. Use cases include interview transcripts, lecture notes, podcast show notes, and investigative reporting, where rapid turnaround and multilingual support add substantial editorial value.