Afluister Recorder

Afluister Recorder analyzes uploaded audio to generate transcripts, timing data, and quality metrics for researchers, podcasters, and journalists.

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אודות כלי זה

Afluister Recorder accepts audio uploads and returns a time-aligned transcript, duration, and quality metrics. It targets podcasters, researchers, journalists, and media teams needing rapid transcription and QA checks. The tool supports common formats (mp3, wav, m4a) and provides a plain transcript along with timestamps and optional subtitle export. It emphasizes privacy and batch processing for ongoing projects. The analytics include speaking rate, noise estimates, and basic speaker separation if enabled, enabling efficient content organization and compliance reviews. Outputs are suitable for search indexing and archival retrieval, with ready exports to JSON or SRT.
The system conceptually ingests audio, runs an ASR model to produce word-level timestamps, computes duration and basic acoustic metrics, and assembles structured outputs for downstream workflows. Users can process single files or batches, then export results for integration with media pipelines. The differentiators are language support (en/nl), batch capability, and privacy-forward processing, making it valuable for studios, research labs, and newsrooms seeking fast, auditable transcripts without manual listening.

איך להשתמש

  1. Provide inputs by uploading an audio file in mp3, wav, or m4a formats.
  2. Optionally select language (en or nl) or enable auto-detect.
  3. Run analysis to generate a time-stamped transcript and metrics.
  4. Review outputs and export as JSON or SRT; save transcript text if needed.
  5. If multi-speaker analysis is enabled, review diarized segments and adjust as needed.
How to use afluister recorder

Frequently Asked Questions

מצא תשובות מהירות

What file formats are supported?
Supported formats include MP3, WAV, and M4A. If an uploaded file uses a different encoding, the system will attempt to transcode to a compatible format before analysis, or return an actionable error if transcoding is not possible.
How accurate is the transcription?
Accuracy depends on audio quality, language, and speaking clarity. The tool provides word-level timestamps and a confidence estimate per segment. For Dutch and English content with clear audio, expected WER ranges are typical of off-the-shelf ASR models and improve with diarization when enabled.
Can this be used for real-time transcription?
No. The tool processes uploaded audio files in batch mode. Real-time streaming transcription is outside the current scope and would require a live capture pipeline.
How is data privacy handled?
Processing is designed to be privacy-conscious with optional data deletion controls. Uploaded files and results are stored only for the defined retention period, and users can opt out of permanent retention to comply with GDPR and other regulations.

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