Audio Cleanup and Transcription (Whisper, etc)

Audio Cleanup and Transcription (Whisper, etc)

Using AI and open-source tools to clarify, clean, and transcribe speech recordings.

Overview

Audio cleanup and transcription tools help activists, researchers, and journalists make sense of noisy or hard-to-hear recordings. Whether documenting a public meeting, analyzing leaked audio, or improving accessibility for interviews, these tools can:

• Remove background noise
• Boost speech clarity
• Transcribe spoken words to text

Recent advances in AI, especially tools like OpenAI's Whisper, make it easier than ever to convert messy audio into readable, searchable text.

How It Works

Audio cleanup tools use filters and machine learning to enhance clarity:

• Noise reduction removes background hiss, hum, or crowd noise
• Equalization emphasizes voice frequencies
• Compression balances loud/soft parts of the recording

Transcription tools convert speech into text using automatic speech recognition (ASR) models. Some also support:

• Speaker diarization (who said what)
• Timestamping
• Multilingual support

Tools and Software

• Whisper by OpenAI:
  • State-of-the-art, open-source ASR model
  • Supports many languages and noisy recordings
  • Can run locally or via command line

• Audacity:
  • Free, open-source audio editor
  • Includes noise reduction, EQ, and compression

• Auphonic:
  • Web-based tool for automatic audio leveling and cleanup
  • Great for podcasts or interviews

• Descript:
  • Transcription and editing software with visual interface
  • Useful for editing audio by editing the text

• Otter.ai / Trint / Sonix:
  • Commercial web-based transcription tools with collaboration features

Use Cases in Activism

• Transcribing recorded public meetings or police interactions
• Enhancing low-quality protest footage audio
• Creating subtitles for accessibility and archiving
• Analyzing covert recordings for reports or investigations

Legal and Ethical Considerations

• Consent: Be aware of one-party vs two-party consent laws for recordings
• Disclosure: Label transcriptions as "machine-generated" unless reviewed
• Bias: Transcription tools may misinterpret accented speech or marginalized voices
• Security: Avoid uploading sensitive content to cloud services without protection — use offline tools like Whisper where possible

Best Practices

• Use high-quality microphones when possible to reduce need for heavy cleanup
• Clean audio before transcribing for better accuracy
• Always preserve original files in case of review or legal need
• Manually review and correct transcripts for accuracy when used as evidence

Limitations

• Whisper and others may misinterpret overlapping or fast speech
• Strong accents, slang, or technical jargon may cause errors
• Cleanup can’t always recover heavily damaged audio
• Offline transcription can require strong hardware (especially GPUs)

Related Tools and Topics

• Image and Video Enhancement
• Metadata Removal from Files and Images
• AI Summarizers and Text Analysis

Resources and Further Reading

• https://github.com/openai/whisper – Whisper source code and usage
• https://manual.audacityteam.org – Audacity documentation
• Tactical Tech and Witness guides on audio evidence handling

Legal Disclaimer

This page is for educational purposes only. Recording and transcribing speech may be subject to privacy laws. Always inform and respect participants, and use these tools responsibly to enhance truth and accessibility.