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Speech Synthesis
Whisper Speaker Diarization

Whisper Speaker Diarization

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What is Whisper Speaker Diarization ?

Whisper Speaker Diarization is a feature within the Whisper Automatic Speech Recognition (ASR) system, designed to identify and label speakers in audio recordings. It is a powerful tool for organizing and analyzing multi-speaker audio data, making it easier to understand who said what and when.

Features

• Speaker Identification: Automatically detects and labels different speakers in an audio file.
• Transcript-Compatible Output: Generates speaker tags that can be integrated into transcription files.
• Support for Multiple Formats: Works with common audio formats such as WAV, MP3, and FLAC.
• Multi-Language Support: Compatible with a wide range of languages and dialects.
• Real-Time Processing: Enables speaker diarization for live audio streams or real-time applications.
• Adjustable Sensitivity: Allows users to fine-tune speaker detection sensitivity based on their needs.

How to use Whisper Speaker Diarization ?

  1. Prepare Your Audio File: Ensure your audio file is in a supported format (e.g., WAV, MP3).
  2. Run Whisper Speaker Diarization: Use the Whisper ASR system with the speaker diarization option enabled. This can be done via the command line or through an API call.
  3. Review the Output: The system will generate a transcription with speaker labels, indicating who spoke and when.
  4. Apply to Multiple Files: Use the tool in batch mode to process multiple audio files simultaneously.

Frequently Asked Questions

1. What is the purpose of Whisper Speaker Diarization?
Whisper Speaker Diarization is used to automatically identify and label speakers in audio recordings, making it easier to analyze multi-speaker conversations or meetings.

2. What file formats does Whisper Speaker Diarization support?
Whisper Speaker Diarization supports common audio formats such as WAV, MP3, and FLAC.

3. Can I adjust the sensitivity of speaker detection?
Yes, Whisper Speaker Diarization allows users to adjust the sensitivity of speaker detection to meet their specific needs.

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