diarize_speech

Transcribe audio to text with speaker diarization using the Whissle MCP Server. Identifies speakers, generates a transcription, and saves the output file to a specified or default directory. Requires an audio file path and optional parameters for model and speaker count.

Instructions

Convert speech to text with speaker diarization and save the output text file to a given directory. Directory is optional, if not provided, the output file will be saved to $HOME/Desktop.

⚠️ COST WARNING: This tool makes an API call to Whissle which may incur costs. Only use when explicitly requested by the user.

Args:
    audio_file_path (str): Path to the audio file to transcribe
    model_name (str, optional): The name of the ASR model to use. Defaults to "en-NER"
    max_speakers (int, optional): Maximum number of speakers to identify
    boosted_lm_words (List[str], optional): Words to boost in recognition
    boosted_lm_score (int, optional): Score for boosted words (0-100)
    output_directory (str, optional): Directory where files should be saved.
        Defaults to $HOME/Desktop if not provided.

Returns:
    TextContent with the diarized transcription and path to the output file.

Input Schema

Name	Required	Default
`audio_file_path`	Yes
`boosted_lm_score`	No
`boosted_lm_words`	No
`max_speakers`	No
`model_name`	No	en-NER

Input Schema (JSON Schema)

{
  "properties": {
    "audio_file_path": {
      "title": "Audio File Path",
      "type": "string"
    },
    "boosted_lm_score": {
      "default": 80,
      "title": "Boosted Lm Score",
      "type": "integer"
    },
    "boosted_lm_words": {
      "default": null,
      "items": {
        "type": "string"
      },
      "title": "Boosted Lm Words",
      "type": "array"
    },
    "max_speakers": {
      "default": 2,
      "title": "Max Speakers",
      "type": "integer"
    },
    "model_name": {
      "default": "en-NER",
      "title": "Model Name",
      "type": "string"
    }
  },
  "required": [
    "audio_file_path"
  ],
  "title": "diarize_speechArguments",
  "type": "object"
}

Whissle MCP Server

diarize_speech

Instructions

Input Schema

Input Schema (JSON Schema)

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