agent:
  name: whisperx_asr_diarization
templates:
- template_name: InputTemplate
  class_name: InputTemplate
  attributes: {}
- template_name: WhisperxDiarizedTranscription
  class_name: WhisperxDiarizedTranscription
  template_input: InputTemplate
  attributes:
    root_dir: path_to_root_dir
    audio_file_path: audio_sample.mp3
    asr_model_name: large-v3
    device: cuda
    sample_rate: 16000
    chunk_size_in_secs: 20
    min_speakers: 2
    max_speakers: 2

Transcribe an audio file using a single ASR engine.

Run using uv run sinapsis-asr

Example: uv run sinapsis-asr --audio "path to audio" --model parakeet --chunk-size-in-secs 20 --device cuda

This command has the following options:

--audio AUDIO_PATH       Path to audio (required)
--model MODEL            Type of model to run (required)
--device DEVICE          Device to run the model (required)
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--model-name MODEL_NAME  Name of model to use
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR  Output directory for results

Models

• "parakeet"
• "canary"

Model names

• Parakeet:

  • "nvidia/parakeet-tdt-0.6b-v2"
  • "nvidia/parakeet-tdt-0.6b-v3"

• Canary:

  • "nvidia/canary-qwen-2.5b"

Device options

• "cuda"
• "cpu"

Identify speakers and their turn times in an audio file using a single diarization engine.

Run using uv run sinapsis-diarize

Example: uv run sinapsis-diarize --audio "path to audio" --model sortformer --chunk-size-in-secs 20 --device cuda

This command has the following options:

--audio AUDIO_PATH       Path to audio (required)
--model MODEL            Type of model to run (required)
--device DEVICE          Device to run the model (required)
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--model-name MODEL_NAME  Name of model to use
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR  Output directory for results

Models

• "sortformer"
• "pyannote"

Model names

• Sortformer:

  • "nvidia/diar_streaming_sortformer_4spk-v2.1"

• Pyannote:

  • "pyannote/speaker-diarization-community-1"

Device options

• "cuda"
• "cpu"

Transcribe and diarize an audio file by composing separate ASR and diarization engines. Produces a speaker-attributed transcript.

Run using uv run sinapsis-asr-diarize

Example:

uv run sinapsis-asr-diarize --audio "path to audio" --asr-model parakeet --diarization-model sortformer --chunk-size-in-secs 20 --device cuda

This command has the following options:

--audio AUDIO_PATH       Path to audio (required)
--asr-model ASR_MODEL    Type of ASR model to run (required)
--diarization-model DIARIZATION_MODEL Type of Diarization model to run (required)
--device DEVICE          Device to run the model (required)
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--asr-model-name ASR_MODEL_NAME Name of ASR model to use
--diarization-model-name DIARIZATION_MODEL_NAME Name of Diarization model to use
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR  Output directory for results
--num-speakers NUM_SPEAKERS Number of speakers for models that require it

ASR Models

• "parakeet"
• "canary"

Diarization Models

• "sortformer"
• "pyannote"

Model names

• Parakeet:

  • "nvidia/parakeet-tdt-0.6b-v2"
  • "nvidia/parakeet-tdt-0.6b-v3"

• Canary:

  • "nvidia/canary-qwen-2.5b"

• Sortformer:

  • "nvidia/diar_streaming_sortformer_4spk-v2.1"

• Pyannote:

  • "pyannote/speaker-diarization-community-1"

Device options

• "cuda"
• "cpu"

Transcribe and diarize an audio file using the WhisperX monolithic pipeline. Unlike sinapsis-asr-diarize, this uses a single model for both ASR and diarization.

Run using uv run sinapsis-whisperx-asr-diarize

Example:

uv run sinapsis-whisperx-asr-diarize --audio "path to audio" --model-name large-v3 --chunk-size-in-secs 20 --device cuda

This command has the following options:

--audio AUDIO_PATH       Path to audio (required)
--model-name MODEL       WhisperX model size (required)
--device DEVICE          Device to run the model (required)
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR  Output directory for results
--min-speakers MIN_SPEAKERS Minimum number of speakers
--max-speakers MAX_SPEAKERS Maximum number of speakers

Model names

• "tiny"
• "base"
• "small"
• "medium"
• "large-v1"
• "large-v2"
• "large-v3"

Device options

• "cuda"
• "cpu"

Transcribe, diarize, and detect emotions in an audio file. Composes ASR, diarization, and emotion detection engines to produce a speaker-attributed transcript with per-segment emotions.

Run using uv run sinapsis-asr-diarize-emotion

Example:

uv run sinapsis-asr-diarize-emotion --audio "path to audio" --asr-model parakeet --diarization-model sortformer --emotion-model speechbrain --chunk-size-in-secs 20 --device cuda

This command has the following options:

--audio AUDIO_PATH       Path to audio (required)
--asr-model ASR_MODEL    Type of ASR model to run (required)
--diarization-model DIARIZATION_MODEL Type of Diarization model to run (required)
--emotion-model EMOTION_MODEL Type of Emotion model to run (required)
--device DEVICE          Device to run the model (required)
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--asr-model-name ASR_MODEL_NAME Name of ASR model to use
--diarization-model-name DIARIZATION_MODEL_NAME Name of Diarization model to use
--emotion-model-name EMOTION_MODEL_NAME Name of emotion model to use
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR  Output directory for results
--num-speakers NUM_SPEAKERS Number of speakers for models that require it

ASR Models

• "parakeet"
• "canary"

Diarization Models

• "sortformer"
• "pyannote"

Emotion Models

• "speechbrain"

Model names

• Parakeet:

  • "nvidia/parakeet-tdt-0.6b-v2"
  • "nvidia/parakeet-tdt-0.6b-v3"

• Canary:

  • "nvidia/canary-qwen-2.5b"

• Sortformer:

  • "nvidia/diar_streaming_sortformer_4spk-v2.1"

• Pyannote:

  • "pyannote/speaker-diarization-community-1"

Device options

• "cuda"
• "cpu"