Skip to main content

Audio diarization with nvidias nemo

Project description

sp




Sinapsis Diarization

Templates for Automatic Speech Recognition, Diarization and Emotion Recognition.

🐍 Installation🚀 Features📚 Example usageCLI 📙 Documentation🔍 License

The sinapsis-diarization module provides templates for real-time facial recognition with RetinaFace and DeepFace, enabling efficient and accurate inference.

🐍 Installation

Install using your package manager of choice. We encourage the use of uv

uv pip install sinapsis-diarization

or wiht raw pip

pip install sinapsis-diarization

[!IMPORTANT] Templates in sinapsis-diarization package may require extra dependencies. For development, we recommend installing the package with all the optional dependencies:

uv pip install sinapsis-diarization[all] --extra-index-url https://pypi.sinapsis.tech

or

pip install sinapsis-diarization[all] --extra-index-url https://pypi.sinapsis.tech

[!IMPORTANT] Templates in sinapsis-diarization package may require a Huggingface Token. Set the environment variable for Hugginface using export HF_TOKEN="your_huggingface_token"

🚀 Features

Templates Supported

The Sinapsis Diarization module provides multiple templates for Automatic Speech Recognition, Diarization and Emotion Recognition.

  • SinapsisParakeetASR: Runs Parakeet speech recognition for audio transcription.
  • SinapsisCanaryASR: Runs Canary speech recognition for audio transcription
  • SinapsisSortformerDiarizer: Runs Sortformer to get diarization of the speakers in an audio.
  • SinapsisPyannoteDiarizer: Runs Pyannote to get diarization of speakers in an audio.
  • ParakeetPyannoteASRDiarization: Runs Parakeet and Pyannote to transcribe an audio and divide it by speaker and time.
  • ParakeetSortformerASRDiarization: Runs parakeet and Sortformer to transcribe an audio and divide it by speaker and time.
  • ParakeetPyannoteSpeechbrainASREmotionDiarization: Runs Parakeet, Pyannote and Speechbrain to transcribe an audio, divide it by speaker and assign emotions to the segments.
  • ParakeetSortformerSpeechbrainASREmotionDiarization: Runs Parakeet, Sortformer and Speechbrain to transcribe an audio, divide it by speaker and assign emotions to the segments.
  • SinapsisWhisperxASRDiarization: Runs Whisperx to transcribe an audio and divide it by speaker and time.

📚 Example usage

The following example demonstrates how to use the SinapsisWhisperxASRDiarization template for diarization.

This configuration defines an agent and a sequence of templates to run diarization with Whisperx. Provide an audio that you wish to transcribe at the audio_file_path attribute and choose one of the available models that fits your setup. ("tiny", "base", "small", "medium", "large-v1", "large-v2", "large-v2"). Pick a maximum and minimum number of speakers. This config also allows for the audio to be divided in chunks of n seconds for easier processing.

Config file
agent:
  name: whisperx_asr_diarization
templates:
- template_name: InputTemplate
  class_name: InputTemplate
  attributes: {}
- template_name: SinapsisWhisperxASRDiarization
  class_name: SinapsisWhisperxASRDiarization
  template_input: InputTemplate
  attributes:
    audio_file_path: path to audio file
    asr_model_name: large-v3
    device: cuda
    sample_rate: 16000
    chunk_size_in_secs: -1
    min_speakers: 2
    max_speakers: 2

To run the agent, you should run:

sinapsis run /path/to/sinapsis-diarization/src/sinapsis_diarization/configs/transcription_with_diarization/whisperx_asr_diarization.yml

📙 CLI

The pipelines for ASR, Diarization en Emotion diarization are available as CLI commands that take an audio and model options as input, and then transcribe/diarize the results in a given output directory (by default results):

Sinapsis ASR

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
--model MODEL Type of model to run
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--model-name MODEL_NAMEName of model to use
--device DEVICE Device to run the model
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR Output directory for transcription

Models

  • "parakeet"
  • "canary"

Model names

  • Parakeet:

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

    • "nvidia/parakeet-tdt-0.6b-v2"

Device options

  • "cuda"
  • "cpu"
Sinapsis Diarize

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

Models

  • "sortformer"
  • "pyannote"

Model names

  • Sortformer:

    • "nvidia/diar_streaming_sortformer_4spk-v2.1"
  • Pyannote:

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

Device options

  • "cuda"
  • "cpu"
Sinapsis ASR Diarize

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
--asr-model ASR_MODEL Type of ASR model to run
--diarization-model DIARIZATION_MODEL Type of Diarization model to run
--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 DIARIZATIN_MODEL_NAME Name of Diarization model to use
--device DEVICE Device to run the model
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR Output directory for transcription
--num-speakers NUM_SPEAKERS Number of speakers for models that require it

ASR Models

  • "sortformer"
  • "pyannote"

Diarization Models

  • "sortformer"
  • "pyannote"

Model names

  • Parakeet:

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

    • "nvidia/parakeet-tdt-0.6b-v2"
  • Sortformer:

    • "nvidia/diar_streaming_sortformer_4spk-v2.1"
  • Pyannote:

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

Device options

  • "cuda"
  • "cpu"
Sinapsis Whisperx ASR Diarize

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
--model-name MODEL Type of ASR model to run
--chunk-size-in-secs CHUNK_SIZE Size of chunks in seconds
--device DEVICE Device to run the model
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR Output directory for transcription
--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"
Sinapsis ASR Diarize Emotion

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 --chunk-size-in-secs 20 --device cuda

This command has the following options:

--audio AUDIO_PATH Path to audio
--asr-model ASR_MODEL Type of ASR model to run
--diarization-model DIARIZATION_MODEL Type of Diarization model to run
--emotion-model EMOTION_MODEL Type of Emotion model to run
--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 DIARIZATIN_MODEL_NAME Name of Diarization model to use
--device DEVICE Device to run the model
--sample-rate SAMPLE_RATE Sample rate of audio
--output-dir OUTPUT_DIR Output directory for transcription
--num-speakers NUM_SPEAKERS Number of speakers for models that require it

ASR Models

  • "sortformer"
  • "pyannote"

Diarization Models

  • "sortformer"
  • "pyannote"

Emotion Models

  • "speechbrain"

Model names

  • Parakeet:

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

    • "nvidia/parakeet-tdt-0.6b-v2"
  • Sortformer:

    • "nvidia/diar_streaming_sortformer_4spk-v2.1"
  • Pyannote:

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

Device options

  • "cuda"
  • "cpu"

📙 Documentation

Documentation is available on the sinapsis website

Tutorials for different projects within sinapsis are available at sinapsis tutorials page

🔍 License

The templates in this project are licensed under the AGPLv3 license, which encourages open collaboration and sharing. For more details, please refer to the LICENSE file.

The command line interface and pipelines in this project are licensed under the MIT license, which allows for unrestricted use of the software and encourages open collaboration. For more details please refer to the LICENSE file

For commercial use, please refer to our official Sinapsis website for information on obtaining a commercial license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sinapsis_diarization-0.1.2.tar.gz (39.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sinapsis_diarization-0.1.2-py3-none-any.whl (56.2 kB view details)

Uploaded Python 3

File details

Details for the file sinapsis_diarization-0.1.2.tar.gz.

File metadata

File hashes

Hashes for sinapsis_diarization-0.1.2.tar.gz
Algorithm Hash digest
SHA256 6a6ea3a12ea1e71f0d95250830c63bcea1edbae7a54b2dd2576e42c0d9524fe8
MD5 3f0799f8ec12efe10cfa76364fa885ba
BLAKE2b-256 757aa494000cae1ce7ce90dad5728658f0119c3eb7d98159ebffa2dc77dccf2f

See more details on using hashes here.

File details

Details for the file sinapsis_diarization-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for sinapsis_diarization-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 d70611dfe7a05cea136611a6eb1acb009e27efc4373c814640ffbd8a0da35ff7
MD5 95dbd03ee10414e898e5e6868d52cca1
BLAKE2b-256 e5c9634ba124cabdba295b9669a5413cbe12fbd06fd9c7ac1a53e3d654bfb3aa

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page