# Falcon Binding for Python
## Falcon Speaker Diarization Engine
Made in Vancouver, Canada by [Picovoice](https://picovoice.ai)
Falcon is an on-device speaker diarization engine. Falcon is:
- Private; All voice processing runs locally.
- Cross-Platform:
- Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64)
- Raspberry Pi (4, 3) and NVIDIA Jetson Nano
## Compatibility
- Python 3.7+
- Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (4, 3), and NVIDIA Jetson Nano.
## Installation
```console
pip3 install pvfalcon
```
## AccessKey
Falcon requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Falcon SDKs.
You can get your `AccessKey` for free. Make sure to keep your `AccessKey` secret.
Signup or Login to [Picovoice Console](https://console.picovoice.ai/) to get your `AccessKey`.
### Usage
Create an instance of the engine and perform speaker diarization on an audio file:
```python
import pvfalcon
handle = pvfalcon.create(access_key='${ACCESS_KEY}')
segments = handle.process_file('${AUDIO_PATH}')
for segment in segments:
print("{speaker tag=%d - start_sec=%.2f end_sec=%.2f}"
% (segment.speaker_tag, segment.start_sec, segment.end_sec))
```
Replace `${ACCESS_KEY}` with yours obtained from [Picovoice Console](https://console.picovoice.ai/) and
`${AUDIO_PATH}` to the path an audio file. Finally, when done be sure to explicitly release the resources using
`handle.delete()`.
## Demos
[pvfalcondemo](https://pypi.org/project/pvfalcondemo/) provides command-line utilities for processing audio using
Falcon.
Raw data
{
"_id": null,
"home_page": "https://github.com/Picovoice/falcon",
"name": "pvfalcon",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "Speaker Diarization,Speaker Identification,Voice Identification",
"author": "Picovoice",
"author_email": "hello@picovoice.ai",
"download_url": "https://files.pythonhosted.org/packages/f6/00/9b14a3d3c5c885005ab1d8d9a8776656eeef17997a3c0dce4ae438172e55/pvfalcon-1.0.1.tar.gz",
"platform": null,
"description": "# Falcon Binding for Python\n\n## Falcon Speaker Diarization Engine\n\nMade in Vancouver, Canada by [Picovoice](https://picovoice.ai)\n\nFalcon is an on-device speaker diarization engine. Falcon is:\n\n- Private; All voice processing runs locally.\n- Cross-Platform:\n - Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64)\n - Raspberry Pi (4, 3) and NVIDIA Jetson Nano\n\n## Compatibility\n\n- Python 3.7+\n- Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (4, 3), and NVIDIA Jetson Nano.\n\n## Installation\n\n```console\npip3 install pvfalcon\n```\n\n## AccessKey\n\nFalcon requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Falcon SDKs.\nYou can get your `AccessKey` for free. Make sure to keep your `AccessKey` secret.\nSignup or Login to [Picovoice Console](https://console.picovoice.ai/) to get your `AccessKey`.\n\n### Usage\n\nCreate an instance of the engine and perform speaker diarization on an audio file:\n\n```python\nimport pvfalcon\n\nhandle = pvfalcon.create(access_key='${ACCESS_KEY}')\n\nsegments = handle.process_file('${AUDIO_PATH}')\nfor segment in segments:\n print(\"{speaker tag=%d - start_sec=%.2f end_sec=%.2f}\" \n % (segment.speaker_tag, segment.start_sec, segment.end_sec))\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from [Picovoice Console](https://console.picovoice.ai/) and\n`${AUDIO_PATH}` to the path an audio file. Finally, when done be sure to explicitly release the resources using\n`handle.delete()`.\n\n## Demos\n\n[pvfalcondemo](https://pypi.org/project/pvfalcondemo/) provides command-line utilities for processing audio using\nFalcon.\n",
"bugtrack_url": null,
"license": "",
"summary": "Falcon Speaker Diarization Engine",
"version": "1.0.1",
"project_urls": {
"Homepage": "https://github.com/Picovoice/falcon"
},
"split_keywords": [
"speaker diarization",
"speaker identification",
"voice identification"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "70d4f96b7b0f64230c6f965aa273097a73fc91bf88b4269f661f632be28577fb",
"md5": "00fc0fa40303b2bb7961df4e76e2a7e0",
"sha256": "a1b631142c94734ed0a2e7eaaed794bf272d6205524e11513d4304256ee4dce6"
},
"downloads": -1,
"filename": "pvfalcon-1.0.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "00fc0fa40303b2bb7961df4e76e2a7e0",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 14670093,
"upload_time": "2024-02-05T18:31:04",
"upload_time_iso_8601": "2024-02-05T18:31:04.102116Z",
"url": "https://files.pythonhosted.org/packages/70/d4/f96b7b0f64230c6f965aa273097a73fc91bf88b4269f661f632be28577fb/pvfalcon-1.0.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "f6009b14a3d3c5c885005ab1d8d9a8776656eeef17997a3c0dce4ae438172e55",
"md5": "f7e7fbb84b4405e6c0887adc5d3d9b66",
"sha256": "a03f890efe846eaea72dac1c55bff56be97fd933bdd5cced5d2e8465293f31d7"
},
"downloads": -1,
"filename": "pvfalcon-1.0.1.tar.gz",
"has_sig": false,
"md5_digest": "f7e7fbb84b4405e6c0887adc5d3d9b66",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 14664378,
"upload_time": "2024-02-05T18:31:08",
"upload_time_iso_8601": "2024-02-05T18:31:08.296657Z",
"url": "https://files.pythonhosted.org/packages/f6/00/9b14a3d3c5c885005ab1d8d9a8776656eeef17997a3c0dce4ae438172e55/pvfalcon-1.0.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-02-05 18:31:08",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Picovoice",
"github_project": "falcon",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "pvfalcon"
}