# Cheetah Speech-to-Text Demos
Made in Vancouver, Canada by [Picovoice](https://picovoice.ai)
## Cheetah
Cheetah is an on-device streaming speech-to-text engine. Cheetah is:
- Private; All voice processing runs locally.
- [Accurate](https://picovoice.ai/docs/benchmark/stt/)
- [Compact and Computationally-Efficient](https://github.com/Picovoice/speech-to-text-benchmark#rtf)
- Cross-Platform:
- Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64)
- Android and iOS
- Chrome, Safari, Firefox, and Edge
- Raspberry Pi (3, 4, 5)
## Compatibility
- Python 3.8+
- Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), and Raspberry Pi (3, 4, 5).
## Installation
```console
pip3 install pvcheetahdemo
```
## AccessKey
Cheetah requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Cheetah 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
### Microphone Demo
You need a working microphone connected to your machine for this demo. Run the following in the terminal:
```console
cheetah_demo_mic --access_key ${ACCESS_KEY}
```
Replace `${ACCESS_KEY}` with yours obtained from Picovoice Console.
### File Demo
Run the following in the terminal:
```console
cheetah_demo_file --access_key ${ACCESS_KEY} --wav_paths ${WAV_PATH}
```
Replace `${ACCESS_KEY}` with yours obtained from Picovoice Console and `${WAV_PATH}` with a path to a compatible
(single-channel, 16 kHz, 16-bit PCM) wav file you wish to transcribe.
Raw data
{
"_id": null,
"home_page": "https://github.com/Picovoice/cheetah",
"name": "pvcheetahdemo",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "Speech-to-Text, ASR, Speech Recognition, Voice Recognition, Automatic Speech Recognition",
"author": "Picovoice",
"author_email": "hello@picovoice.ai",
"download_url": "https://files.pythonhosted.org/packages/6d/1f/9fe54d8cebceb949393cc9c3d43ff4e6555c13ef1175076af9aa09e21bc7/pvcheetahdemo-2.0.2.tar.gz",
"platform": null,
"description": "# Cheetah Speech-to-Text Demos\n\nMade in Vancouver, Canada by [Picovoice](https://picovoice.ai)\n\n## Cheetah\n\nCheetah is an on-device streaming speech-to-text engine. Cheetah is:\n\n- Private; All voice processing runs locally.\n- [Accurate](https://picovoice.ai/docs/benchmark/stt/)\n- [Compact and Computationally-Efficient](https://github.com/Picovoice/speech-to-text-benchmark#rtf)\n- Cross-Platform:\n - Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64)\n - Android and iOS\n - Chrome, Safari, Firefox, and Edge\n - Raspberry Pi (3, 4, 5)\n\n## Compatibility\n\n- Python 3.8+\n- Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), and Raspberry Pi (3, 4, 5).\n\n## Installation\n\n```console\npip3 install pvcheetahdemo\n```\n\n## AccessKey\n\nCheetah requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Cheetah 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\n### Microphone Demo\n\nYou need a working microphone connected to your machine for this demo. Run the following in the terminal:\n\n```console\ncheetah_demo_mic --access_key ${ACCESS_KEY}\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from Picovoice Console.\n\n### File Demo\n\nRun the following in the terminal:\n\n```console\ncheetah_demo_file --access_key ${ACCESS_KEY} --wav_paths ${WAV_PATH}\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from Picovoice Console and `${WAV_PATH}` with a path to a compatible\n(single-channel, 16 kHz, 16-bit PCM) wav file you wish to transcribe.\n",
"bugtrack_url": null,
"license": null,
"summary": "Cheetah speech-to-text engine demos",
"version": "2.0.2",
"project_urls": {
"Homepage": "https://github.com/Picovoice/cheetah"
},
"split_keywords": [
"speech-to-text",
" asr",
" speech recognition",
" voice recognition",
" automatic speech recognition"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "eb260852c664172490e7fab227e50c1d934ba33ab030538c8a91618d112f1260",
"md5": "9c5ef4c2bbce0ab1c97dd08032a868c7",
"sha256": "cc47a2217820db110567b941fdcfd919b76c0c6dd383f6ac6646bce4fa32596f"
},
"downloads": -1,
"filename": "pvcheetahdemo-2.0.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "9c5ef4c2bbce0ab1c97dd08032a868c7",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 9237,
"upload_time": "2024-09-17T23:41:38",
"upload_time_iso_8601": "2024-09-17T23:41:38.583906Z",
"url": "https://files.pythonhosted.org/packages/eb/26/0852c664172490e7fab227e50c1d934ba33ab030538c8a91618d112f1260/pvcheetahdemo-2.0.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "6d1f9fe54d8cebceb949393cc9c3d43ff4e6555c13ef1175076af9aa09e21bc7",
"md5": "6cff3ff5190a9fb498e973cb9959d33b",
"sha256": "50f2c9639003354fc722c6e2e12f62e66a4aa148f4975ca9e121ea883c8eb606"
},
"downloads": -1,
"filename": "pvcheetahdemo-2.0.2.tar.gz",
"has_sig": false,
"md5_digest": "6cff3ff5190a9fb498e973cb9959d33b",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 8251,
"upload_time": "2024-09-17T23:41:39",
"upload_time_iso_8601": "2024-09-17T23:41:39.926068Z",
"url": "https://files.pythonhosted.org/packages/6d/1f/9fe54d8cebceb949393cc9c3d43ff4e6555c13ef1175076af9aa09e21bc7/pvcheetahdemo-2.0.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-17 23:41:39",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Picovoice",
"github_project": "cheetah",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "pvcheetahdemo"
}