# Cheetah Binding for Python
## Cheetah Speech-to-Text Engine
Made in Vancouver, Canada by [Picovoice](https://picovoice.ai)
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 pvcheetah
```
## 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
Create an instance of the engine and transcribe audio:
```python
import pvcheetah
handle = pvcheetah.create(access_key='${ACCESS_KEY}')
def get_next_audio_frame():
pass
while True:
partial_transcript, is_endpoint = handle.process(get_next_audio_frame())
if is_endpoint:
final_transcript = handle.flush()
```
Replace `${ACCESS_KEY}` with yours obtained from [Picovoice Console](https://console.picovoice.ai/). When done be sure
to explicitly release the resources using `handle.delete()`.
### Language Model
The Cheetah Python SDK comes preloaded with a default English language model (`.pv` file).
Default models for other supported languages can be found in [lib/common](../../lib/common).
Create custom language models using the [Picovoice Console](https://console.picovoice.ai/). Here you can train
language models with custom vocabulary and boost words in the existing vocabulary.
Pass in the `.pv` file via the `model_path` argument:
```python
cheetah = pvcheetah.create(
access_key='${ACCESS_KEY}',
model_path='${MODEL_FILE_PATH}')
```
## Demos
[pvcheetahdemo](https://pypi.org/project/pvcheetahdemo/) provides command-line utilities for processing audio using
Cheetah.
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"description": "# Cheetah Binding for Python\n\n## Cheetah Speech-to-Text Engine\n\nMade in Vancouver, Canada by [Picovoice](https://picovoice.ai)\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 pvcheetah\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\nCreate an instance of the engine and transcribe audio:\n\n```python\nimport pvcheetah\n\nhandle = pvcheetah.create(access_key='${ACCESS_KEY}')\n\ndef get_next_audio_frame():\n pass\n\nwhile True:\n partial_transcript, is_endpoint = handle.process(get_next_audio_frame())\n if is_endpoint:\n final_transcript = handle.flush()\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from [Picovoice Console](https://console.picovoice.ai/). When done be sure\nto explicitly release the resources using `handle.delete()`.\n\n### Language Model\n\nThe Cheetah Python SDK comes preloaded with a default English language model (`.pv` file).\nDefault models for other supported languages can be found in [lib/common](../../lib/common).\n\nCreate custom language models using the [Picovoice Console](https://console.picovoice.ai/). Here you can train\nlanguage models with custom vocabulary and boost words in the existing vocabulary.\n\nPass in the `.pv` file via the `model_path` argument:\n```python\ncheetah = pvcheetah.create(\n access_key='${ACCESS_KEY}',\n model_path='${MODEL_FILE_PATH}')\n```\n\n## Demos\n\n[pvcheetahdemo](https://pypi.org/project/pvcheetahdemo/) provides command-line utilities for processing audio using\nCheetah.\n",
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