Cheetah

Made in Vancouver, Canada by Picovoice

Cheetah is an on-device streaming speech-to-text engine. Cheetah is:

• Private; All voice processing runs locally.
• Accurate
• Compact and Computationally-Efficient
• Cross-Platform:
  • Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64, arm64)
  • Android and iOS
  • Chrome, Safari, Firefox, and Edge
  • Raspberry Pi (3, 4, 5)

Table of Contents

• Cheetah
  • Table of Contents
  • AccessKey
  • Language Support
  • Demos
    • Python
    • C
    • iOS
    • Android
    • Flutter
    • React Native
    • Java
    • Node.js
    • .Net
    • Web
    • Vanilla JavaScript and HTML
    • React
  • SDKs
    • Python
    • C
    • iOS
    • Android
    • Flutter
    • React Native
    • Node.js
    • Java
    • .Net
    • Web
    • Vanilla JavaScript and HTML (ES Modules)
    • React
  • Releases

AccessKey

AccessKey is your authentication and authorization token for deploying Picovoice SDKs, including Cheetah. Anyone who is using Picovoice needs to have a valid AccessKey. You must keep your AccessKey secret. You would need internet connectivity to validate your AccessKey with Picovoice license servers even though the voice recognition is running 100% offline.

AccessKey also verifies that your usage is within the limits of your account. You can see your usage limits and real-time usage on your Picovoice Console Profile. To get, renew or adjust your usage limits, please reach out to our Enterprise Sales Team or your existing Picovoice contact.

Language Support

• Cheetah Streaming Speech-to-Text currently supports English, French, German, Italian, Portuguese, and Spanish.
• Support for additional languages is available for commercial customers on a case-by-case basis.

Demos

Python Demos

Install the demo package:

pip3 install pvcheetahdemo

cheetah_demo_mic --access_key ${ACCESS_KEY}

Replace ${ACCESS_KEY} with yours obtained from Picovoice Console.

C Demos

If using SSH, clone the repository with:

git clone --recurse-submodules git@github.com:Picovoice/cheetah.git

If using HTTPS, clone the repository with:

git clone --recurse-submodules https://github.com/Picovoice/cheetah.git

Build the demo:

cmake -S demo/c/ -B demo/c/build && cmake --build demo/c/build

Run the demo:

./demo/c/build/cheetah_demo_mic -a ${ACCESS_KEY} -m ${MODEL_PATH} -l ${LIBRARY_PATH}

Replace ${ACCESS_KEY} with yours obtained from Picovoice Console, ${LIBRARY_PATH} with the path to appropriate library under lib, and ${MODEL_PATH} to path to default model file (or your custom one).

iOS Demos

To run the demo, go to demo/ios/CheetahDemo and run:

pod install

Replace let accessKey = "${YOUR_ACCESS_KEY_HERE}" in the file ViewModel.swift with your AccessKey.

Then, using Xcode, open the generated CheetahDemo.xcworkspace and run the application.

Android Demo

Using Android Studio, open demo/android/CheetahDemo as an Android project and then run the application.

Replace "${YOUR_ACCESS_KEY_HERE}" in the file MainActivity.java with your AccessKey.

Flutter Demo

To run the Cheetah demo on Android or iOS with Flutter, you must have the Flutter SDK installed on your system. Once installed, you can run flutter doctor to determine any other missing requirements for your relevant platform. Once your environment has been set up, launch a simulator or connect an Android/iOS device.

Run the prepare_demo script from demo/flutter with a language code to set up the demo in the language of your choice (e.g. de -> German, ko -> Korean). To see a list of available languages, run prepare_demo without a language code.

dart scripts/prepare_demo.dart ${LANGUAGE}

Replace "${YOUR_ACCESS_KEY_HERE}" in the file main.dart with your AccessKey.

Run the following command from demo/flutter to build and deploy the demo to your device:

flutter run

React Native Demo

To run the React Native Cheetah demo app you will first need to set up your React Native environment. For this, please refer to React Native's documentation. Once your environment has been set up, navigate to demo/react-native/CheetahDemo to run the following commands:

For Android:

yarn android-install          # sets up environment
yarn android-run ${LANGUAGE}  # builds and deploys to Android

For iOS:

yarn ios-install              # sets up environment
yarn ios-run ${LANGUAGE}      # builds and deploys to iOS

Node.js Demo

Install the demo package:

yarn global add @picovoice/cheetah-node-demo

With a working microphone connected to your device, run the following in the terminal:

cheetah-mic-demo --access_key ${ACCESS_KEY}

For more information about Node.js demos go to demo/nodejs.

Java Demos

The Cheetah Java demo is a command-line application that lets you choose between running Cheetah on an audio file or on real-time microphone input.

To try the real-time demo, make sure there is a working microphone connected to your device. Then invoke the following commands from the terminal:

cd demo/java
./gradlew build
cd build/libs
java -jar cheetah-mic-demo.jar -a ${ACCESS_KEY}

For more information about Java demos go to demo/java.

.NET Demo

Cheetah .NET demo is a command-line application that lets you choose between running Cheetah on an audio file or on real-time microphone input.

Make sure there is a working microphone connected to your device. From demo/dotnet/CheetahDemo run the following in the terminal:

dotnet run -c MicDemo.Release -- --access_key ${ACCESS_KEY}

Replace ${ACCESS_KEY} with your Picovoice AccessKey.

For more information about .NET demos, go to demo/dotnet.

Web Demos

Vanilla JavaScript and HTML

From demo/web run the following in the terminal:

yarn
yarn start

(or)

npm install
npm run start

Open http://localhost:5000 in your browser to try the demo.

React Demo

From demo/react run the following in the terminal:

yarn
yarn start

(or)

npm install
npm run start

Open http://localhost:3000 in your browser to try the demo.

SDKs

Python

Install the Python SDK:

pip3 install pvcheetah

Create an instance of the engine and transcribe audio in real-time:

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.

To get word-level metadata, use the annotated API:

import pvcheetah

handle = pvcheetah.create(access_key='${ACCESS_KEY}')

def get_next_audio_frame():
    pass

while True:
    partial_output = handle.process_annotated(get_next_audio_frame())

    partial_transcript = partial_output.transcript
    partial_words = partial_output.words
    is_endpoint = partial_output.is_endpoint

    if is_endpoint:
        final_output = handle.flush_annotated()
        final_transcript = final_output.transcript
        final_words = final_output.words

C

Create an instance of the engine and transcribe audio in real-time:

#include <stdbool.h>
#include <stdio.h>
#include <stdlib.h>

#include "pv_cheetah.h"

pv_cheetah_t *handle = NULL;
const pv_status_t status = pv_cheetah_init("${ACCESS_KEY}", "${MODEL_PATH}", "${DEVICE}", 0.f, false, false, &handle);
if (status != PV_STATUS_SUCCESS) {
    // error handling logic
}

extern const int16_t *get_next_audio_frame(void);

while (true) {
    char *partial_transcript = NULL;
    int32_t partial_num_words = 0;
    pv_word_t *partial_words = NULL;
    bool is_endpoint = false;
    const pv_status_t status = pv_cheetah_process(
            handle,
            get_next_audio_frame(),
            &partial_transcript,
            &partial_num_words,
            &partial_words,
            &is_endpoint);
    if (status != PV_STATUS_SUCCESS) {
        // error handling logic
    }
    // do something with transcript
    pv_cheetah_transcript_delete(partial_transcript);
    pv_cheetah_words_delete(partial_num_words, partial_words);
    if (is_endpoint) {
        char *final_transcript = NULL;
        int32_t final_num_words = 0;
        pv_word_t *final_words = NULL;
        const pv_status_t status = pv_cheetah_flush(handle, &final_transcript, &final_num_words, &final_words);
        if (status != PV_STATUS_SUCCESS) {
            // error handling logic
        }
        // do something with transcript
        pv_cheetah_transcript_delete(final_transcript);
        pv_cheetah_words_delete(final_num_words, final_words);
    }
}

Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and ${MODEL_PATH} to path to default model file (or your custom one). Finally, when done be sure to release resources acquired using pv_cheetah_delete(handle).

iOS

The Cheetah iOS binding is available via CocoaPods. To import it into your iOS project, add the following line to your Podfile and run pod install:

pod 'Cheetah-iOS'

Create an instance of the engine and transcribe audio in real-time:

import Cheetah

let modelPath = Bundle(for: type(of: self)).path(
        forResource: "${MODEL_FILE}", // Name of the model file name for Cheetah
        ofType: "pv")!

let cheetah = Cheetah(accessKey: "${ACCESS_KEY}", modelPath: modelPath)

func getNextAudioFrame() -> [Int16] {
  // .. get audioFrame
  return audioFrame;
}

while true {
  do {
    let partialTranscript, isEndpoint = try cheetah.process(getNetAudioFrame())
    if isEndpoint {
      let finalTranscript = try cheetah.flush()
    }
  } catch let error as CheetahError {
      // handle error
  } catch { }
}

Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and ${MODEL_FILE} with a custom trained model from Picovoice Console or the [default model](