Made in Vancouver, Canada by Picovoice
Leopard is an on-device speech-to-text engine. Leopard is:
AccessKey is your authentication and authorization token for deploying Picovoice SDKs, including Leopard. 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. Everyone who signs up for
Picovoice Console receives the Free Tier usage rights described
here. If you wish to increase your limits, you can purchase a subscription plan.
Install the demo package:
pip3 install pvleoparddemo
Run the following in the terminal:
leopard_demo_file --access_key ${ACCESS_KEY} --audio_paths ${AUDIO_FILE_PATH}
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and ${AUDIO_FILE_PATH} with a path to an audio file you
wish to transcribe.
Build the demo:
cmake -S demo/c/ -B demo/c/build && cmake --build demo/c/build
Run the demo:
./demo/c/build/leopard_demo -a ${ACCESS_KEY} -l ${LIBRARY_PATH} -m ${MODEL_FILE_PATH} ${AUDIO_FILE_PATH}
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console, ${LIBRARY_PATH} with the path to appropriate
library under lib, ${MODEL_FILE_PATH} to path to default model file
(or your custom one), and ${AUDIO_FILE_PATH} with a path to an audio file you wish to transcribe.
To run the demo, go to demo/ios/LeopardDemo and run:
pod install
Replace let accessKey = "${YOUR_ACCESS_KEY_HERE}" in the file ViewModel.swift with your AccessKey.
Then, using Xcode, open the generated LeopardDemo.xcworkspace and run the application.
Using Android Studio, open demo/android/LeopardDemo as an Android project and then run the application.
Replace "${YOUR_ACCESS_KEY_HERE}" in the file MainActivity.java with your AccessKey.
Install the demo package:
yarn global add @picovoice/leopard-node-demo
Run the following in the terminal:
leopard-file-demo --access_key ${ACCESS_KEY} --input_audio_file_path ${AUDIO_FILE_PATH}
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and ${AUDIO_FILE_PATH} with a path to an audio file you
wish to transcribe.
For more information about Node.js demos go to demo/nodejs.
To run the Leopard 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
To run the React Native Leopard 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/LeopardDemo/src 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
The Leopard Java demo is a command-line application that lets you choose between running Leopard on an audio file or on microphone input.
From demo/java run the following commands from the terminal to build and run the file demo:
cd demo/java
./gradlew build
cd build/libs
java -jar leopard-file-demo.jar -a ${ACCESS_KEY} -i ${AUDIO_FILE_PATH}
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and ${AUDIO_FILE_PATH} with a path to an audio file you wish to transcribe.
For more information about Java demos go to demo/java.
Leopard .NET demo is a command-line application that lets you choose between running Leopard on an audio file or on real-time microphone input.
From demo/dotnet/LeopardDemo run the following in the terminal:
dotnet run -c FileDemo.Release -- --access_key ${ACCESS_KEY} --input_audio_path ${AUDIO_FILE_PATH}
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and ${AUDIO_FILE_PATH} with a path to an audio file you
wish to transcribe.
For more information about .NET demos, go to demo/dotnet.
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.
From demo/react run the following in the terminal:
yarn
yarn start ${LANGUAGE}
(or)
npm install
npm run start ${LANGUAGE}
Open http://localhost:3000 in your browser to try the demo.
Install the Python SDK:
pip3 install pvleopard
Create an instance of the engine and transcribe an audio file:
import pvleopard
leopard = pvleopard.create(access_key='${ACCESS_KEY}')
print(leopard.process_file('${AUDIO_FILE_PATH}'))
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console and
${AUDIO_FILE_PATH} to path an audio file. Finally, when done be sure to explicitly release the resources using
leopard.delete().
Create an instance of the engine and transcribe an audio file:
#include <stdbool.h>
#include <stdio.h>
#include <stdlib.h>
#include "pv_leopard.h"
pv_leopard_t *leopard = NULL;
bool enable_automatic_punctuation = false;
bool enable_speaker_diarization = false;
const char *device = "best";
pv_status_t status = pv_leopard_init(
"${ACCESS_KEY}",
"${MODEL_FILE_PATH}",
device,
enable_automatic_punctuation,
enable_speaker_diarization,
&leopard);
if (status != PV_STATUS_SUCCESS) {
// error handling logic
}
char *transcript = NULL;
int32_t num_words = 0;
pv_word_t *words = NULL;
status = pv_leopard_process_file(
leopard,
"${AUDIO_FILE_PATH}",
&transcript,
&num_words,
&words);
if (status != PV_STATUS_SUCCESS) {
// error handling logic
}
fprintf(stdout, "%s\n", transcript);
for (int32_t i = 0; i < num_words; i++) {
fprintf(
stdout,
"[%s]\t.start_sec = %.1f .end_sec = %.1f .confidence = %.2f .speaker_tag = %d\n",
words[i].word,
words[i].start_sec,
words[i].end_sec,
words[i].confidence,
words[i].speaker_tag);
}
pv_leopard_transcript_delete(transcript);
pv_leopard_words_delete(words);
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console, ${MODEL_FILE_PATH} to path to
default model file (or your custom one), and ${AUDIO_FILE_PATH} to path an audio file.
Finally, when done be sure to release resources acquired using pv_leopard_delete(leopard).
The Leopard iOS binding is available via CocoaPods. To import it into your iOS project, add the following line to your Podfile and run pod install:
pod 'Leopard-iOS'
Create an instance of the engine and transcribe an audio_file:
import Leopard
let modelPath = Bundle(for: type(of: self)).path(
forResource: "${MODEL_FILE}", // Name of the model file name for Leopard
ofType: "pv")!
let leopard = Leopard(accessKey: "${ACCESS_KEY}", modelPath: modelPath)
do {
let audioPath = Bundle(for: type(of: self)).path(forResource: "${AUDIO_FILE_NAME}", ofType: "${AUDIO_FILE_EXTENSION}")
let result = leopard.process(audioPath)
print(result.transcript)
} catch let error as LeopardError {
} catch { }
Replace ${ACCESS_KEY} with yours obtained from Picovoice Console, ${MODEL_FILE} a custom trained model from console or the default model, ${AUDIO_FILE_NAME} with the name of the audio file and ${AUDIO_FILE_EXTENSION} with the extension of the audio file.
To include the package in your Android project, ensure you have included mavenCentral() in your top-level build.gradle file and then add the following to your app's build.gradle:
dependencies {
implementation 'ai.picovoice:leopard-android:${LATEST_VERSION}'
}
Create an instance of the engine and transcribe an audio file:
```java import ai.picovoice.leopard.*;
final String accessKey = "${ACCESS_KEY}"; // AccessKey obtained from Picovoice Console (https://console.picovoice.ai/) final String mo
$ claude mcp add leopard \
-- python -m otcore.mcp_server <graph>