Leopard

Made in Vancouver, Canada by Picovoice

Leopard is an on-device speech-to-text engine. Leopard is:

offline and runs locally without an internet connection. Nothing is sent to cloud to fully protect users' privacy.
compact and computationally-efficient making it suitable for IoT applications.
highly-accurate.
cross-platform. Raspberry Pi, Beagle Bone, Android, iOS, Linux (x86_64), Mac, Windows (x86_64), and Web Browsers (WebAssembly) are supported. Linux (x86_64) is available for personal and non-commercial use free of charge. Other platforms are only available under commercial license.
customizable. Allows adding new words and adapting to different contexts (Available only under commercial license).

License

This repository is provided for non-commercial use only. Please refer to LICENSE for details. The license file in this repository is time-limited. Picovoice assures that the license is valid for at least 30 days at any given time.

If you wish to use Leopard in a commercial product request access here. The following table depicts the feature comparison between the free and commercial versions:

	Free	Commercial
Non-Commercial Use	Yes	Yes
Commercial Use	No	Yes
Supported Platforms	Ubuntu (x86_64)	Linux (x86_64), Mac, Windows (x86_64), iOS, Android, Raspberry Pi, Beagle Bone, and modern Web Browsers.
Custom Language Models	No	Yes
Compact Language Models	No	Yes
Support	Community Support	Enterprise Support

Structure of Repository

Leopard is shipped as an ANSI C shared library. The binary files for supported platforms are located under lib and header files are at include. Bindings are available at binding to facilitate usage from higher-level languages/platforms. Demo applications are at demo. When possible, use one of the demo applications as a starting point for your own implementation. Finally, resources is a placeholder for data used by various applications within the repository.

Running Demo Applications

Python Demo Application

The demo transcribes a set of audio files provided as command line arguments. The demo has been tested using Python 3.6. Note that the files need to be single-channel, 16KHz, and 16-bit linearly-encoded. For more information about audio requirements refer to pv_leopard.h. The following transcribes the WAV file located in the resource directory.

python demo/python/leopard_demo.py --audio_paths resources/audio_samples/test.wav

In order to transcribe multiple files concatenate their paths using comma as below.

python demo/python/leopard_demo.py --audio_paths PATH_TO_AUDIO_FILE_1,PATH_TO_AUDIO_FILE_2,PATH_TO_AUDIO_FILE_3

C Demo Application

This demo application accepts a set of WAV files as input and returns their transcripts. Note that the demo expects the audio files to be WAV, 16KHz, and 16-bit linearly-encoded. It does not perform any verification to assure the compatibility or correctness of the input audio files. Set the current working directory to the root of the repository. The demo can be built using gcc as below.

gcc -I include/ -O3 demo/c/leopard_demo.c -ldl -o leopard_demo

The usage can be attained by

./leopard_demo

Then it can be used as follows

./leopard_demo \
./lib/linux/x86_64/libpv_leopard.so \
./lib/common/acoustic_model.pv \
./lib/common/language_model.pv \
./resources/license/leopard_eval_linux.lic \
./resources/audio_samples/test.wav

In order to transcribe multiple files, append the absolute path to each additional file to the list of command line arguments as follows:

./leopard_demo \
./lib/linux/x86_64/libpv_leopard.so \
./lib/common/acoustic_model.pv \
./lib/common/language_model.pv \
./resources/license/leopard_eval_linux.lic \
PATH_TO_AUDIO_FILE_1 PATH_TO_AUDIO_FILE_2 PATH_TO_AUDIO_FILE_3

Integration

Python

leopard.py provides a Python binding for Leopard library. Below is a quick demonstration of how to construct an instance of it.

library_path = ... # The file is available under lib/linux/x86_64/libpv_leopard.so
acoustic_model_path = ... # The file is available under lib/common/acoustic_model.pv
language_model_path = ... # The file is available under lib/common/language_model.pv
license_path = ... # The file is available under resources/license/leopard_eval_linux.lic

handle = Leopard(library_path, acoustic_model_path, language_model_path, license_path)

When initialized, valid sample rate can be obtained using handle.sample_rate.

audio = ... # audio data to be transcribed

transcript = handle.process(audio)

When finished, release the acquired resources.

handle.delete()

C

Leopard is implemented in ANSI C and therefore can be directly linked to C applications. pv_leopard.h header file contains relevant information. An instance of Leopard object can be constructed as follows.

const char *acoustic_model_path = ... // The file is available under lib/common/acoustic_model.pv
const char *language_model_path = ... // The file is available under lib/common/language_model.pv
const char *license_path = ... // The file is available under resources/license/leopard_eval_linux.lic

pv_leopard_t *handle;
const pv_status_t status = pv_leopard_init(
    acoustic_model_path,
    language_model_path,
    license_path,
    &handle);
if (status != PV_STATUS_SUCCESS) {
    // error handling logic
}

Now the handle can be used to process audio. Leopard accepts single-channel 16-bit PCM audio. The sample rate can be retrieved using pv_sample_rate().

const int16_t *audio = ... // audio data to be transcribed
const int audio_length = ... // number of samples in audio

char *transcript;
const pv_status_t status = pv_leopard_process(handle, audio, audio_length, &transcript);
if (status != PV_STATUS_SUCCESS) {
    // error handling logic
}

free(transcript);

Finally, when done be sure to release resources acquired.

pv_leopard_delete(handle);

Releases

V1.0.0 — January 14th, 2020

Initial release.

boukeversteegh/leopard