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Leopard Speech-to-Text
.NET Quick Start


Platforms

  • Linux (x86_64)
  • macOS (x86_64, arm64)
  • Windows (x86_64)
  • NVIDIA Jetson Nano
  • Raspberry Pi (3, 4)

Requirements

  • Picovoice Account & AccessKey

.NET Framework 4.6.1+ / .NET Standard 2.0+ / .NET Core 3.1+:

  • Windows (x86_64)

.NET Core 2.0+ / .NET Core 3.1+:

  • Linux (x86_64)
  • macOS (x86_64)

.NET Core 3.1+:

  • NVIDIA Jetson Nano
  • Raspberry Pi (3, 4)

.NET 6.0+:

  • macOS (arm64)

Picovoice Account & AccessKey

Signup or Login to Picovoice Console to get your AccessKey. Make sure to keep your AccessKey secret.

Quick Start

Setup

  1. Install .NET.

  2. Install the Leopard NuGet package in Visual Studio or using the .NET CLI:

dotnet add package Leopard

Usage

Create an instance of the engine:

using Pv;
const string accessKey = "${ACCESS_KEY}";
Leopard leopard = Leopard.Create(accessKey);

Transcribe an audio file by providing an absolute path to the file:

LeopardTranscript result = leopard.ProcessFile("${AUDIO_FILE_PATH}");

Transcribe raw audio data (sample rate of 16 kHz, 16-bit linearly encoded and 1 channel):

short[] GetAudioData()
{
// ...
}
LeopardTranscript result = leopard.Process(GetAudioData());

Demo

For the Leopard .NET SDK, we offer demo applications that demonstrate how to use the Speech-to-Text engine on audio files.

Setup

  1. Clone the Leopard repository from GitHub:
git clone --recurse-submodules https://github.com/Picovoice/leopard.git
  1. Build the demo:
cd leopard/demo/dotnet/Leopard
dotnet build -c FileDemo.Release

Usage

Use the --help flag to see the usage options for the demo:

dotnet run -c FileDemo.Release -- --help

Run the following command to transcribe an audio file:

dotnet run -c FileDemo.Release -- --access_key ${ACCESS_KEY}
--input_audio_path ${AUDIO_PATH}

For more information on our Leopard demos for .NET, head over to our GitHub repository.

Resources

Package

  • Leopard on NuGet

API

  • Leopard .NET API Docs

GitHub

  • Leopard .NET SDK on GitHub
  • Leopard .NET Demos on GitHub

Benchmark

  • Speech-to-Text Benchmark

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