

Sherpa Onnx
Overview :
Sherpa-onnx is a speech recognition and speech synthesis project based on the next-generation Kaldi, utilizing onnxruntime for inference. It supports a wide range of speech-related functionalities, including automatic speech recognition (ASR), text-to-speech (TTS), speaker recognition, speaker verification, language identification, and keyword detection. It is compatible with various platforms and operating systems, including embedded systems, Android, iOS, Raspberry Pi, RISC-V, and servers.
Target Users :
Sherpa-onnx is suitable for developers and researchers, especially those who need to implement speech recognition and speech synthesis functions on different platforms. It provides various APIs, including C++, C, Python, Go, C#, Java, Kotlin, JavaScript, and Swift, to accommodate developers from diverse backgrounds.
Use Cases
Use sherpa-onnx to implement real-time speech-to-text on Android devices.
Leverage sherpa-onnx for batch speech recognition tasks on servers.
Employ sherpa-onnx for keyword detection on embedded systems.
Features
Supports stream and non-stream speech recognition (ASR).
Supports text-to-speech conversion (TTS).
Supports speaker recognition.
Supports speaker verification.
Supports language identification.
Supports audio tagging and keyword detection.
Supports multiple platforms and operating systems.
How to Use
1. Clone or download the sherpa-onnx project to your local machine.
2. Select the appropriate API and platform based on your required functionalities.
3. Configure the environment and dependencies according to the documentation.
4. Load the pre-trained model and perform testing.
5. Adjust parameters according to your specific requirements to optimize performance.
6. Integrate into your application to implement speech recognition or speech synthesis functionalities.
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