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This PR adds support for streaming T-one Russian ASR models across various language bindings in the sherpa-onnx library. The changes enable T-one CTC (Connectionist Temporal Classification) model integration by adding new configuration structures and example implementations. - Introduces OnlineToneCtcModelConfig structures across all language bindings (C, C++, Swift, Java, Kotlin, Go, etc.) - Adds T-one CTC model support to WASM implementations for both ASR and keyword spotting - Provides comprehensive example implementations demonstrating T-one model usage in multiple programming languages
Introduction
This directory contains examples for Dart API.
You can find the package at https://pub.dev/packages/sherpa_onnx
Description
| Directory | Description |
|---|---|
| ./speaker-diarization | Example for speaker diarization. |
| ./add-punctuations | Example for adding punctuations to text. |
| ./audio-tagging | Example for audio tagging. |
| ./keyword-spotter | Example for keyword spotting |
| ./non-streaming-asr | Example for non-streaming speech recognition |
| ./speaker-identification | Example for speaker identification and verification. |
| ./streaming-asr | Example for streaming speech recognition |
| ./tts | Example for text to speech |
| ./vad-with-non-streaming-asr | Example for voice activity detection with non-streaming speech recognition. You can use it to generate subtitles. |
| ./vad | Example for voice activity detection |
| ./speech-enhancement-gtcrn | Example for speech enhancement/denoising |
How to create an example in this folder
dart create vad
cd vad
# Edit pubspec.yaml and add sherpa_onnx to dependencies
dart pub get
dart run