3bf986d08d
This PR adds support for non-streaming Zipformer CTC ASR models across multiple language bindings, WebAssembly, examples, and CI workflows. - Introduces a new OfflineZipformerCtcModelConfig in C/C++, Python, Swift, Java, Kotlin, Go, Dart, Pascal, and C# APIs - Updates initialization, freeing, and recognition logic to include Zipformer CTC in WASM and Node.js - Adds example scripts and CI steps for downloading, building, and running Zipformer CTC models Model doc is available at https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/icefall/zipformer.html
Introduction
This directory contains examples for how to use the Object Pascal APIs of sherpa-onnx.
Documentation for this directory: https://k2-fsa.github.io/sherpa/onnx/pascal-api/index.html
| Directory | Description |
|---|---|
| read-wav | It shows how to read a wave file. |
| speaker-diarization | It shows how to use Pascal API for speaker diarization. |
| streaming-asr | It shows how to use streaming models for speech recognition. |
| non-streaming-asr | It shows how to use non-streaming models for speech recognition. |
| vad | It shows how to use the voice activity detection API. |
| vad-with-non-streaming-asr | It shows how to use the voice activity detection API with non-streaming models for speech recognition. |
| portaudio-test | It shows how to use PortAudio for recording and playing. |
| tts | It shows how to use the text-to-speech API. |