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
File description
- ./http_server.py It defines which files to server. Files are saved in ./web.
- non_streaming_server.py WebSocket server for non-streaming models.
- vad-remove-non-speech-segments.py It uses silero-vad to remove non-speech segments and concatenate all speech segments into a single one.
- vad-with-non-streaming-asr.py It shows how to use VAD with a non-streaming ASR model for speech recognition from a microphone