Refactors and extends model export support to include new NeMo Parakeet TDT int8 variants for English and Japanese, updating the Kotlin API, export scripts, test runners, and CI workflows.
- Added support for two new int8 model types in OfflineRecognizer.kt.
- Enhanced Python export scripts to perform dynamic quantization and metadata injection.
- Updated shell scripts and GitHub workflows to package, test, and publish int8 model artifacts.
Add support for the NeMo Canary model in both Java and Kotlin APIs, wiring it through
JNI and updating examples and CI.
- Introduce OfflineCanaryModelConfig in Kotlin and Java with builder patterns
- Extend OfflineRecognizer to accept and apply the new canary config via setConfig
- Update JNI binding (GetOfflineConfig) and getOfflineModelConfig mapping (type 32),
plus examples and CI workflows
This PR introduces support for NeMo Canary models across C, C++, and JavaScript APIs
by adding new Canary configuration structures, updating bindings, extending examples,
and enhancing CI workflows.
- Add OfflineCanaryModelConfig to all language bindings (C, C++, JS, ETS).
- Implement SetConfig methods and NAPI wrappers for updating recognizer config at runtime.
- Update examples and CI scripts to demonstrate and test NeMo Canary model usage.
Adds support for building and packaging Linux AArch64 (arm64) artifacts alongside x64 for Dart/Flutter plugins.
- Detects host architecture in CMake and adjusts library paths
- Extends test workflows to run on an ARM runner and handle linux-aarch64 paths
- Splits release pipeline into separate x64 and aarch64 build/package jobs
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
