This PR integrates LODR (Level-Ordered Deterministic Rescoring) support from Icefall into both online and offline recognizers, enabling LODR for LM shallow fusion and LM rescore.
- Extended OnlineLMConfig and OfflineLMConfig to include lodr_fst, lodr_scale, and lodr_backoff_id.
- Implemented LodrFst and LodrStateCost classes and wired them into RNN LM scoring in both online and offline code paths.
- Updated Python bindings, CLI entry points, examples, and CI test scripts to accept and exercise the new LODR options.
* Support streaming zipformer CTC
* test online zipformer2 CTC
* Update doc of sherpa-onnx.cc
* Add Python APIs for streaming zipformer2 ctc
* Add Python API examples for streaming zipformer2 ctc
* Swift API for streaming zipformer2 CTC
* NodeJS API for streaming zipformer2 CTC
* Kotlin API for streaming zipformer2 CTC
* Golang API for streaming zipformer2 CTC
* C# API for streaming zipformer2 CTC
* Release v1.9.6
* Refactor online recognizer.
Make it easier to support other streaming models.
Note that it is a breaking change for the Python API.
`sherpa_onnx.OnlineRecognizer()` used before should be
replaced by `sherpa_onnx.OnlineRecognizer.from_transducer()`.
