xuning / sherpaonnx

This PR disables loading native libraries from JAR resources specifically on Android platforms. The change prevents potential issues with JAR-based library loading on Android while maintaining compatibility with other platforms.

This PR fixes the C API by adding proper support for durations in offline recognition results. The issue addresses problems introduced in a previous PR where the durations field was added to the C API struct but not properly handled across all language bindings.

Key changes:

- Adds durations field handling across multiple language bindings (Swift, Kotlin, Java, C#)
- Fixes field ordering in C API struct to ensure ABI compatibility
- Updates JNI implementation to properly extract and pass durations data

Co-authored-by: yaozengwei <yaozengwei@outlook.com>

This PR fixes the uploading process for win32 libraries to Hugging Face by updating Windows OS detection and correcting the file copy destination path.

- Replaces deprecated wmic command with PowerShell-based OS detection for better reliability
- Adds fallback mechanism using cmd /c ver when PowerShell is unavailable
- Corrects the destination path for win32 library archives to include version subdirectory

This PR simplifies the usage of the non-Android Java API by providing platform-specific JAR files that include native shared libraries, eliminating the need for users to manually manage native dependencies.

- Refactored LibraryUtils.java to support multiple library loading methods including extracting from JAR resources
- Added build infrastructure to create platform-specific native library JAR files
- Introduced debug capabilities and improved error handling for library loading

This PR adds support for two new Piper TTS (Text-to-Speech) models: an Indonesian model (id_ID-news_tts-medium) and a Hindi model (hi_IN-rohan-medium).

Co-authored-by: Aruxxxi <xiangcl@zhisuan.com>

This PR implements support for specifying pronunciations of phrases in Chinese TTS by modifying the lexicon processing logic. The change introduces a greedy longest-match algorithm that attempts to match multi-word phrases before falling back to individual word processing.

This PR adds support for exporting two new whisper distil models (distil-large-v3 and distil-large-v3.5) to ONNX format for use with sherpa-onnx. The changes enable these models to be processed through the existing export pipeline.

- Added support for distil-large-v3 and distil-large-v3.5 models in the export script
- Updated GitHub workflow to include the new models in the CI matrix
- Configured proper n_mels parameter (128) for the new distil models

This PR updates version information across all Android applications in the sherpa-onnx project to version 1.12.9 with version code 20250817. The changes automate version updates through a release script and apply consistent versioning across all Android app modules.

This PR refactors CI test configurations by removing pull request triggers from multiple GitHub Actions workflows and fixes a bug in the cosine similarity calculation. Additionally, it updates Python version paths for newer 3.13.6 release.

This PR adds support for new streaming ASR models from VOSK (Russian) and Kroko (German) to the sherpa-onnx project. It integrates three new models: one German Kroko streaming model and two Russian VOSK streaming models (regular and int8 quantized versions).

- Adds configuration for three new streaming ASR models (indices 24-26)
- Updates APK generation scripts to include the new models
- Modifies GitHub workflow for model upload and deployment

This PR adds support for the newer version (v3) of NVIDIA's parakeet-tdt-0.6b model by exporting it to sherpa-onnx format. The v3 model supports 25 languages, maintaining the same usage pattern as v2 but with improved language coverage.