docs: add CONTRIBUTING.md (#284)

Provides contribution guidelines including:
- Development environment setup (with CPU instructions)
- How to report bugs and submit PRs
- Project structure overview
- Model architecture summary (emotion labels, events, languages)
- Docker usage instructions

Co-authored-by: Daniel weadock <danielweadock@Daniels-MacBook-Air.local>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: 3 people

CONTRIBUTING.md

@@ -0,0 +1,152 @@
+# Contributing to SenseVoice
+
+Thank you for your interest in contributing to SenseVoice! This guide will help you get started.
+
+## Getting Started
+
+### Prerequisites
+
+- Python 3.8 or higher
+- Git
+- (Optional) CUDA-compatible GPU for faster inference
+
+### Setting Up the Development Environment
+
+1. **Fork and clone the repository:**
+
+```bash
+git clone https://github.com/<your-username>/SenseVoice.git
+cd SenseVoice
+```
+
+2. **Create a virtual environment:**
+
+```bash
+python3 -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+```
+
+3. **Install dependencies:**
+
+```bash
+pip install -r requirements.txt
+```
+
+4. **Verify the installation:**
+
+```bash
+python -c "from funasr import AutoModel; print('Installation successful')"
+```
+
+### Running on CPU
+
+If you don't have a GPU, you can run SenseVoice on CPU by setting the device to `"cpu"`:
+
+```python
+model = AutoModel(
+    model="iic/SenseVoiceSmall",
+    trust_remote_code=True,
+    device="cpu",
+)
+```
+
+For the FastAPI server:
+
+```bash
+export SENSEVOICE_DEVICE=cpu
+fastapi run --port 50000
+```
+
+## How to Contribute
+
+### Reporting Bugs
+
+1. Search [existing issues](https://github.com/FunAudioLLM/SenseVoice/issues) to avoid duplicates.
+2. Use the [Bug Report template](https://github.com/FunAudioLLM/SenseVoice/issues/new?template=bug_report.md).
+3. Include your environment details (OS, Python version, PyTorch version, GPU, CUDA version).
+4. Provide a minimal code sample to reproduce the issue.
+
+### Submitting Pull Requests
+
+1. **Fork the repository** and create a new branch from `main`:
+
+```bash
+git checkout -b your-branch-name
+```
+
+2. **Make your changes.** Keep commits focused and atomic.
+
+3. **Test your changes** to make sure nothing is broken.
+
+4. **Push to your fork** and open a Pull Request against `FunAudioLLM/SenseVoice:main`.
+
+5. **Describe your changes** clearly in the PR description. Explain *what* changed and *why*.
+
+### Types of Contributions We Welcome
+
+- **Bug fixes** — Check [open issues labeled `bug`](https://github.com/FunAudioLLM/SenseVoice/issues?q=is%3Aissue+is%3Aopen+label%3Abug) for known problems.
+- **Documentation improvements** — Typo fixes, clarifications, additional examples, translations.
+- **New examples** — Demo scripts showing different use cases (emotion detection, event detection, multilingual transcription).
+- **Performance improvements** — Optimizations for inference speed or memory usage.
+- **Test coverage** — Unit tests and integration tests are very welcome.
+
+### Code Style
+
+- Follow existing code patterns and conventions in the repository.
+- Use type hints where applicable.
+- Add docstrings to new functions and classes.
+- Keep lines under 120 characters.
+
+## Project Structure
+
+```
+SenseVoice/
+├── model.py          # Core SenseVoiceSmall model (encoder, CTC decoder, emotion/event embeddings)
+├── api.py            # FastAPI server for inference
+├── webui.py          # Gradio web interface
+├── demo1.py          # Inference example using FunASR AutoModel
+├── demo2.py          # Direct model inference with timestamp support
+├── export.py         # ONNX model export
+├── export_meta.py    # Export utilities for model rebuilding
+├── finetune.sh       # Fine-tuning script with DeepSpeed support
+├── requirements.txt  # Python dependencies
+├── Dockerfile        # Docker build configuration
+├── data/             # Example training and validation data
+├── utils/            # Utilities (frontend, ONNX inference, CTC alignment, export)
+└── image/            # Documentation images
+```
+
+## Understanding the Model
+
+SenseVoice is a non-autoregressive encoder-only model that outputs:
+
+- **Speech transcription** (ASR) across 50+ languages
+- **Emotion labels**: `HAPPY`, `SAD`, `ANGRY`, `NEUTRAL`, `FEARFUL`, `DISGUSTED`, `SURPRISED`
+- **Audio event labels**: `BGM`, `Speech`, `Applause`, `Laughter`, `Cry`, `Sneeze`, `Breath`, `Cough`
+- **Language identification** for Mandarin, English, Cantonese, Japanese, and Korean
+
+The model uses a SANM (Self-Attention with Normalized Memory) encoder architecture with CTC decoding. Emotion and event labels are predicted from the first 4 encoder output tokens, while the remaining tokens produce the transcription.
+
+## Docker
+
+You can also run SenseVoice using Docker:
+
+```bash
+# Build
+docker build -t sensevoice .
+
+# Run with GPU
+docker run --gpus all -p 50000:50000 sensevoice
+
+# Run on CPU
+docker run -e SENSEVOICE_DEVICE=cpu -p 50000:50000 sensevoice
+```
+
+## Questions?
+
+- Open an issue using the [Questions template](https://github.com/FunAudioLLM/SenseVoice/issues/new?template=ask_questions.md).
+- Join the community via the DingTalk group (see [README](./README.md#community)).
+
+## License
+
+By contributing to SenseVoice, you agree that your contributions will be licensed under the same license as the project. See [FunASR License](https://github.com/modelscope/FunASR?tab=readme-ov-file#license) for details.