Update README.md

README.md

@@ -1,3 +1,73 @@
 ---
 license: apache-2.0
+pipeline_tag: text-to-speech
+language:
+- zh
+- en
+- de
+- fr
+- ja
+- ko
+tags:
+- m5-tts
+- voice-cloning
+- multilingual
+- onnx
+- onnxruntime
 ---
+
+# M5-TTS-50M-ONNX
+
+English | [简体中文](README_zh.md)
+
+[GitHub](https://github.com/ASLP-lab/M5-TTS) · [Demo](https://aslp-lab.github.io/M5-TTS-Demo-Page/) · [Space](https://huggingface.co/spaces/ASLP-lab/M5-TTS-Space) · [Models](https://huggingface.co/collections/ASLP-lab/m5-tts)
+
+**M5-TTS** is a compact multilingual and multi-dialect text-to-speech system from ASLP@NPU and LycheeAI Lab. It combines a 30M temporal backbone with a 20M local multi-token prediction decoder, using 16 audio codebooks at 12.5 frames/s for **24 kHz** speech generation. The speech codec is separate from the language model.
+
+This repository provides a **complete FP32 ONNX inference bundle**, including TTS graphs, text/audio embeddings, the text tokenizer and reference-audio encoder/decoder graphs. The same files support CPU and NVIDIA GPU voice cloning; no separate codec download is needed. The source checkpoint is identified in `manifest.json` and should not be assumed identical to another M5 checkpoint.
+
+## Quickstart
+
+Use Python 3.10 on Linux. Install from the code repository:
+
+```bash
+git clone https://github.com/ASLP-lab/M5-TTS.git
+cd M5-TTS
+conda create -n m5tts python=3.10 -y
+conda activate m5tts
+pip install -r requirements.txt
+```
+
+**CPU inference**, from the repository root:
+
+```bash
+python infer_onnx.py \
+  --model ASLP-lab/M5-TTS-50M-ONNX \
+  --device cpu --threads 4 \
+  --text "你好，欢迎使用我们的语音合成模型。" \
+  --prompt-wav assets/aslp_default_voice.wav \
+  --prompt-text "猪携带该疾病，然后通过蚊子传染给人类。" \
+  --output outputs/onnx_cpu.wav
+```
+
+**NVIDIA GPU inference:**
+
+```bash
+python infer_onnx.py \
+  --model ASLP-lab/M5-TTS-50M-ONNX \
+  --device cuda --device-id 0 \
+  --text "你好，欢迎使用我们的语音合成模型。" \
+  --prompt-wav assets/aslp_default_voice.wav \
+  --prompt-text "猪携带该疾病，然后通过蚊子传染给人类。" \
+  --output outputs/onnx_gpu.wav
+```
+
+CUDA execution requires a compatible NVIDIA driver. The shared requirements install `onnxruntime-gpu`, which also supports CPU execution; do not additionally install `onnxruntime`. FlashAttention is not used by this entry point.
+
+Add `--stream` to write generated audio chunks incrementally. Output is a WAV plus a same-stem JSON statistics file. The current ONNX entry point requires reference audio and its transcript; it does not expose preset speaker IDs or dialect/accent conditioning. CPU and GPU results may differ numerically.
+
+See the [ONNX guide](https://github.com/ASLP-lab/M5-TTS#onnx-inference) and [Android example](https://github.com/ASLP-lab/M5-TTS/tree/main/android). Only clone voices you own or have permission to use.
+
+## License
+
+Apache-2.0. The Qwen-derived audio codec retains its upstream attribution; see the [third-party notice](https://github.com/ASLP-lab/M5-TTS/blob/main/m5/codec_qwen12hz/NOTICE).