From fa9a6cdb1eade68c258eed7297f5a8a8a5329ac6 Mon Sep 17 00:00:00 2001
From: Flute <41096447+fluteink@users.noreply.github.com>
Date: 星期三, 01 十月 2025 14:44:28 +0800
Subject: [PATCH] 更新文档和运行脚本，修复文档拼写错误 (#2688)

---
 README.md |   11 ++++++++---
 1 files changed, 8 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 44f9fc8..cabdcac 100644
--- a/README.md
+++ b/README.md
@@ -9,7 +9,7 @@
 [![PyPI](https://img.shields.io/pypi/v/funasr)](https://pypi.org/project/funasr/)
 
 <p align="center">
-<a href="https://trendshift.io/repositories/3839" target="_blank"><img src="https://trendshift.io/api/badge/repositories/3839" alt="alibaba-damo-academy%2FFunASR | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://trendshift.io/repositories/3839" target="_blank"><img src="https://trendshift.io/api/badge/repositories/3839" alt="modelscope%2FFunASR | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 </p>
 
 <strong>FunASR</strong> hopes to build a bridge between academic research and industrial applications on speech recognition. By supporting the training & finetuning of the industrial-grade speech recognition model, researchers and developers can conduct research and production of speech recognition models more conveniently, and promote the development of speech recognition ecology. ASR for Fun锛�
@@ -315,11 +315,16 @@
 ### Test ONNX
 ```python
 # pip3 install -U funasr-onnx
-from funasr_onnx import Paraformer
+from pathlib import Path
+from runtime.python.onnxruntime.funasr_onnx.paraformer_bin import Paraformer
+
+
+home_dir = Path.home()
+
 model_dir = "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
 model = Paraformer(model_dir, batch_size=1, quantize=True)
 
-wav_path = ['~/.cache/modelscope/hub/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav']
+wav_path = [f"{home_dir}/.cache/modelscope/hub/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav"]
 
 result = model(wav_path)
 print(result)

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