From 19645da9e998581e6329d679bae968d0c45d1895 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期一, 15 一月 2024 20:46:40 +0800
Subject: [PATCH] update readme

---
 README_zh.md |   38 +++++++++++++++-----------------------
 1 files changed, 15 insertions(+), 23 deletions(-)

diff --git a/README_zh.md b/README_zh.md
index 5a489ee..2da2171 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -86,12 +86,15 @@
 ### 闈炲疄鏃惰闊宠瘑鍒�
 ```python
 from funasr import AutoModel
-
-model = AutoModel(model="paraformer-zh")
-# for the long duration wav, you could add vad model
-# model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc")
-
-res = model(input="asr_example_zh.wav", batch_size=64)
+# paraformer-zh is a multi-functional asr model
+# use vad, punc, spk or not as you need
+model = AutoModel(model="paraformer-zh", model_revision="v2.0.2", \
+                  vad_model="fsmn-vad", vad_model_revision="v2.0.2", \
+                  punc_model="ct-punc-c", punc_model_revision="v2.0.2", \
+                  spk_model="cam++", spk_model_revision="v2.0.2")
+res = model(input=f"{model.model_path}/example/asr_example.wav", 
+            batch_size=64, 
+            hotword='榄旀惌')
 print(res)
 ```
 娉細`model_hub`锛氳〃绀烘ā鍨嬩粨搴擄紝`ms`涓洪�夋嫨modelscope涓嬭浇锛宍hf`涓洪�夋嫨huggingface涓嬭浇銆�
@@ -105,7 +108,7 @@
 encoder_chunk_look_back = 4 #number of chunks to lookback for encoder self-attention
 decoder_chunk_look_back = 1 #number of encoder chunks to lookback for decoder cross-attention
 
-model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.0")
+model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.2")
 
 import soundfile
 import os
@@ -119,13 +122,7 @@
 for i in range(total_chunk_num):
     speech_chunk = speech[i*chunk_stride:(i+1)*chunk_stride]
     is_final = i == total_chunk_num - 1
-    res = model(input=speech_chunk,
-                cache=cache,
-                is_final=is_final,
-                chunk_size=chunk_size,
-                encoder_chunk_look_back=encoder_chunk_look_back,
-                decoder_chunk_look_back=decoder_chunk_look_back,
-                )
+    res = model(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size, encoder_chunk_look_back=encoder_chunk_look_back, decoder_chunk_look_back=decoder_chunk_look_back)
     print(res)
 ```
 
@@ -160,11 +157,7 @@
 for i in range(total_chunk_num):
     speech_chunk = speech[i*chunk_stride:(i+1)*chunk_stride]
     is_final = i == total_chunk_num - 1
-    res = model(input=speech_chunk,
-                cache=cache,
-                is_final=is_final,
-                chunk_size=chunk_size,
-                )
+    res = model(input=speech_chunk, cache=cache, is_final=is_final, chunk_size=chunk_size)
     if len(res[0]["value"]):
         print(res)
 ```
@@ -173,7 +166,7 @@
 ```python
 from funasr import AutoModel
 
-model = AutoModel(model="ct-punc", model_revision="v2.0.1")
+model = AutoModel(model="ct-punc", model_revision="v2.0.2")
 
 res = model(input="閭d粖澶╃殑浼氬氨鍒拌繖閲屽惂 happy new year 鏄庡勾瑙�")
 print(res)
@@ -186,9 +179,8 @@
 model = AutoModel(model="fa-zh", model_revision="v2.0.0")
 
 wav_file = f"{model.model_path}/example/asr_example.wav"
-text_file = f"{model.model_path}/example/asr_example.wav"
-res = model(input=(wav_file, text_file),
-            data_type=("sound", "text"))
+text_file = f"{model.model_path}/example/text.txt"
+res = model(input=(wav_file, text_file), data_type=("sound", "text"))
 print(res)
 ```
 鏇村璇︾粏鐢ㄦ硶锛圼绀轰緥](examples/industrial_data_pretraining)锛�

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