From 0281b70896bd8069a9d26dad1ef2b5090ae5fc4a Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期四, 25 一月 2024 10:20:31 +0800
Subject: [PATCH] update umap import
---
README_zh.md | 21 +++++++++++----------
1 files changed, 11 insertions(+), 10 deletions(-)
diff --git a/README_zh.md b/README_zh.md
index dc20302..552a5a0 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -87,12 +87,13 @@
from funasr import AutoModel
# 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")
+model = AutoModel(model="paraformer-zh", model_revision="v2.0.4",
+ vad_model="fsmn-vad", vad_model_revision="v2.0.4",
+ punc_model="ct-punc-c", punc_model_revision="v2.0.4",
+ # spk_model="cam++", spk_model_revision="v2.0.2",
+ )
res = model.generate(input=f"{model.model_path}/example/asr_example.wav",
- batch_size=64,
+ batch_size_s=300,
hotword='榄旀惌')
print(res)
```
@@ -107,7 +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="v2.0.2")
+model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.4")
import soundfile
import os
@@ -131,7 +132,7 @@
```python
from funasr import AutoModel
-model = AutoModel(model="fsmn-vad", model_revision="v2.0.2")
+model = AutoModel(model="fsmn-vad", model_revision="v2.0.4")
wav_file = f"{model.model_path}/example/asr_example.wav"
res = model.generate(input=wav_file)
@@ -143,7 +144,7 @@
from funasr import AutoModel
chunk_size = 200 # ms
-model = AutoModel(model="fsmn-vad", model_revision="v2.0.2")
+model = AutoModel(model="fsmn-vad", model_revision="v2.0.4")
import soundfile
@@ -165,7 +166,7 @@
```python
from funasr import AutoModel
-model = AutoModel(model="ct-punc", model_revision="v2.0.2")
+model = AutoModel(model="ct-punc", model_revision="v2.0.4")
res = model.generate(input="閭ｄ粖澶╃殑浼氬氨鍒拌繖閲屽惂 happy new year 鏄庡勾瑙�")
print(res)
@@ -182,7 +183,7 @@
res = model.generate(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�
+鏇村璇︾粏鐢ㄦ硶锛圼绀轰緥](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)锛�
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