From 98c94ab3ab0266482117343a064beeb6bd6bcedc Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 28 二月 2024 20:45:07 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR merge

---
 README.md |   25 ++++++++++++++++---------
 1 files changed, 16 insertions(+), 9 deletions(-)

diff --git a/README.md b/README.md
index 454adc9..04a3e68 100644
--- a/README.md
+++ b/README.md
@@ -105,10 +105,8 @@
 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="v2.0.4",
-                  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",
+model = AutoModel(model="paraformer-zh",  vad_model="fsmn-vad",  punc_model="ct-punc-c", 
+                  # spk_model="cam++", 
                   )
 res = model.generate(input=f"{model.model_path}/example/asr_example.wav", 
                      batch_size_s=300, 
@@ -125,7 +123,7 @@
 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="v2.0.4")
+model = AutoModel(model="paraformer-zh-streaming")
 
 import soundfile
 import os
@@ -148,17 +146,19 @@
 ```python
 from funasr import AutoModel
 
-model = AutoModel(model="fsmn-vad", model_revision="v2.0.4")
+model = AutoModel(model="fsmn-vad")
 wav_file = f"{model.model_path}/example/asr_example.wav"
 res = model.generate(input=wav_file)
 print(res)
 ```
+Note: The output format of the VAD model is: `[[beg1, end1], [beg2, end2], ..., [begN, endN]]`, where `begN/endN` indicates the starting/ending point of the `N-th` valid audio segment, measured in milliseconds.
+
 ### Voice Activity Detection (Streaming)
 ```python
 from funasr import AutoModel
 
 chunk_size = 200 # ms
-model = AutoModel(model="fsmn-vad", model_revision="v2.0.4")
+model = AutoModel(model="fsmn-vad")
 
 import soundfile
 
@@ -175,11 +175,18 @@
     if len(res[0]["value"]):
         print(res)
 ```
+Note: The output format for the streaming VAD model can be one of four scenarios:
+- `[[beg1, end1], [beg2, end2], .., [begN, endN]]`锛歍he same as the offline VAD output result mentioned above.
+- `[[beg, -1]]`锛欼ndicates that only a starting point has been detected.
+- `[[-1, end]]`锛欼ndicates that only an ending point has been detected.
+- `[]`锛欼ndicates that neither a starting point nor an ending point has been detected. 
+
+The output is measured in milliseconds and represents the absolute time from the starting point.
 ### Punctuation Restoration
 ```python
 from funasr import AutoModel
 
-model = AutoModel(model="ct-punc", model_revision="v2.0.4")
+model = AutoModel(model="ct-punc")
 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)
 ```
@@ -187,7 +194,7 @@
 ```python
 from funasr import AutoModel
 
-model = AutoModel(model="fa-zh", model_revision="v2.0.4")
+model = AutoModel(model="fa-zh")
 wav_file = f"{model.model_path}/example/asr_example.wav"
 text_file = f"{model.model_path}/example/text.txt"
 res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))

--
Gitblit v1.9.1