From d80ac2fd2df4e7fb8a28acfa512bb11472b5cc99 Mon Sep 17 00:00:00 2001
From: liugz18 <57401541+liugz18@users.noreply.github.com>
Date: 星期四, 18 七月 2024 21:34:55 +0800
Subject: [PATCH] Rename 'res' in line 514 to avoid with naming conflict with line 365
---
examples/industrial_data_pretraining/paraformer_streaming/demo.py | 60 ++++++++++++++++++++++++++++++++----------------------------
1 files changed, 32 insertions(+), 28 deletions(-)
diff --git a/examples/industrial_data_pretraining/paraformer_streaming/demo.py b/examples/industrial_data_pretraining/paraformer_streaming/demo.py
index 601a531..a1e9882 100644
--- a/examples/industrial_data_pretraining/paraformer_streaming/demo.py
+++ b/examples/industrial_data_pretraining/paraformer_streaming/demo.py
@@ -3,40 +3,44 @@
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
# MIT License (https://opensource.org/licenses/MIT)
-from funasr import AutoModel
-
-chunk_size = [5, 10, 5] #[0, 10, 5] 600ms, [0, 8, 4] 480ms
-encoder_chunk_look_back = 0 #number of chunks to lookback for encoder self-attention
-decoder_chunk_look_back = 0 #number of encoder chunks to lookback for decoder cross-attention
-wav_file="/Users/zhifu/Downloads/NCYzUhAtZNI_0015.wav"
-model = AutoModel(model="iic/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online", model_revision="v2.0.4")
-res = model.generate(input=wav_file,
- chunk_size=chunk_size,
- encoder_chunk_look_back=encoder_chunk_look_back,
- decoder_chunk_look_back=decoder_chunk_look_back,
- )
-print(res)
-
-# exit()
-
-import soundfile
import os
-# wav_file = os.path.join(model.model_path, "example/asr_example.wav")
+from funasr import AutoModel
+
+chunk_size = [0, 10, 5] # [0, 10, 5] 600ms, [0, 8, 4] 480ms
+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="iic/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online")
+
+wav_file = os.path.join(model.model_path, "example/asr_example.wav")
+res = model.generate(
+ input=wav_file,
+ chunk_size=chunk_size,
+ encoder_chunk_look_back=encoder_chunk_look_back,
+ decoder_chunk_look_back=decoder_chunk_look_back,
+)
+print(res)
+
+
+import soundfile
+
+
+wav_file = os.path.join(model.model_path, "example/asr_example.wav")
speech, sample_rate = soundfile.read(wav_file)
-chunk_stride = chunk_size[1] * 960 # 600ms銆�480ms
+chunk_stride = chunk_size[1] * 960 # 600ms銆�480ms
cache = {}
-total_chunk_num = int(len((speech)-1)/chunk_stride+1)
+total_chunk_num = int(len((speech) - 1) / chunk_stride + 1)
for i in range(total_chunk_num):
- speech_chunk = speech[i*chunk_stride:(i+1)*chunk_stride]
+ speech_chunk = speech[i * chunk_stride : (i + 1) * chunk_stride]
is_final = i == total_chunk_num - 1
- res = model.generate(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.generate(
+ 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)
--
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