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Liangcd
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Commit
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2a2c14b
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Parent(s):
a487abc
[demo] Update app.py and add examples
Browse files- app.py +28 -14
- examples/BAC009S0767W0127.wav +0 -0
- examples/BAC009S0767W0424.wav +0 -0
- examples/BAC009S0767W0488.wav +0 -0
app.py
CHANGED
@@ -1,3 +1,17 @@
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import json
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import gradio as gr
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@@ -5,48 +19,47 @@ import numpy as np
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import wenetruntime as wenet
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wenet.set_log_level(2)
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-
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def recognition(audio):
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print(audio)
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if audio is None:
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return "Input Error! Please enter one audio!"
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sr, y = audio
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assert sr in [48000, 16000]
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if sr == 48000: # Optional resample to 16000
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y = (y / max(np.max(y), 1) * 32767)[::3].astype("int16")
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ans =
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if ans
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return "ERROR! No text output! Please try again!"
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# ans (json)
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# {
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# 'nbest' : [{"sentence" : ""}], 'type' : 'final_result
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# }
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ans = json.loads(ans)
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print(ans)
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txt = ans['nbest'][0]['sentence']
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return txt
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# input
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inputs =
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gr.inputs.Audio(source="microphone",
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type="numpy",
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label='Speaker#1')
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]
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output = gr.outputs.Textbox(label="Output Text")
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text = "Speech Recognition in WeNet | 基于 WeNet 的语音识别"
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# description
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description = ("
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article = (
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"<p style='text-align: center'>"
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"<a href='https://github.com/wenet-e2e/
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"</p>")
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interface = gr.Interface(
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@@ -56,6 +69,7 @@ interface = gr.Interface(
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title=text,
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description=description,
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article=article,
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theme='huggingface',
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)
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# Copyright (c) 2022 Horizon Robotics. (authors: Binbin Zhang)
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# 2022 Chengdong Liang ([email protected])
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import gradio as gr
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import wenetruntime as wenet
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wenet.set_log_level(2)
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decoder_cn = wenet.Decoder(lang='chs')
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def recognition(audio):
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if audio is None:
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return "Input Error! Please enter one audio!"
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sr, y = audio
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assert sr in [48000, 16000]
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if sr == 48000: # Optional resample to 16000
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y = (y / max(np.max(y), 1) * 32767)[::3].astype("int16")
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ans = decoder_cn.decode(y.tobytes(), True)
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if ans is None:
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return "ERROR! No text output! Please try again!"
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# NOTE: ans (json)
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# {
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# 'nbest' : [{"sentence" : ""}], 'type' : 'final_result
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# }
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ans = json.loads(ans)
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txt = ans['nbest'][0]['sentence']
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return txt
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# input
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inputs = gr.inputs.Audio(source="microphone", type="numpy", label='Input audio')
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output = gr.outputs.Textbox(label="Output Text")
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examples = [
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['examples/BAC009S0767W0127.wav'],
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['examples/BAC009S0767W0424.wav'],
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['examples/BAC009S0767W0488.wav'],
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]
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text = "Speech Recognition in WeNet | 基于 WeNet 的语音识别"
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# description
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description = ("Wenet Demo ! This is a Mandarin streaming speech recognition !")
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article = (
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"<p style='text-align: center'>"
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"<a href='https://github.com/wenet-e2e/wenet' target='_blank'>Github: Learn more about WeNet</a>"
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"</p>")
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interface = gr.Interface(
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title=text,
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description=description,
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article=article,
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examples=examples,
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theme='huggingface',
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)
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examples/BAC009S0767W0127.wav
ADDED
Binary file (130 kB). View file
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examples/BAC009S0767W0424.wav
ADDED
Binary file (81 kB). View file
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examples/BAC009S0767W0488.wav
ADDED
Binary file (95.8 kB). View file
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