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1 Parent(s): 1f9ba8e

Update app (7).py

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  1. app (7).py +8 -33
app (7).py CHANGED
@@ -1,18 +1,3 @@
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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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-
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  import gradio as gr
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  import torch
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  from wenet.cli.model import load_model
@@ -43,7 +28,7 @@ model = download_rev_models()
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  def recognition(audio, style=0):
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  if audio is None:
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  return "Input Error! Please enter one audio!"
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- # NOTE: model supports 16k sample_rate
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  cat_embs = ','.join([str(s) for s in (style, 1-style)])
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  cat_embs = process_cat_embs(cat_embs)
@@ -62,29 +47,21 @@ inputs = [
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  gr.Slider(0, 1, value=0, label="Verbatimicity - from non-verbatim (0) to verbatim (1)", info="Choose a transcription style between non-verbatim and verbatim"),
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  ]
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- examples = [
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- ['examples/POD1000000012_S0000335.wav'],
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- ['examples/POD1000000013_S0000062.wav'],
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- ['examples/POD1000000032_S0000020.wav'],
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- ['examples/POD1000000032_S0000038.wav'],
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- ['examples/POD1000000032_S0000050.wav'],
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- ['examples/POD1000000032_S0000058.wav'],
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- ]
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-
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  output = gr.outputs.Textbox(label="Output Text")
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- text = "Reverb ASR Transcription Styles Demo"
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  # description
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  description = (
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- "Reverb ASR supports verbatim and non-verbatim transcription. Try recording an audio with disfluencies (ex: \'uh\', \'um\') and testing both transcription styles. Or, choose an example audio below." # noqa
 
 
 
 
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  )
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- article = (
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- "<p style='text-align: center'>"
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- "<a href='https://rev.com' target='_blank'>Learn more about Rev</a>" # noqa
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- "</p>")
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  interface = gr.Interface(
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  fn=recognition,
@@ -92,8 +69,6 @@ interface = gr.Interface(
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  outputs=output,
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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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  import gradio as gr
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  import torch
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  from wenet.cli.model import load_model
 
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  def recognition(audio, style=0):
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  if audio is None:
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  return "Input Error! Please enter one audio!"
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+
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  cat_embs = ','.join([str(s) for s in (style, 1-style)])
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  cat_embs = process_cat_embs(cat_embs)
 
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  gr.Slider(0, 1, value=0, label="Verbatimicity - from non-verbatim (0) to verbatim (1)", info="Choose a transcription style between non-verbatim and verbatim"),
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  ]
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  output = gr.outputs.Textbox(label="Output Text")
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+ text = "ASR Transcription Opensource Demo"
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  # description
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  description = (
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+ " Opensource Automatic Speech Recognition in English
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+
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+ Verbatim Transcript style(1) refers to word to word-to-word transcription of an audio
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+ Non Verbatim Transcript style(0) refers to just conserving the message of the original audio
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+ "
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  )
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+
 
 
 
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  interface = gr.Interface(
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  fn=recognition,
 
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  outputs=output,
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  title=text,
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  description=description,
 
 
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  theme='huggingface',
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  )
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