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Runtime error
Runtime error
change Arthur.config to lower standarad
Browse files- app.py +68 -51
- config/Arthur.yaml +4 -4
- local/check_data.py +8 -7
- local/convert_metrics.py +73 -0
app.py
CHANGED
@@ -19,7 +19,7 @@ from transformers import pipeline
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import librosa
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import librosa.display
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import matplotlib.pyplot as plt
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-
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# Google cloud service
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from googleapiclient.discovery import build
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@@ -229,8 +229,14 @@ def calc_mos(_, audio_path, id, ref, pre_ppm, fig=None):
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"GOOD JOB! Please 【Save the Recording】.\nYou can start recording the next sample."
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)
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# Google Drive saving
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-
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return (
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fig_h,
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@@ -240,6 +246,7 @@ def calc_mos(_, audio_path, id, ref, pre_ppm, fig=None):
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phone_transcription,
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ppm,
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error_msg,
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)
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with open("src/description.html", "r", encoding="utf-8") as f:
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@@ -345,7 +352,6 @@ def generate_now_time_wav():
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# Add google drive cloud saving
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def click_google_saving(audio_file,
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):
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# reference_id,
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# reference_textbox,
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@@ -361,8 +367,7 @@ def click_google_saving(audio_file,
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request = service.files().create(
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media_body=media,
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body={'name': name,
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}
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)
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# 'reference_id': reference_id,
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# "reference_textbox": reference_textbox,
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@@ -373,6 +378,8 @@ def click_google_saving(audio_file,
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# "ppm": ppm,
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# "msg": msg
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response = request.execute()
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# return response.get('id')
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@@ -404,18 +411,19 @@ with gr.Blocks(css=css, theme=my_theme) as demo:
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interactive=True,
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elem_classes="ref_text",
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)
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with gr.Row():
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b = gr.Button(value="1.Submit", variant="primary", elem_classes="submit")
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@@ -440,42 +448,48 @@ with gr.Blocks(css=css, theme=my_theme) as demo:
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interactive=False,
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elem_classes="message",
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)
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# Logger
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callback.setup(
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@@ -488,10 +502,11 @@ with gr.Blocks(css=css, theme=my_theme) as demo:
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hyp,
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wer,
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ppm,
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msg
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flagging_dir="./exp/%s" % config["exp_id"],
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)
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with gr.Row():
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b2 = gr.Button("2. Save the Recording", variant="primary", elem_id="save")
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js_confirmed_saving = "(x) => confirm('Recording Saved!')"
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@@ -508,6 +523,7 @@ with gr.Blocks(css=css, theme=my_theme) as demo:
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wer,
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ppm,
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msg,
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],
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outputs=None,
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preprocess=False,
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@@ -527,9 +543,10 @@ with gr.Blocks(css=css, theme=my_theme) as demo:
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wer,
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ppm,
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msg,
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],
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value="3.Clear All",
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elem_id="clear",
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)
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demo.launch(share=
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import librosa
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import librosa.display
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import matplotlib.pyplot as plt
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from local.convert_metrics import nat2avaMOS, WER2INTELI
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# Google cloud service
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from googleapiclient.discovery import build
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"GOOD JOB! Please 【Save the Recording】.\nYou can start recording the next sample."
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)
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# Google Drive saving
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saved_google_id = None
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if error_msg == ("GOOD JOB! Please 【Save the Recording】.\nYou can start recording the next sample."):
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saved_google_id = click_google_saving(audio_path)
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# TODO: add saved_google_id to the csv file
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## else:
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## TODO: clear all output as start recording again
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## print("Saving Failed")
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return (
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fig_h,
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phone_transcription,
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ppm,
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error_msg,
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saved_google_id,
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)
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with open("src/description.html", "r", encoding="utf-8") as f:
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# Add google drive cloud saving
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def click_google_saving(audio_file,
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):
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# reference_id,
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# reference_textbox,
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request = service.files().create(
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media_body=media,
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body={'name': name, }
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)
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# 'reference_id': reference_id,
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# "reference_textbox": reference_textbox,
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# "ppm": ppm,
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# "msg": msg
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response = request.execute()
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# get saved file id
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return response.get('id')
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# return response.get('id')
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interactive=True,
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elem_classes="ref_text",
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)
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with gr.Row():
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with gr.Accordion("Input for Development", open=False):
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reference_id = gr.Textbox(
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value="ID",
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placeholder="Utter ID",
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label="Reference_ID",
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visible=True,
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)
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reference_PPM = gr.Textbox(
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placeholder="Pneumatic Voice's PPM",
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label="Ref PPM",
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visible=True,
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)
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with gr.Row():
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b = gr.Button(value="1.Submit", variant="primary", elem_classes="submit")
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interactive=False,
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elem_classes="message",
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)
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with gr.Accordion("Output for Development", open=False):
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wav_plot = gr.Plot(PlaceHolder="Wav/Pause Plot", label="wav_pause_plot", visible=True)
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predict_mos = gr.Textbox(
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placeholder="Predicted MOS",
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label="Predicted MOS",
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visible=True,
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)
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hyp = gr.Textbox(placeholder="Hypothesis", label="Hypothesis", visible=True)
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wer = gr.Textbox(placeholder="Word Error Rate", label="WER", visible=True)
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predict_pho = gr.Textbox(
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placeholder="Predicted Phonemes",
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label="Predicted Phonemes",
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visible=True,
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)
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ppm = gr.Textbox(
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placeholder="Phonemes per minutes",
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label="PPM",
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visible=True,
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)
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saved_google_drive_id = gr.Textbox(
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placeholder="Saved Google Drive ID",
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label="Saved Google Drive ID",
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visible=True,
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)
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outputs = [
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wav_plot,
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predict_mos,
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hyp,
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wer,
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predict_pho,
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ppm,
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msg,
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saved_google_drive_id
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]
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# b = gr.Button("Submit")
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b.click(fn=calc_mos, inputs=inputs, outputs=outputs, api_name="Submit")
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# Logger
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callback.setup(
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hyp,
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wer,
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ppm,
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msg,
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saved_google_drive_id],
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flagging_dir="./exp/%s" % config["exp_id"],
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)
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# Saving the Recording to CSV Logger (TO BE DELETED)
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with gr.Row():
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b2 = gr.Button("2. Save the Recording", variant="primary", elem_id="save")
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js_confirmed_saving = "(x) => confirm('Recording Saved!')"
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wer,
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ppm,
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msg,
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saved_google_drive_id
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],
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outputs=None,
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preprocess=False,
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wer,
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ppm,
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msg,
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saved_google_drive_id
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],
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value="3.Clear All",
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elem_id="clear",
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)
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demo.launch(share=False)
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config/Arthur.yaml
CHANGED
@@ -3,10 +3,10 @@ ref_txt: data/Arthur_the_rat.txt
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ref_feature: data/Patient_sil_trim_16k_normed_5_snr_40/Arthur_the_rat.csv
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ref_wavs: data/Patient_sil_trim_16k_normed_5_snr_40/Arthur_the_rat
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thre:
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minppm:
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maxppm:
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WER: 0.
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AUTOMOS:
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auth:
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username: Kath
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password: Kath
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ref_feature: data/Patient_sil_trim_16k_normed_5_snr_40/Arthur_the_rat.csv
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ref_wavs: data/Patient_sil_trim_16k_normed_5_snr_40/Arthur_the_rat
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thre:
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minppm: 300
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maxppm: 300
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WER: 0.5
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AUTOMOS: 2.0
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auth:
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username: Kath
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password: Kath
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local/check_data.py
CHANGED
@@ -2,9 +2,11 @@ from googleapiclient.discovery import build
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from google.oauth2 import service_account
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from googleapiclient.http import MediaFileUpload
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import pdb
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pdb.set_trace()
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import gradio as gr
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# 来自Google Cloud控制台的JSON凭据文件
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credentials_file = "./src/peerless-window-254907-b386b71c0d99.json"
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print(files)
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from googleapiclient.http import MediaIoBaseDownload
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import io
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file_id =
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# Get the file's metadata
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file = service.files().get(fileId=file_id).execute()
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request = service.files().get_media(fileId="1YjON2ObGM826KaaqF-sKM7CO0tAtzWGg")
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with open(file['name'], 'wb') as file_obj:
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downloader = MediaIoBaseDownload(file_obj, request)
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done = False
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print(f"Downloaded: {file['name']}")
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pdb.set_trace()
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# print('文件ID:%s' % response.get('id'))
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from google.oauth2 import service_account
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from googleapiclient.http import MediaFileUpload
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import pdb
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import gradio as gr
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'''
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Usage: python loacl/checkdata.py <google_file_id>
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'''
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# 来自Google Cloud控制台的JSON凭据文件
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credentials_file = "./src/peerless-window-254907-b386b71c0d99.json"
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print(files)
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from googleapiclient.http import MediaIoBaseDownload
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import io
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import sys
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file_id = sys.argv[1]
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# "1YjON2ObGM826KaaqF-sKM7CO0tAtzWGg"
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# Get the file's metadata
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file = service.files().get(fileId=file_id).execute()
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request = service.files().get_media(fileId=file_id)
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with open(file['name'], 'wb') as file_obj:
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downloader = MediaIoBaseDownload(file_obj, request)
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done = False
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print(f"Downloaded: {file['name']}")
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pdb.set_trace()
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local/convert_metrics.py
ADDED
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import numpy as np
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import matplotlib.pyplot as plt
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# Natural MOS to AVA MOS
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def linear_function(x):
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m = (4 - 1) / (1.5 - 1)
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b = 1 - m * 1
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return m * x + b
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def quadratic_function(x):
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return -0.0816 * (x - 5) ** 2 + 5
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# Natural MOS to AVA MOS
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def nat2avaMOS(x):
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if x <= 1.5:
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return linear_function(x)
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elif x >1.5 and x <= 5:
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return quadratic_function(x)
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# Word error rate to Intellibility Score (X is percentage)
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def WER2INTELI(x):
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if x <= 10:
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return 100
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elif x <= 100:
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slope = (30 - 100) / (100 - 10)
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intercept = 100 - slope * 10
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return slope * x + intercept
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else:
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return 100 * np.exp(-0.01 * (x - 100))
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# 生成 x 值
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# x = np.linspace(0, 200, 400) # 从0到200生成400个点
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# 计算对应的 y 值
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# y = [WER2INTELI(xi) for xi in x]
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# plt.plot(x, y)
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# plt.xlabel('x')
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# plt.ylabel('f(x)')
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# plt.title('Custom Function')
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# plt.grid(True)
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# plt.show()
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# 生成 x 值的范围
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x1 = np.linspace(1, 1.5, 100)
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x2 = np.linspace(1.5, 5, 100)
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# 计算对应的 y 值
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y1 = linear_function(x1)
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y2 = quadratic_function(x2)
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# 绘制线性部分
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plt.plot(x1, y1, label='Linear Function (1 <= x <= 1.5)')
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# 绘制二次部分
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plt.plot(x2, y2, label='Quadratic Function (1.5 <= x <= 5)')
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# 添加标签和标题
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plt.xlabel('Natural Mean Opinion Score')
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plt.ylabel('AVA Mean Opinion Score')
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plt.title('nat2avaMOS')
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# 添加图例
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plt.legend()
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# 显示图形
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plt.grid(True)
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# 显示图像
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# plt.savefig("./local/nat2avaMOS.png")
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# plt.savefig("./local/WER2INT.png")
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