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import gradio as gr # needs to be installed
from dataset import Dataset
dataset = Dataset()
def eval(data_subset:str, model_1:str, model_2:str, model_3:str)->str:
result = f"""# HELLO THERE
Data Subset: {data_subset}
Model 1: {model_1}
Model 2: {model_2}
Model_3: {model_3}
"""
return result
def get_card(selected_model:str)->str:
if selected_model == "None":
return ""
elif selected_model == "Model2":
return "A very good model indeed"
elif selected_model == "Model3":
return "Also very good"
else:
return "Unknown Model"
def is_own(data_subset:str):
if data_subset == "own":
own_audio = gr.Audio(sources=['microphone'],streaming=False)
own_transcription = gr.TextArea(lines=2)
return own_audio, own_transcription
own_audio = None
own_transcription = None
return own_audio, own_transcription
with gr.Blocks() as app:
gr.Markdown("# VocalVenturer 💬")
gr.Markdown("-------")
gr.Markdown("""
Hello there, this is the VocalVenturer, this app is aimed at helping you making more informed model choices for ASR.
Please choose a Data Subset to evalutate the Models on. You also have the opportunity to record and transcibe an own sample.
The Models will be evaluated using the *WER* metric -> here is an amazing Leaderboard for it LINK""")
with gr.Row():
with gr.Column(scale=1):
pass
with gr.Column(scale=3):
data_subset = gr.Radio(
value="Libris",
choices=["Libris","Common","own"],
label="Data subset / Own Sample",
)
with gr.Column(scale=1):
pass
with gr.Row():
own_audio = gr.Audio(sources=['microphone'],streaming=False,visible=False)
own_transcription = gr.TextArea(lines=2, visible=False)
data_subset.change(is_own, inputs=[data_subset], outputs=[own_audio, own_transcription])
with gr.Row():
with gr.Column(scale=1):
model_1 = gr.Dropdown(
choices=["None","Model2","Model3"],
label="Select Model 1"
)
model_1_card = gr.Markdown("")
with gr.Column(scale=1):
model_2 = gr.Dropdown(
choices=["None","Model2","Model3"],
label="Select Model 2"
)
model_2_card = gr.Markdown("")
with gr.Column(scale=1):
model_3 = gr.Dropdown(
choices=["None","Model2","Model3"],
label="Select Model 3"
)
model_3_card = gr.Markdown("")
model_1.change(get_card, inputs=model_1, outputs=model_1_card)
model_2.change(get_card, inputs=model_2, outputs=model_2_card)
model_3.change(get_card, inputs=model_3, outputs=model_3_card)
eval_btn = gr.Button(
value="Evaluate",
variant="primary"
)
gr.Markdown("-------")
gr.Markdown("### Results")
results = gr.Markdown("")
eval_btn.click(eval, [data_subset, model_1, model_2, model_3], results)
app.launch(debug=True) |