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import speech_recognition as sr
import difflib
import gradio as gr
# Step 1: Transcribe the audio file
def transcribe_audio(audio):
recognizer = sr.Recognizer()
# Convert audio into recognizable format for the Recognizer
audio_file = sr.AudioFile(audio.name)
with audio_file as source:
audio_data = recognizer.record(source)
try:
# Recognize the audio using Google Web Speech API
print("Transcribing the audio...")
transcription = recognizer.recognize_google(audio_data)
print("Transcription completed.")
return transcription
except sr.UnknownValueError:
return "Google Speech Recognition could not understand the audio"
except sr.RequestError as e:
return f"Error with Google Speech Recognition service: {e}"
# Step 2: Compare the transcribed text with the input paragraph
def compare_texts(reference_text, transcribed_text):
word_scores = []
reference_words = reference_text.split()
transcribed_words = transcribed_text.split()
sm = difflib.SequenceMatcher(None, reference_text, transcribed_text)
similarity_score = round(sm.ratio() * 100, 2)
for i, word in enumerate(reference_words):
try:
if word.lower() == transcribed_words[i].lower():
word_scores.append({"word": word, "quality_score": 100})
else:
word_scores.append({"word": word, "quality_score": 50}) # Assuming 50 if it's wrong
except IndexError:
word_scores.append({"word": word, "quality_score": 0})
fidelity_class = "CORRECT" if similarity_score > 50 else "INCORRECT"
output = {
"quota_remaining": -1,
"reference_text_from_application": reference_text,
"status": "success",
"text_score": {
"fidelity_class": fidelity_class,
"quality_score": similarity_score,
"text": reference_text,
"transcribedText": transcribed_text,
"word_score_list": word_scores
},
"version": "1.1"
}
return output
# Gradio Interface Function
def gradio_function(paragraph, audio):
# Transcribe the audio
transcribed_text = transcribe_audio(audio)
# Compare the original paragraph with the transcribed text
comparison_result = compare_texts(paragraph, transcribed_text)
# Return comparison result
return comparison_result
# Gradio Interface
interface = gr.Interface(
fn=gradio_function,
inputs=[
gr.inputs.Textbox(lines=5, label="Input Paragraph"),
gr.inputs.Audio(source="microphone", type="file", label="Record Audio")
],
outputs="json",
title="Speech Recognition Comparison",
description="Input a paragraph, record your audio, and compare the transcription to the original text."
)
# Launch Gradio app
interface.launch()
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