app.py

import gradio as gr
from gtts import gTTS
import time
import difflib
import tempfile
import os
import speech_recognition as sr

# Function to play the text (optional)
def play_text(text):
    tts = gTTS(text=text, lang='hi', slow=False)
    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp3')
    tts.save(temp_file.name)
    os.system(f"start {temp_file.name}")  # Windows
    return "✅ Text is being read out. Please listen and read it yourself."

# Function to transcribe user's audio and compare with the original text
def transcribe_audio(audio, original_text):
    recognizer = sr.Recognizer()
    with sr.AudioFile(audio) as source:
        audio_data = recognizer.record(source)
    
    try:
        start_time = time.time()
        # Split the audio into chunks (1-minute chunks in this example)
        audio_length = len(audio_data.frame_data)
        chunk_size = 60000  # 1 minute (60,000 ms)
        
        # Splitting audio data into chunks
        chunks = [audio_data.frame_data[i:i+chunk_size] for i in range(0, audio_length, chunk_size)]
        
        transcription = ""
        for chunk in chunks:
            audio_chunk = sr.AudioData(chunk, audio_data.sample_rate, audio_data.sample_width)
            # Using Google Speech Recognition (supports Hindi)
            transcription += recognizer.recognize_google(audio_chunk, language="hi-IN") + " "
        
        end_time = time.time()
        
        # Calculate Accuracy
        original_words = original_text.strip().split()
        transcribed_words = transcription.strip().split()
        matcher = difflib.SequenceMatcher(None, original_words, transcribed_words)
        accuracy = round(matcher.ratio() * 100, 2)
        
        # Calculate speed
        duration = end_time - start_time  # time to process (not speaking time)
        speed = round(len(transcribed_words) / duration, 2)  # words per second
        
        # Compare words and highlight mistakes
        wrong_words = []
        for i, word in enumerate(original_words):
            if i >= len(transcribed_words) or word != transcribed_words[i]:
                wrong_words.append(f"🔴 {word}")
        
        result = {
            "📝 Transcribed Text": transcription,
            "🎯 Accuracy (%)": accuracy,
            "⏱️ Speaking Speed (words/sec)": speed,
            "❌ Incorrect Words": ' '.join(wrong_words) if wrong_words else "None"
        }
        return result
    except Exception as e:
        return {"error": str(e)}

# Gradio App
with gr.Blocks() as app:
    gr.Markdown("## 🗣️ Hindi Reading & Pronunciation Practice App")
    
    with gr.Row():
        input_text = gr.Textbox(label="Paste Hindi Text Here", placeholder="यहाँ हिंदी टेक्स्ट लिखें...")
        play_button = gr.Button("🔊 Listen to Text")

    play_button.click(play_text, inputs=[input_text], outputs=[])

    gr.Markdown("### 🎤 Now upload or record yourself reading the text aloud below:")
    audio_input = gr.Audio(type="filepath", label="Upload or Record Your Voice")
    
    submit_button = gr.Button("✅ Submit Recording for Checking")
    
    output = gr.JSON(label="Results")
    
    submit_button.click(transcribe_audio, inputs=[audio_input, input_text], outputs=[output])

# Launch the app
app.launch()