Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from gtts import gTTS
+import tempfile
+
+# Load ASR & Translation models
+asr_model = pipeline("automatic-speech-recognition", model="openai/whisper-medium", device=0)
+translator = pipeline("translation", model="ai4bharat/indictrans2-en-indic", device=0)
+
+# Map language names to codes
+lang_code_map = {
+    "Hindi": "hi", "Kannada": "kn", "Tamil": "ta", "Telugu": "te", "Bengali": "bn", "Marathi": "mr",
+    "Gujarati": "gu", "Punjabi": "pa", "Malayalam": "ml", "Assamese": "as", "Odia": "or", "Urdu": "ur",
+    "Sanskrit": "sa", "Nepali": "ne", "Manipuri": "mni", "English": "en"
+}
+
+languages = list(lang_code_map.keys())
+
+def process_speech(audio, speaker_lang, listener_lang):
+    # Step 1: Speech → Text
+    transcript = asr_model(audio)["text"]
+
+    # Step 2: Translate
+    try:
+        result = translator(transcript, src_lang=speaker_lang.lower(), tgt_lang=listener_lang.lower())
+        translated_text = result[0]["translation_text"]
+    except:
+        translated_text = "[Translation failed]"
+
+    # Step 3: Text → Speech
+    tts_lang = lang_code_map.get(listener_lang, "en")
+    tts = gTTS(translated_text, lang=tts_lang)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as f:
+        tts.save(f.name)
+        return transcript, translated_text, f.name
+
+# Gradio UI
+with gr.Blocks(title="Indian Language Speech Translator") as demo:
+    gr.Markdown("## 🗣️ Real-Time Indian Speech Translator")
+    gr.Markdown("Choose two languages and take turns speaking. The app will translate and speak for you in real-time.")
+
+    with gr.Row():
+        speaker_lang = gr.Dropdown(choices=languages, value="Hindi", label="🎙️ Speaker's Language")
+        listener_lang = gr.Dropdown(choices=languages, value="Kannada", label="👂 Listener's Language")
+
+    audio_input = gr.Audio(source="microphone", type="filepath", label="🎤 Speak here")
+
+    with gr.Row():
+        transcript_box = gr.Textbox(label="📝 Recognized Speech")
+        translation_box = gr.Textbox(label="🌐 Translated Text")
+
+    audio_output = gr.Audio(label="🔊 Translated Speech")
+
+    btn = gr.Button("Translate & Speak")
+
+    btn.click(
+        fn=process_speech,
+        inputs=[audio_input, speaker_lang, listener_lang],
+        outputs=[transcript_box, translation_box, audio_output]
+    )
+
+demo.launch()