Create app.py

app.py

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+import torch
+import soundfile as sf
+import numpy as np
+import gradio as gr
+from transformers import VitsModel, MBartForConditionalGeneration, AutoTokenizer, pipeline
+
+# Load the models and tokenizers
+transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
+translation_tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-50-one-to-many-mmt", use_fast=False)
+translation_model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-one-to-many-mmt")
+tts_tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-hin")
+tts_model = VitsModel.from_pretrained("facebook/mms-tts-hin")
+
+def process_audio(audio):
+    if audio is None:
+        return "No audio provided.", None
+
+    sr, y = audio
+    y = y.astype(np.float32)
+    y /= np.max(np.abs(y))
+
+    # Transcribe the audio
+    transcription = transcriber({"sampling_rate": sr, "raw": y})["text"]
+
+    # Translate from English to Hindi
+    model_inputs = translation_tokenizer(transcription, return_tensors="pt", padding=True, truncation=True)
+    generated_tokens = translation_model.generate(
+        **model_inputs,
+        forced_bos_token_id=translation_tokenizer.lang_code_to_id["hi_IN"]
+    )
+    translated_text = translation_tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+
+    # Generate Hindi speech from translated text
+    tts_inputs = tts_tokenizer(translated_text, return_tensors="pt")
+    try:
+        with torch.no_grad():
+            tts_output = tts_model(**tts_inputs)
+            waveform = tts_output.waveform.squeeze().cpu().numpy()
+    except RuntimeError as e:
+        return f"Runtime Error: {e}", None
+
+    # Save the waveform to an audio file
+    audio_path = 'output.wav'
+    sf.write(audio_path, waveform, 22050)
+
+    return audio_path
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=process_audio,
+    inputs=gr.Audio(sources=["microphone"], type="numpy"),
+    outputs="audio",
+    title="Speech-to-Hindi",
+    description="Record your speech or upload an audio file to transcribe, translate to Hindi, and convert to speech."
+)
+
+# Launch the Gradio app
+demo.launch(debug=True)