initial commit

app.py

@@ -0,0 +1,102 @@
+import gradio as gr
+import whisper
+from translate import Translator
+from TTS.api import TTS
+import uuid
+from pathlib import Path
+
+
+model = whisper.load_model("base")
+tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True)
+
+def v2vtranslate(audiofile):
+
+    print("Starting transcription...")
+    transcription_result = transcribeaudio(audiofile)
+
+    if transcription_result.status == model.transcribe.error:
+      raise gr.Error(transcription_result.error)
+    else:
+      text = transcription_result.text
+      print(f"Transcribed Text: {text}")
+
+    print("Starting translation...")
+    es_translation,fr_translation,hi_translation,ja_translation = translatetext(text)
+    print(f"Translations:\nSpanish: {es_translation}\nFrench: {fr_translation}\nHindi: {hi_translation}\nJapanese: {ja_translation}")
+
+    print("Generating TTS audio files(Outside Function)...")
+    es_translation_path = readtranslation(es_translation,audiofile)
+    fr_translation_path = readtranslation(fr_translation,audiofile)
+    hi_translation_path = readtranslation(hi_translation,audiofile)
+    ja_translation_path = readtranslation(ja_translation,audiofile)
+    print(f"Generated audio paths:\nSpanish: {es_translation_path}\nFrench: {fr_translation_path}\nHindi: {hi_translation_path}\nJapanese: {ja_translation_path}")
+
+
+
+    es_path = Path(es_translation_path)
+    fr_path = Path(fr_translation_path)
+    hi_path = Path(hi_translation_path)
+    ja_path = Path(ja_translation_path)
+
+
+
+def transcribeaudio(audiofile):
+
+    print("Transcribing audio...")
+    tresult = model.transcribe(audiofile)
+
+    if "text" not in tresult:
+        print("Transcription failed.")
+        return {"status": "error", "error": "Transcription failed"}
+
+    audio = whisper.load_audio(audiofile)
+    audio = whisper.pad_or_trim(audio)
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+    _, probs = model.detect_language(mel)
+    print(f"Detected language: {max(probs, key=probs.get)}")
+
+    return tresult
+
+def translatetext(text):
+
+    translator_spanish = Translator(from_lang="en",to_lang="es")
+    es_text = translator_spanish.translate(text)
+
+    translator_french = Translator(from_lang="en",to_lang="fr")
+    fr_text = translator_french.translate(text)
+
+    translator_hindi = Translator(from_lang="en",to_lang="hi")
+    hi_text = translator_hindi.translate(text)
+
+    translator_japanese = Translator(from_lang="en",to_lang="ja")
+    ja_text = translator_japanese.translate(text)
+    print(f"Japanese Translation(Inside Function): {ja_text}")
+
+    return es_text,fr_text,hi_text,ja_text
+
+
+def readtranslation(text,audiofile):
+
+    print(f"Generating TTS for text(Inside Function): {text}")
+    output_path = f"{uuid.uuid4()}.wav"
+    tts.tts_to_file(text=text,
+                file_path=output_path,
+                speaker_wav=audiofile,
+                language="en")
+    print(f"Generated audio file at: {output_path}")
+    return output_path
+
+
+audio_input = gr.Audio(
+    sources=['microphone'],
+    type="filepath"
+    )
+demo = gr.Interface(
+    fn=v2vtranslate,
+    inputs=audio_input,
+    outputs=[gr.Audio(label="Spanish"),gr.Audio(label="French"),gr.Audio(label="Hindi"),gr.Audio(label="Japanese")]
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+translate
+TTS 
+openai-whisper