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Audio-transalotor

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History: 9 commits

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Rename requirements . text to requirements.txt

68c4ea5 verified 7 days ago

.gitattributes

1.52 kB

Duplicate from gradio-templates/chatbot 7 days ago
README.md

473 Bytes

initial commit 7 days ago
app.py

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import gradio as gr from transformers import pipeline from TTS.api import TTS # ----------------------------- # 1. Load Speech-to-Text (Whisper) # ----------------------------- stt = pipeline( "automatic-speech-recognition", model="openai/whisper-large-v3", device="cpu" ) # ----------------------------- # 2. Load Translation (M2M100) # ----------------------------- translator = pipeline( "translation", model="facebook/m2m100_418M" ) # List of supported languages languages = { "English": "en", "French": "fr", "Kinyarwanda": "rw", "Swahili": "sw", "German": "de", "Spanish": "es", "Portuguese": "pt", "Italian": "it", "Chinese (Mandarin)": "zh", "Japanese": "ja", "Korean": "ko", "Arabic": "ar", "Russian": "ru", } # ----------------------------- # 3. Load Text-to-Speech (XTTSv2) # ----------------------------- tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2") # ----------------------------- # MAIN FUNCTION # ----------------------------- def process_audio(audio, target_lang): # Step 1: STT text = stt(audio)["text"] # Step 2: Translate lang_code = languages[target_lang] translation = translator( text, forced_bos_token_id=translator.tokenizer.get_lang_id(lang_code) )[0]["translation_text"] # Step 3: TTS output_audio_path = "output.wav" tts.tts_to_file( text=translation, file_path=output_audio_path, speaker_wav=None, language=lang_code ) return text, translation, output_audio_path # ----------------------------- # 4. Gradio UI # ----------------------------- with gr.Blocks(css="custom.css") as app: gr.Markdown("<h1>🌍 Multilingual Voice-to-Voice AI Translator</h1>") gr.Markdown("Record or upload audio → AI Converts speech → Translates → Speaks output voice.") with gr.Row(): audio_input = gr.Audio(type="filepath", label="🎤 Upload or Record Audio") lang_input = gr.Dropdown(list(languages.keys()), label="🌐 Choose Target Language") with gr.Row(): text_out = gr.Textbox(label="📝 Transcribed Text") translation_out = gr.Textbox(label="🌍 Translated Text") audio_out = gr.Audio(label="🔊 AI Generated Voice Output") submit = gr.Button("🚀 Translate & Convert") submit.click( fn=process_audio, inputs=[audio_input, lang_input], outputs=[text_out, translation_out, audio_out] ) app.launch() 7 days ago
custom . css

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body { background-color: #f1f5f9; } h1 { text-align: center; color: #2d6cdf; font-weight: 900; } 7 days ago
requirements.txt

117 Bytes

Rename requirements . text to requirements.txt 7 days ago