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| import os | |
| import gradio as gr | |
| import whisper | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| from gtts import gTTS | |
| import sentencepiece | |
| def translate_voice(file, target_lang): | |
| try: | |
| # Load the model and switch to float32 | |
| model = whisper.load_model("base").float() | |
| # Load the audio | |
| audio = whisper.load_audio(file.name) | |
| # Pad or trim the audio | |
| audio = whisper.pad_or_trim(audio) | |
| # Convert the audio to a log Mel spectrogram and move it to the same device as the model (CPU in your case) | |
| mel = whisper.log_mel_spectrogram(audio).to(model.device).float() # convert to full-precision float32 | |
| # Proceed with your language detection and decoding | |
| _, probs = model.detect_language(mel) | |
| options = whisper.DecodingOptions() | |
| result = whisper.decode(model, mel, options) | |
| text = result.text | |
| lang = max(probs, key=probs.get) | |
| # Translate | |
| tokenizer = AutoTokenizer.from_pretrained("alirezamsh/small100") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("alirezamsh/small100") | |
| tokenizer.src_lang = target_lang | |
| encoded_bg = tokenizer(text, return_tensors="pt") | |
| generated_tokens = model.generate(**encoded_bg) | |
| translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0] | |
| # Text-to-audio (TTS) | |
| tts = gTTS(text=translated_text, lang=target_lang) | |
| filename = "to_speech.mp3" | |
| tts.save(filename) | |
| return filename, text, translated_text, target_lang | |
| except Exception as e: | |
| return str(e), "", "", "" | |
| iface = gr.Interface( | |
| fn=translate_voice, | |
| inputs=[ | |
| gr.inputs.File(label="Your Audio"), | |
| gr.inputs.Dropdown(choices=['en', 'ru', 'de', 'fr'], label="Target Language") | |
| ], | |
| outputs=[ | |
| gr.outputs.Audio(type="filepath", label="Translated Audio"), | |
| gr.outputs.Textbox(label="Original Text"), | |
| gr.outputs.Textbox(label="Translated Text"), | |
| gr.outputs.Textbox(label="Target Language"), | |
| ] | |
| ) | |
| iface.launch() | |