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from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan |
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from datasets import load_dataset |
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import torch |
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import soundfile as sf |
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from datasets import load_dataset |
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from IPython.display import Audio |
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import streamlit as st |
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st.title("TTS-App") |
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text = st.text_input('Donnez votre text à prédire: ', ' ') |
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processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts") |
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model = SpeechT5ForTextToSpeech.from_pretrained("microsoft/speecht5_tts") |
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vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan") |
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inputs = processor(text=text, return_tensors="pt") |
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embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation") |
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speaker_embeddings = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0) |
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speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder) |
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sf.write("speech.wav", speech.numpy(), samplerate=16000) |
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audio_path="speech.wav" |
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Audio(audio_path) |
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st.audio(audio_path) |
