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import spaces |
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import gradio as gr |
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import librosa |
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import numpy as np |
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import torch |
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from transformers import pipeline |
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synthesiser = pipeline("text-to-speech", "techiaith/microsoft_speecht5_finetuned_bu_tts_cy_en") |
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speaker_embeddings = { |
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"GGP": "spkemb/speaker0.npy", |
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"BGP": "spkemb/speaker1.npy", |
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"BDP": "spkemb/speaker2.npy", |
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} |
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@spaces.GPU |
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def predict(text, speaker): |
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if len(text.strip()) == 0: |
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return (16000, np.zeros(0).astype(np.int16)) |
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input_ids = inputs["input_ids"] |
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input_ids = input_ids[..., :model.config.max_text_positions] |
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if speaker == "Surprise Me!": |
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idx = np.random.randint(len(speaker_embeddings)) |
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key = list(speaker_embeddings.keys())[idx] |
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speaker_embedding = np.load(speaker_embeddings[key]) |
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np.random.shuffle(speaker_embedding) |
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x = (np.random.rand(512) >= 0.5) * 1.0 |
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x[x == 0] = -1.0 |
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speaker_embedding *= x |
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else: |
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speaker_embedding = np.load(speaker_embeddings[speaker[:3]]) |
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speaker_embedding = torch.tensor(speaker_embedding).unsqueeze(0) |
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speech = synthesiser(text, forward_params={"speaker_embeddings": speaker_embedding}) |
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speech = (speech.numpy() * 32767).astype(np.int16) |
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return (16000, speech) |
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title = "Techiaith Finetune Microsoft/SpeechT5: Speech Synthesis" |
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description = """ |
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Lleisiau TTS microsoft_speech_T5_finetune_bu_tts_cy_en |
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""" |
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examples = [ |
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["Rhyfeddod neu ffenomenon optegol a meteorolegol yw enfys, pan fydd sbectrwm o olau yn ymddangos yn yr awyr pan fo'r haul yn disgleirio ar ddiferion o leithder yn atmosffer y ddaear.", "GGP (gwryw-gogledd-pro)"], |
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["Rhyfeddod neu ffenomenon optegol a meteorolegol yw enfys, pan fydd sbectrwm o olau yn ymddangos yn yr awyr pan fo'r haul yn disgleirio ar ddiferion o leithder yn atmosffer y ddaear.", "BGP (benyw-gogledd-pro)"], |
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["Rhyfeddod neu ffenomenon optegol a meteorolegol yw enfys, pan fydd sbectrwm o olau yn ymddangos yn yr awyr pan fo'r haul yn disgleirio ar ddiferion o leithder yn atmosffer y ddaear.", "BDP (benyw-de-pro)"], |
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] |
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gr.Interface( |
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fn=predict, |
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inputs=[ |
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gr.Text(label="Input Text"), |
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gr.Radio(label="Speaker", choices=[ |
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"GGP (gwryw-gogledd-pro)", |
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"BGP (benyw-gogledd-pro)", |
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"BDP (benyw-de-pro)", |
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"Surprise Me!" |
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], |
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value="GGP (gwryw-gogledd-pro)"), |
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], |
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outputs=[ |
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gr.Audio(label="Generated Speech", type="numpy"), |
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], |
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title=title, |
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description=description, |
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examples=examples, |
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).launch() |
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