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import time |
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import torch |
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from transformers import set_seed |
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from transformers import VitsTokenizer, VitsModel |
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def synthesize_facebook(s:str, iso3:str) -> str: |
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''' |
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For given text, speak it. |
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Parameters |
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---------- |
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s: str |
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The written text. |
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is03:str |
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The ISO-3 code of the text's language. |
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Returns |
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---------- |
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synth:str |
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The synthesized audio. |
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''' |
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set_seed(555) |
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start_time = time.time() |
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tokenizer = VitsTokenizer.from_pretrained(f"facebook/mms-tts-{iso3}") |
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model = VitsModel.from_pretrained(f"facebook/mms-tts-{iso3}") |
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inputs = tokenizer(text=s, return_tensors="pt") |
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with torch.no_grad(): |
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outputs = model(**inputs) |
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synth = outputs.waveform[0] |
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print("Time elapsed: ", int(time.time() - start_time), " seconds") |
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return synth.numpy() |
