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| import gradio as gr | |
| import numpy as np | |
| import torch | |
| from InferenceInterfaces.Meta_FastSpeech2 import Meta_FastSpeech2 | |
| def float2pcm(sig, dtype='int16'): | |
| """ | |
| https://gist.github.com/HudsonHuang/fbdf8e9af7993fe2a91620d3fb86a182 | |
| """ | |
| sig = np.asarray(sig) | |
| if sig.dtype.kind != 'f': | |
| raise TypeError("'sig' must be a float array") | |
| dtype = np.dtype(dtype) | |
| if dtype.kind not in 'iu': | |
| raise TypeError("'dtype' must be an integer type") | |
| i = np.iinfo(dtype) | |
| abs_max = 2 ** (i.bits - 1) | |
| offset = i.min + abs_max | |
| return (sig * abs_max + offset).clip(i.min, i.max).astype(dtype) | |
| class TTS_Interface: | |
| def __init__(self): | |
| self.device = "cuda" if torch.cuda.is_available() else "cpu" | |
| self.model = Meta_FastSpeech2(device=self.device) | |
| def read(self, prompt, language): | |
| language_id_lookup = { | |
| "English" : "en", | |
| "German" : "de", | |
| "Greek" : "el", | |
| "Spanish" : "es", | |
| "Finnish" : "fi", | |
| "Russian" : "ru", | |
| "Hungarian": "hu", | |
| "Dutch" : "nl", | |
| "French" : "fr" | |
| } | |
| self.model.set_language(language_id_lookup[language]) | |
| wav = self.model(prompt) | |
| return 48000, float2pcm(wav.cpu().numpy()) | |
| meta_model = TTS_Interface() | |
| iface = gr.Interface(fn=meta_model.read, | |
| inputs=[gr.inputs.Textbox(lines=2, placeholder="write what you want the synthesis to read here...", label=" "), | |
| gr.inputs.Dropdown(['English', | |
| 'German', | |
| 'Greek', | |
| 'Spanish', | |
| 'Finnish', | |
| 'Russian', | |
| 'Hungarian', | |
| 'Dutch', | |
| 'French'], type="value", default='English', label="Language Selection")], | |
| outputs=gr.outputs.Audio(type="numpy", label=None), | |
| layout="vertical", | |
| title="IMS Toucan Multilingual Multispeaker Demo", | |
| thumbnail="Utility/toucan.png", | |
| theme="default", | |
| allow_flagging="never", | |
| allow_screenshot=False) | |
| iface.launch() | |