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| import os | |
| os.environ['CUDA_VISIBLE_DEVICES'] = '' | |
| os.environ['TF_FORCE_GPU_ALLOW_GROWTH'] = 'true' | |
| from huggingface_hub import snapshot_download | |
| from malaya_speech.torch_model.vits.model_infer import SynthesizerTrn | |
| from malaya_speech.torch_model.vits.commons import intersperse | |
| from malaya_speech.utils.text import TTS_SYMBOLS | |
| from malaya_speech.tts import load_text_ids | |
| from malaya_speech.utils.astype import float_to_int | |
| import gradio as gr | |
| import torch | |
| import os | |
| import json | |
| try: | |
| from malaya_boilerplate.hparams import HParams | |
| except BaseException: | |
| from malaya_boilerplate.train.config import HParams | |
| speaker_id = { | |
| 'Husein': 0, | |
| 'Shafiqah Idayu': 1, | |
| } | |
| normalizer = load_text_ids(pad_to = None, understand_punct = True, is_lower = False) | |
| folder = snapshot_download(repo_id="malaysia-ai/malay-VITS-multispeaker") | |
| with open(os.path.join(folder, 'config.json')) as fopen: | |
| hps = HParams(**json.load(fopen)) | |
| model = SynthesizerTrn( | |
| len(TTS_SYMBOLS), | |
| hps.data.filter_length // 2 + 1, | |
| hps.train.segment_size // hps.data.hop_length, | |
| n_speakers=hps.data.n_speakers, | |
| **hps.model, | |
| ).eval() | |
| model.load_state_dict(torch.load(os.path.join(folder, 'model.pth'), map_location='cpu')) | |
| def tts(text, speaker, temperature, length_ratio): | |
| if len(text) < 1: | |
| raise gr.Error('input text must longer than 0') | |
| if speaker not in speaker_id: | |
| raise gr.Error('speaker is not available') | |
| t, ids = normalizer.normalize(text, add_fullstop = True) | |
| if hps.data.add_blank: | |
| ids = intersperse(ids, 0) | |
| ids = torch.LongTensor(ids) | |
| ids_lengths = torch.LongTensor([ids.size(0)]) | |
| ids = ids.unsqueeze(0) | |
| sid = torch.tensor([speaker_id[speaker]]) | |
| with torch.no_grad(): | |
| audio = model.infer( | |
| ids, | |
| ids_lengths, | |
| noise_scale=0.0, | |
| noise_scale_w=0.0, | |
| length_scale=1.0, | |
| sid=sid, | |
| ) | |
| y_ = audio[0].numpy() | |
| data = float_to_int(y_[0, 0]) | |
| return (22050, data) | |
| demo = gr.Interface( | |
| fn=tts, | |
| inputs=[ | |
| gr.components.Textbox(label='Text'), | |
| gr.components.Dropdown(label='Available speakers', choices=list(speaker_id.keys()), value = 'Husein'), | |
| gr.Slider(0.0, 1.0, value=0.6666, label='temperature, changing this will manipulate pitch'), | |
| gr.Slider(0.0, 3.0, value=1.0, label='length ratio, changing this will manipulate duration output'), | |
| ], | |
| outputs=['audio'], | |
| examples=[ | |
| ['Syed Saddiq berkata, mereka seharusnya mengingati bahawa semasa menjadi Perdana Menteri Pakatan Harapan', 'Husein', 0.6666, 1.0], | |
| ['Shah Alam - Pertubuhan Kebajikan Anak Bersatu Selangor bersetuju pihak kerajaan mewujudkan Suruhanjaya Siasatan Diraja untuk menyiasat isu kartel daging.', 'Shafiqah Idayu', 0.6666, 1.0], | |
| ], | |
| cache_examples=False, | |
| title='End-to-End Malay TTS using VITS', | |
| ) | |
| demo.queue().launch(server_name='0.0.0.0') | |