# -*- coding: utf-8 -*- import gradio as gr from models import SynthesizerTrn from khmer_phonemizer import phonemize_single import utils import commons import torch import khmernormalizer _pad = "_" _punctuation = ". " _letters_ipa = "acefhijklmnoprstuwzĕŋŏŭɑɓɔɗəɛɡɨɲʋʔʰː" # Export all symbols: symbols = [_pad] + list(_punctuation) + list(_letters_ipa) # Special symbol ids SPACE_ID = symbols.index(" ") _symbol_to_id = {s: i for i, s in enumerate(symbols)} def text_to_sequence(text): sequence = [] for symbol in text: symbol_id = _symbol_to_id[symbol] sequence += [symbol_id] return sequence def get_text(text, hps): text_norm = text_to_sequence(text) if hps.data.add_blank: text_norm = commons.intersperse(text_norm, 0) text_norm = torch.LongTensor(text_norm) return text_norm hps = utils.get_hparams_from_file("config.json") net_g = SynthesizerTrn( len(symbols), hps.data.filter_length // 2 + 1, hps.train.segment_size // hps.data.hop_length, **hps.model ) _ = net_g.eval() _ = utils.load_checkpoint("G_35000.pth", net_g, None) def generate_voice(text): text = khmernormalizer.normalize(text) text = " ".join(phonemize_single(text) + ["."]) stn_tst = get_text(text, hps) with torch.no_grad(): x_tst = stn_tst.unsqueeze(0) x_tst_lengths = torch.LongTensor([stn_tst.size(0)]) audio = ( net_g.infer( x_tst, x_tst_lengths, noise_scale=0.667, noise_scale_w=0.8, length_scale=1, )[0][0, 0] .data.cpu() .float() .numpy() ) return (hps.data.sampling_rate, audio) with gr.Blocks( title="Khmer Word to Speech", theme=gr.themes.Default( font=[gr.themes.GoogleFont("Noto Sans Khmer"), "Arial", "sans-serif"] ), ) as blocks: gr.Markdown("# Khmer Word to Speech") input_text = gr.Text(label="ពាក្យខ្លី", lines=1) examples = gr.Examples(examples=["មនុស្សជាតិ", "ភ្នំព្រះ"], inputs=[input_text]) run_button = gr.Button(value="បង្កើត") out_audio = gr.Audio( label="សំឡេងដែលបានបង្កើត", type="numpy", ) inputs = [input_text] outputs = [out_audio] run_button.click( fn=generate_voice, inputs=inputs, outputs=outputs, queue=True, ) blocks.queue(concurrency_count=1).launch(debug=True)