import json import os import re import librosa import numpy as np import torch from torch import no_grad, LongTensor import commons import utils import gradio as gr from models import SynthesizerTrn from text import text_to_sequence from text.symbols import symbols limitation = os.getenv("SYSTEM") == "spaces" # limit text and audio length in huggingface spaces def get_text(text, hps): text_norm = text_to_sequence(text, hps.data.text_cleaners) if hps.data.add_blank: text_norm = commons.intersperse(text_norm, 0) text_norm = torch.LongTensor(text_norm) return text_norm def create_tts_fn(net_g, hps, speaker_ids): def tts_fn(text, speaker, speed): if limitation: text_len = len(text) max_len = 5000 if text_len > max_len: return "Error: Text is too long", None speaker_id = speaker_ids[speaker] stn_tst = get_text(text, hps) with no_grad(): x_tst = stn_tst.unsqueeze(0) x_tst_lengths = LongTensor([stn_tst.size(0)]) sid = LongTensor([speaker_id]) audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.8, length_scale=1.0 / speed)[0][0, 0].data.cpu().float().numpy() del stn_tst, x_tst, x_tst_lengths, sid return "Success", (hps.data.sampling_rate, audio) return tts_fn css = """ #advanced-btn { color: white; border-color: black; background: black; font-size: .7rem !important; line-height: 19px; margin-top: 24px; margin-bottom: 12px; padding: 2px 8px; border-radius: 14px !important; } #advanced-options { display: none; margin-bottom: 20px; } """ if __name__ == '__main__': models_tts = [] name = 'AronaTTS' lang = '일본어 / 한국어 (Japanese / Korean)' example = '[JA]先生、今日は天気が本当にいいですね。[JA][KO]선생님, 안녕하세요. my name is arona[KO]' config_path = f"pretrained_model/arona_ms_istft_vits.json" model_path = f"pretrained_model/arona_ms_istft_vits.pth" cover_path = f"pretrained_model/cover.gif" hps = utils.get_hparams_from_file(config_path) net_g = SynthesizerTrn( len(symbols), hps.data.filter_length // 2 + 1, hps.train.segment_size // hps.data.hop_length, n_speakers=hps.data.n_speakers, **hps.model) _ = net_g.eval() utils.load_checkpoint(model_path, net_g, None) net_g.eval() speaker_ids = [0] speakers = [name] t = 'vits' models_tts.append((name, cover_path, speakers, lang, example, hps.symbols, create_tts_fn(net_g, hps, speaker_ids))) app = gr.Blocks(css=css) with app: gr.Markdown("# BlueArchive Arona TTS Using VITS Model\n" "![visitor badge](https://visitor-badge.glitch.me/badge?page_id=openduckparty.AronaTTS)\n\n") for i, (name, cover_path, speakers, lang, example, symbols, tts_fn ) in enumerate(models_tts): with gr.Column(): gr.Markdown(f"## {name}\n\n" f"![cover](file/{cover_path})\n\n" f"lang: {lang}") tts_input1 = gr.TextArea(label="Text (5000 words limitation)", value=example, elem_id=f"tts-input{i}") tts_input2 = gr.Dropdown(label="Speaker", choices=speakers, type="index", value=speakers[0]) tts_input3 = gr.Slider(label="Speed", value=1, minimum=0.1, maximum=2, step=0.1) tts_submit = gr.Button("Generate", variant="primary") tts_output1 = gr.Textbox(label="Output Message") tts_output2 = gr.Audio(label="Output Audio") tts_submit.click(tts_fn, [tts_input1, tts_input2, tts_input3], [tts_output1, tts_output2]) _js=f""" (i,phonemes) => {{ let root = document.querySelector("body > gradio-app"); if (root.shadowRoot != null) root = root.shadowRoot; let text_input = root.querySelector("#tts-input{i}").querySelector("textarea"); let startPos = text_input.selectionStart; let endPos = text_input.selectionEnd; let oldTxt = text_input.value; let result = oldTxt.substring(0, startPos) + phonemes[i] + oldTxt.substring(endPos); text_input.value = result; let x = window.scrollX, y = window.scrollY; text_input.focus(); text_input.selectionStart = startPos + phonemes[i].length; text_input.selectionEnd = startPos + phonemes[i].length; text_input.blur(); window.scrollTo(x, y); return []; }}""" app.queue(concurrency_count=3).launch(show_api=False)