mirror of https://github.com/coqui-ai/TTS.git
model path changes for server and string strip
This commit is contained in:
Eren Golge
parent
83b1c7d1cb
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## TTS example web-server
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Steps to run:
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1. Download one of the models given on the main page.
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2. Checkout the corresponding commit history.
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2. Set paths and other options in the file ```server/conf.json```.
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3. Run the server ```python server/server.py -c conf.json```. (Requires Flask)
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4. Go to ```localhost:[given_port]``` and enjoy.
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Note that the audio quality on browser is slightly worse due to the encoder quantization.
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{
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"model_path":"/data/shared/erogol_models/May-25-2018_03:01PM-loc-sens-attention-ad94312",
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"model_name":"checkpoint_291024.pth.tar",
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"model_config":"config.json",
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"port": 5000,
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"use_cuda": true
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}
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#!flask/bin/python
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import argparse
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from synthesizer import Synthesizer
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from TTS.utils.generic_utils import load_config
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from flask import (Flask, Response, request,
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render_template, send_file)
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parser = argparse.ArgumentParser()
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parser.add_argument('-c', '--config_path', type=str,
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help='path to config file for training')
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args = parser.parse_args()
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config = load_config(args.config_path)
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app = Flask(__name__)
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synthesizer = Synthesizer()
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synthesizer.load_model(config.model_path, config.model_name,
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config.model_config, config.use_cuda)
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@app.route('/')
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def index():
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return render_template('index.html')
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@app.route('/api/tts', methods=['GET'])
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def tts():
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text = request.args.get('text')
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print(" > Model input: {}".format(text))
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data = synthesizer.tts(text)
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return send_file(data,
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mimetype='audio/wav')
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if __name__ == '__main__':
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app.run(debug=True, host='0.0.0.0', port=config.port)
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import io
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import os
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import librosa
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import torch
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import scipy
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import numpy as np
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import soundfile as sf
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from TTS.utils.text import text_to_sequence
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from TTS.utils.generic_utils import load_config
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from TTS.utils.audio import AudioProcessor
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from TTS.models.tacotron import Tacotron
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from matplotlib import pylab as plt
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class Synthesizer(object):
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def load_model(self, model_path, model_name, model_config, use_cuda):
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model_config = os.path.join(model_path, model_config)
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self.model_file = os.path.join(model_path, model_name)
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print(" > Loading model ...")
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print(" | > model config: ", model_config)
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print(" | > model file: ", self.model_file)
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config = load_config(model_config)
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self.config = config
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self.use_cuda = use_cuda
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self.model = Tacotron(config.embedding_size, config.num_freq, config.num_mels, config.r)
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self.ap = AudioProcessor(config.sample_rate, config.num_mels, config.min_level_db,
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config.frame_shift_ms, config.frame_length_ms, config.preemphasis,
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config.ref_level_db, config.num_freq, config.power, griffin_lim_iters=60)
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# load model state
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if use_cuda:
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cp = torch.load(self.model_file)
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else:
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cp = torch.load(self.model_file, map_location=lambda storage, loc: storage)
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# load the model
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self.model.load_state_dict(cp['model'])
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if use_cuda:
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self.model.cuda()
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self.model.eval()
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def save_wav(self, wav, path):
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wav *= 32767 / max(1e-8, np.max(np.abs(wav)))
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# sf.write(path, wav.astype(np.int32), self.config.sample_rate, format='wav')
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# wav = librosa.util.normalize(wav.astype(np.float), norm=np.inf, axis=None)
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# wav = wav / wav.max()
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# sf.write(path, wav.astype('float'), self.config.sample_rate, format='ogg')
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scipy.io.wavfile.write(path, self.config.sample_rate, wav.astype(np.int16))
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# librosa.output.write_wav(path, wav.astype(np.int16), self.config.sample_rate, norm=True)
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def tts(self, text):
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text_cleaner = [self.config.text_cleaner]
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wavs = []
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for sen in text.split('.'):
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if len(sen) < 3:
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continue
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sen = sen.strip()
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sen +='.'
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print(sen)
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sen = sen.strip()
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seq = np.array(text_to_sequence(text, text_cleaner))
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chars_var = torch.from_numpy(seq).unsqueeze(0)
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if self.use_cuda:
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chars_var = chars_var.cuda()
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mel_out, linear_out, alignments, stop_tokens = self.model.forward(chars_var)
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linear_out = linear_out[0].data.cpu().numpy()
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wav = self.ap.inv_spectrogram(linear_out.T)
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# wav = wav[:self.ap.find_endpoint(wav)]
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out = io.BytesIO()
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wavs.append(wav)
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wavs.append(np.zeros(10000))
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self.save_wav(wav, out)
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return out
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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<meta name="description" content="">
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<meta name="author" content="">
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<title>Mozillia - Text2Speech engine</title>
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<!-- Bootstrap core CSS -->
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<link href="https://stackpath.bootstrapcdn.com/bootstrap/4.1.1/css/bootstrap.min.css"
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integrity="sha384-WskhaSGFgHYWDcbwN70/dfYBj47jz9qbsMId/iRN3ewGhXQFZCSftd1LZCfmhktB" crossorigin="anonymous" rel="stylesheet">
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<!-- Custom styles for this template -->
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<style>
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body {
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padding-top: 54px;
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}
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@media (min-width: 992px) {
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body {
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padding-top: 56px;
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}
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}
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</style>
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</head>
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<body>
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<!-- Navigation -->
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<nav class="navbar navbar-expand-lg navbar-dark bg-dark fixed-top">
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<div class="container">
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<a class="navbar-brand" href="#">Mozilla TTS</a>
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<button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarResponsive" aria-controls="navbarResponsive" aria-expanded="false" aria-label="Toggle navigation">
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<span class="navbar-toggler-icon"></span>
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</button>
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<div class="collapse navbar-collapse" id="navbarResponsive">
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<ul class="navbar-nav ml-auto">
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<li class="nav-item active">
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<a class="nav-link" href="#">Home
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<span class="sr-only">(current)</span>
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</a>
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</li>
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</ul>
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</div>
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</div>
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</nav>
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<!-- Page Content -->
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<div class="container">
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<div class="row">
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<div class="col-lg-12 text-center">
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<h1 class="mt-5">Mozilla TTS server example.</h1>
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<p class="lead">It is "work-in-progress" with an "far-to-be-alpha" release.</p>
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<ul class="list-unstyled">
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</ul>
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<input id="text" placeholder="Enter text" size=45 type="text" name="text">
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<button id="speak-button" name="speak">Speak</button><br/><br/>
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<audio id="audio" controls autoplay hidden></audio>
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<p id="message"></p>
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</div>
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</div>
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</div>
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<!-- Bootstrap core JavaScript -->
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<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>
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<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css"></script>
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<script>
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function q(selector) {return document.querySelector(selector)}
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q('#text').focus()
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q('#speak-button').addEventListener('click', function(e) {
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text = q('#text').value
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if (text) {
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q('#message').textContent = 'Synthesizing...'
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q('#speak-button').disabled = true
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q('#audio').hidden = true
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synthesize(text)
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}
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e.preventDefault()
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return false
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})
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function synthesize(text) {
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fetch('/api/tts?text=' + encodeURIComponent(text), {cache: 'no-cache'})
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.then(function(res) {
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if (!res.ok) throw Error(res.statusText)
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return res.blob()
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}).then(function(blob) {
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q('#message').textContent = ''
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q('#speak-button').disabled = false
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q('#audio').src = URL.createObjectURL(blob)
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q('#audio').hidden = false
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}).catch(function(err) {
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q('#message').textContent = 'Error: ' + err.message
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q('#speak-button').disabled = false
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})
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}
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</script>
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</body>
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</html>
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