TTS/notebooks/TacotronPlayGround.ipynb

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{
"cells": [
{
"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n",
"Populating the interactive namespace from numpy and matplotlib\n"
]
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},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/miniconda3/envs/pytorch4/lib/python3.6/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['plt']\n",
"`%matplotlib` prevents importing * from pylab and numpy\n",
" \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
]
}
],
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"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"import os\n",
"import sys\n",
"import io\n",
"import torch \n",
"import time\n",
"import numpy as np\n",
"from collections import OrderedDict\n",
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"from matplotlib import pylab as plt\n",
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"\n",
"%pylab inline\n",
"rcParams[\"figure.figsize\"] = (16,5)\n",
"sys.path.append('/home/erogol/projects/')\n",
"\n",
"import librosa\n",
"import librosa.display\n",
"\n",
"from TTS.models.tacotron import Tacotron \n",
"from TTS.layers import *\n",
"from TTS.utils.data import *\n",
"from TTS.utils.audio import AudioProcessor\n",
"from TTS.utils.generic_utils import load_config\n",
"from TTS.utils.text import text_to_sequence\n",
"\n",
"import IPython\n",
"from IPython.display import Audio\n",
"from utils import *"
]
},
{
"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"\u001b[01;31mcheckpoint_34592.pth.tar\u001b[0m config.json\r\n",
"\u001b[01;31mcheckpoint_34968.pth.tar\u001b[0m events.out.tfevents.1526350247.mlc1\r\n"
]
}
],
"source": [
"ls /data/shared/erogol_models/May-14-2018_07:10PM-stop-token-separate-larger-lr-b2e09f9"
]
},
{
"cell_type": "code",
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"execution_count": 18,
"metadata": {},
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"outputs": [],
"source": [
"def tts(model, text, CONFIG, use_cuda, ap, figures=True):\n",
" t_1 = time.time()\n",
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" waveform, alignment, spectrogram, stop_tokens = create_speech(model, text, CONFIG, use_cuda, ap) \n",
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" print(\" > Run-time: {}\".format(time.time() - t_1))\n",
" if figures: \n",
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" visualize(alignment, spectrogram, stop_tokens, CONFIG) \n",
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" IPython.display.display(Audio(waveform, rate=CONFIG.sample_rate)) \n",
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" return alignment, spectrogram, stop_tokens"
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]
},
{
"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [],
"source": [
"# Set constants\n",
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"ROOT_PATH = '/data/shared/erogol_models/May-15-2018_04:12PM-stop-token-rnn-40f1a3d/'\n",
"MODEL_PATH = ROOT_PATH + '/checkpoint_16920.pth.tar'\n",
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"CONFIG_PATH = ROOT_PATH + '/config.json'\n",
"OUT_FOLDER = ROOT_PATH + '/test/'\n",
"CONFIG = load_config(CONFIG_PATH)\n",
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"use_cuda = True"
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]
},
{
"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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" | > Number of characters : 149\n"
]
},
{
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"ename": "TypeError",
"evalue": "super(type, obj): obj must be an instance or subtype of type",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-20-33e7f6a6cc7d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# load the model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTacotron\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mCONFIG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0membedding_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCONFIG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnum_freq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCONFIG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnum_mels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCONFIG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# load the audio processor\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/projects/TTS/models/tacotron.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, embedding_dim, linear_dim, mel_dim, r, padding_idx)\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\" | > Number of characters : {}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msymbols\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0membedding\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormal_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencoder\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mEncoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0membedding_dim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 20\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecoder\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDecoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m256\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmel_dim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpostnet\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCBHG\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmel_dim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mK\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprojections\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m256\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmel_dim\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/projects/TTS/layers/tacotron.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, in_features)\u001b[0m\n\u001b[1;32m 188\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0min_features\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 190\u001b[0;31m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mEncoder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 191\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprenet\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPrenet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0min_features\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout_features\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m256\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m128\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 192\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcbhg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCBHG\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m128\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mK\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprojections\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m128\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m128\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: super(type, obj): obj must be an instance or subtype of type"
]
}
],
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"source": [
"# load the model\n",
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"model = Tacotron(CONFIG.embedding_size, CONFIG.num_freq, CONFIG.num_mels, CONFIG.r)\n",
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"\n",
"# load the audio processor\n",
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"\n",
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"ap = AudioProcessor(CONFIG.sample_rate, CONFIG.num_mels, CONFIG.min_level_db,\n",
" CONFIG.frame_shift_ms, CONFIG.frame_length_ms, CONFIG.preemphasis,\n",
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" CONFIG.ref_level_db, CONFIG.num_freq, CONFIG.power, griffin_lim_iters=30) \n",
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"\n",
"\n",
"# load model state\n",
"if use_cuda:\n",
" cp = torch.load(MODEL_PATH)\n",
"else:\n",
" cp = torch.load(MODEL_PATH, map_location=lambda storage, loc: storage)\n",
"\n",
"# load the model\n",
"model.load_state_dict(cp['model'])\n",
"if use_cuda:\n",
" model.cuda()\n",
"model.eval()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### EXAMPLES FROM TRAINING SET"
]
},
{
"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"outputs": [],
"source": [
"import pandas as pd\n",
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"df = pd.read_csv('/data/shared/KeithIto/LJSpeech-1.0/metadata_val.csv', delimiter='|')"
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]
},
{
"cell_type": "code",
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"execution_count": 22,
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"metadata": {
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"scrolled": false
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"Hosty took the necessary steps to have the Dallas office of the FBI, rather than the New Orleans office, reestablished as the office with principal responsibility.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 6.3198254108428955\n"
]
},
{
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
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"source": [
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"sentence = df.iloc[175, 1]\n",
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"print(sentence)\n",
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"model.decoder.max_decoder_steps = 250\n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Comparision with https://mycroft.ai/blog/available-voices/"
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]
},
{
"cell_type": "code",
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"execution_count": 23,
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"metadata": {
"scrolled": false
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},
"outputs": [
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 4.629634857177734\n"
]
},
{
"data": {
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"\n",
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"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
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"source": [
"sentence = \"It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent.\"\n",
"model.decoder.max_decoder_steps = 250\n",
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"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap, figures=True)"
]
},
{
"cell_type": "code",
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"execution_count": 24,
"metadata": {},
"outputs": [
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 1.2954251766204834\n"
]
},
{
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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" </audio>\n",
" "
],
"text/plain": [
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]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
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"sentence = \"Be a voice,not an echo.\" # 'echo' is not in training set. \n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": 25,
"metadata": {},
"outputs": [
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 2.442563772201538\n"
]
},
{
"data": {
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"text/plain": [
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"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"The human voice is the most perfect instrument of all.\"\n",
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"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": 26,
"metadata": {},
"outputs": [
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 2.959503412246704\n"
]
},
{
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
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"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"I'm sorry Dave. I'm afraid I can't do that.\"\n",
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"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": 27,
"metadata": {},
"outputs": [
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{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 3.3856382369995117\n"
]
},
{
"data": {
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"data": {
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"image/png": "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
"text/plain": [
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"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"This cake is great. It's so delicious and moist.\"\n",
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"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Comparison with https://keithito.github.io/audio-samples/"
]
},
{
"cell_type": "code",
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"execution_count": 28,
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"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 3.539504289627075\n"
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]
},
{
"data": {
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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" <source src=\"data:audio/wav;base64,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" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"Generative adversarial network or variational auto-encoder.\"\n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": 29,
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"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 3.4460177421569824\n"
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]
},
{
"data": {
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"text/plain": [
"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"Scientists at the CERN laboratory say they have discovered a new particle.\"\n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": 30,
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"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 3.5448789596557617\n"
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]
},
{
"data": {
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"\n",
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},
{
"data": {
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"text/plain": [
"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"heres a way to measure the acute emotional intelligence that has never gone out of style.\"\n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": 31,
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"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/projects/TTS/notebooks/utils.py:19: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n",
" torch.from_numpy(seq), volatile=True).unsqueeze(0).cuda()\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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" > Run-time: 2.8492112159729004\n"
]
},
{
"data": {
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{
"data": {
2018-05-16 12:09:15 +00:00
"image/png": "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
"text/plain": [
"<Figure size 1152x1728 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
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"source": [
"sentence = \"President Trump met with other leaders at the Group of 20 conference.\"\n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
"sentence = \"The buses aren't the problem, they actually provide a solution.\"\n",
"align, spec, stop_tokens = tts(model, sentence, CONFIG, use_cuda, ap)"
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]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
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}
},
"nbformat": 4,
"nbformat_minor": 2
}