{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "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",
    "\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",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def tts(model, text, CONFIG, use_cuda, ap, figures=True):\n",
    "    t_1 = time.time()\n",
    "    waveform, alignment, spectrogram = create_speech(model, text, CONFIG, use_cuda, ap) \n",
    "    print(\" >  Run-time: {}\".format(time.time() - t_1))\n",
    "    if figures:                                                                                                         \n",
    "        visualize(alignment, spectrogram, CONFIG)                                                                       \n",
    "    IPython.display.display(Audio(waveform, rate=CONFIG.sample_rate))  \n",
    "    return alignment, spectrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set constants\n",
    "ROOT_PATH = '/data/shared/erogol_models/April-26-2018_05:55AM-aa32c76'\n",
    "MODEL_PATH = ROOT_PATH + '/checkpoint_188864.pth.tar'\n",
    "CONFIG_PATH = ROOT_PATH + '/config.json'\n",
    "OUT_FOLDER = ROOT_PATH + '/test/'\n",
    "CONFIG = load_config(CONFIG_PATH)\n",
    "use_cuda = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the model\n",
    "model = Tacotron(CONFIG.embedding_size, CONFIG.num_freq, CONFIG.num_mels, CONFIG.r)\n",
    "\n",
    "# load the audio processor\n",
    "ap = AudioProcessor(CONFIG.sample_rate, CONFIG.num_mels, CONFIG.min_level_db,\n",
    "                    CONFIG.frame_shift_ms, CONFIG.frame_length_ms, CONFIG.preemphasis,\n",
    "                    CONFIG.ref_level_db, CONFIG.num_freq, CONFIG.power, griffin_lim_iters=80)         \n",
    "\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",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('/data/shared/KeithIto/LJSpeech-1.0/metadata_val.csv', delimiter='|')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = df.iloc[175, 1]\n",
    "print(sentence)\n",
    "model.decoder.max_decoder_steps = 250\n",
    "align, spec = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparision with https://mycroft.ai/blog/available-voices/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "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",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"Be a voice, not an echo.\"  # 'echo' is not in training set. \n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"The human voice is the most perfect instrument of all.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"I'm sorry Dave. I'm afraid I can't do that.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"This cake is great. It's so delicious and moist.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparison with https://keithito.github.io/audio-samples/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"Generative adversarial network or variational auto-encoder.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"Scientists at the CERN laboratory say they have discovered a new particle.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"here’s a way to measure the acute emotional intelligence that has never gone out of style.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"President Trump met with other leaders at the Group of 20 conference.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = \"The buses aren't the problem, they actually provide a solution.\"\n",
    "alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
   ]
  }
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