{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wavelet Features For Speech Recognition.\n",
    "\n",
    "I've been partipating in the TensorFlow speech recognition challenge.  \n",
    "\n",
    "https://www.kaggle.com/c/tensorflow-speech-recognition-challenge\n",
    "\n",
    "It seems like the most common approach is to begin by turning the audio into a spectrogram and then feeding that into a 2D CNN. One trouble with spectrograms is that you have to trade off resolution in frequency for resolution in time and vice versa. In principle you can get higher resolution in time for higher frequencies than you can for lower frequencies but when you pick an input length for your short time fourier transform you lose temporal resolution much below the window length. \n",
    "\n",
    "Wavelets are one possible way around this limitation <!-- TEASER_END -->  and I thought it would be fun to see what sort of performance I could get out of a network which uses wavelet based features as inputs. A wavelet is a function which looks like a \"wiggle\" that is it starts out zero oscilates a couple times and becomes zero again. Technically that isn't quite enough to make a function qualify as a wavelet but for our purposes here it is good enough. If you are interested there is quite a bit of material on the web about wavelets.\n",
    "\n",
    "https://en.wikipedia.org/wiki/Wavelet\n",
    "\n",
    "In practice the way wavelets tend to be used is as a convenient set of low pass and high pass filters which can be iteratively applied to a signal followed by downsampling operations to generate a set of multi-scale representations of the original data. Using the handy pywavelets package we can fetch the filter coefficients for our favorite wavelet and use it as a convolution kernel in a series of convolution layers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import copy\n",
    "\n",
    "import numpy as np\n",
    "import scipy\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "\n",
    "import keras\n",
    "import keras.backend as K\n",
    "import tensorflow as tf\n",
    "\n",
    "import IPython.display as ipd\n",
    "\n",
    "from keras.layers import Conv1D, Conv2D, MaxPooling1D, MaxPooling2D, LeakyReLU, concatenate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Frequency')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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69GrueHI3u1t6nB6OJTgIv/2QtbXNuk85PRo1DTT4Us5LVPNlZ75WVRcDWnSvlJo+/3Z1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\nfxlKTTt412oIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f07e8555d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pywt\n",
    "\n",
    "low_pass, high_pass  = pywt.Wavelet(\"sym20\").filter_bank[:2]\n",
    "low_pass = np.array(low_pass)\n",
    "high_pass = np.array(high_pass)\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(10, 5))\n",
    "axes[0].plot(low_pass)\n",
    "axes[0].plot(high_pass)\n",
    "\n",
    "axes[1].plot(np.abs(np.fft.rfft(low_pass)))\n",
    "axes[1].plot(np.abs(np.fft.rfft(high_pass)))\n",
    "axes[0].set_title(\"Filter Coefficients\")\n",
    "axes[1].set_title(\"FFT magnitudes\")\n",
    "axes[0].set_xlabel(\"Time\")\n",
    "axes[1].set_xlabel(\"Frequency\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since convolution is multiplication in the fourier domain applying the low pass filter keeps the lower half of the frequencies and the high pass filter keeps the upper half. Because we are using what is called a \"perfect reconstruction wavelet\" the filters are also designed such that we don't lose any information by downsampling by 2 after convolution. \n",
    "\n",
    "Lets translate that formula into something suitable for use in tensorflow. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def make_wavelet_expansion(\n",
    "    input_tensor, \n",
    "    n_levels,\n",
    "    low_pass_filter,\n",
    "    high_pass_filter,\n",
    "    trainable=False,\n",
    "):\n",
    "    wv_kwargs = {\n",
    "        \"filters\":1,\n",
    "        \"kernel_size\":len(low_pass),\n",
    "        \"strides\":2,     \n",
    "        \"use_bias\":False, \n",
    "        \"padding\":\"same\", \n",
    "        \"trainable\":trainable,\n",
    "    }\n",
    "    \n",
    "    approximation_coefficients = []\n",
    "    detail_coefficients = []\n",
    "    \n",
    "    last_approximant = input_tensor\n",
    "    for i in range(n_levels):\n",
    "        lpf = low_pass_filter\n",
    "        hpf = high_pass_filter\n",
    "        a_n = Conv1D(\n",
    "            kernel_initializer=keras.initializers.Constant(lpf.reshape((-1, 1))),\n",
    "            name=\"low_pass_{}\".format(i),\n",
    "            **wv_kwargs\n",
    "        )(last_approximant)\n",
    "        d_n = Conv1D(\n",
    "            kernel_initializer=keras.initializers.Constant(hpf.reshape((-1, 1))),\n",
    "            name=\"high_pass_{}\".format(i),\n",
    "            **wv_kwargs,\n",
    "        )(last_approximant)\n",
    "        \n",
    "        detail_coefficients.append(d_n)\n",
    "        approximation_coefficients.append(a_n)\n",
    "        last_approximant = a_n\n",
    "    \n",
    "    return approximation_coefficients, detail_coefficients\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function takes an input tensor with just one channel and passes it through the high pass and low pass filters. The result of applying the low pass filter just smooths the data a little and so the result is called the \"approximation coefficients\". The high pass filter effectively gives the residuals of the original data minus the smoothed data and so these are the \"detail coefficients\". Both of these vectors would carry redundant information if we kept every pixel of the convolution and so by the design of the wavelet filters we can keep only every other point or equivalently use a convolution which is strided by 2.\n",
    "\n",
    "The frequencies in the detail coefficients are high enough that 2 pixels is just about enough to localize an oscilation of that frequency in time while also still giving us a good idea as to the magnitude of that oscillation. The approximation coefficients are a different story. For the frequencies close to the low pass cut off we could almost estimate the magnitude of an oscillation from just one or two coefficients but for lower frequencies we would need more and more. A good way to handle this is to simply repeat the previous application of low and high pass filters again. The detail coefficients again contain only information which is close to the right frequency so that individual pixels (after the downsampling/striding) still carry significant magnitude information while also being about as localized in time as is possible for that frequency. By continuing this process some number of steps we get a typical wavelet expansion.\n",
    "\n",
    "Because wavelets (like ffts) like to operate on vectors which are powers of 2 so that everything works out nicely we will zero pad our audio inputs to be 16,384 points long and do an 8 level wavelet expansion. Since we are doing this all inside of TensorFlow we might as well make the wavelet filters trainable while we are at it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_length = 16000\n",
    "target_length = 16384\n",
    "\n",
    "sound_in = keras.layers.Input(shape=(target_length, 1), name=\"audio\")\n",
    "\n",
    "wavelets_trainable = True\n",
    "\n",
    "approx_stack, detail_stack = make_wavelet_expansion(\n",
    "    sound_in, \n",
    "    n_levels = 9, \n",
    "    low_pass_filter=low_pass, \n",
    "    high_pass_filter=high_pass,\n",
    "    trainable=wavelets_trainable,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The detail coefficients at every level represent independent information from each other but the approximation coefficients are just successively smoothed versions of the input signal. The very last approximation tensor in our stack represents information that hasn't been captured by any of the detail coefficients however and so should be included in our feature set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<tf.Tensor 'high_pass_0/convolution/Squeeze:0' shape=(?, 8192, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_1/convolution/Squeeze:0' shape=(?, 4096, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_2/convolution/Squeeze:0' shape=(?, 2048, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_3/convolution/Squeeze:0' shape=(?, 1024, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_4/convolution/Squeeze:0' shape=(?, 512, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_5/convolution/Squeeze:0' shape=(?, 256, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_6/convolution/Squeeze:0' shape=(?, 128, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_7/convolution/Squeeze:0' shape=(?, 64, 1) dtype=float32>,\n",
       " <tf.Tensor 'high_pass_8/convolution/Squeeze:0' shape=(?, 32, 1) dtype=float32>,\n",
       " <tf.Tensor 'low_pass_8/convolution/Squeeze:0' shape=(?, 32, 1) dtype=float32>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_list = []\n",
    "features_list.extend(detail_stack)\n",
    "features_list.append(approx_stack[-1])\n",
    "\n",
    "features_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unlike the convenience of the STFT however these wavelet features are all different lengths. It would be nice to have a rectangular image representation just like what we get out of a short time fourier transform. We can resize each of these wavelet features to some standard length by either upsampling or averaging. Picking the lowest frequency features and averaging all the others down to that scale would lose us too much temporal information. Meanwhile upsampling all these features back up to the maximum length one would be an awful lot of unnecessary redundancy and probably an unnecessary amount of temporal resolution too. \n",
    "\n",
    "We pick a mid ground somewhere inbetween and upsample the shorter vectors and average the longer vectors so that the all match and then concatenate the vectors together. If we square the magnitudes before we do the averaging then we effectively get a wavelet \"spectrogram\". "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "target_size = 256\n",
    "min_pool_size = 3\n",
    "\n",
    "def press_tensor(\n",
    "    input_tensor, \n",
    "    target_length, \n",
    "    min_pool_size,\n",
    "    pooling_type=\"average\",\n",
    "):\n",
    "    \"\"\"Resize a tensor to a desired shape by upsampling or averaging (or some combination)\"\"\"\n",
    "    cur_size = int(input_tensor.shape[1])\n",
    "    if cur_size < target_length:\n",
    "        input_tensor = keras.layers.UpSampling1D(target_length//cur_size)(input_tensor)\n",
    "    size_ratio = max(1, cur_size//target_length)\n",
    "    pool_size = max(min_pool_size, size_ratio)\n",
    "    if not (pool_size == 1 and size_ratio == 1):\n",
    "        return keras.layers.AveragePooling1D(pool_size=pool_size, strides=size_ratio, padding=\"same\")(input_tensor)\n",
    "    else:\n",
    "        return input_tensor\n",
    "\n",
    "resized_features = []\n",
    "\n",
    "for wv_in in features_list:\n",
    "    x = keras.layers.BatchNormalization()(wv_in)#normalize each filter before taking the power\n",
    "    x = keras.layers.Lambda(lambda x: tf.square(x))(x)#square the coefficients to get a power estimate\n",
    "    resized_features.append(press_tensor(x, target_size, min_pool_size))\n",
    "\n",
    "#concatenate the features together to get our spectrogram\n",
    "specgram = keras.layers.concatenate(resized_features)\n",
    "log_specgram = keras.layers.Lambda(lambda x: tf.log(1.0+x))(specgram)\n",
    "\n",
    "specgram_model = keras.models.Model(sound_in, log_specgram)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now to load in some helpers from a python helper module I wrote for the competition (It will likely show up on github after the competition is over)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tim/anaconda3/lib/python3.6/site-packages/scipy/io/wavfile.py:273: WavFileWarning: Chunk (non-data) not understood, skipping it.\n",
      "  WavFileWarning)\n"
     ]
    }
   ],
   "source": [
    "import tf_speech_recognition as tsr\n",
    "\n",
    "command_words = [\"yes\", \"no\", \"up\", \"down\", \"left\", \"right\", \"on\", \"off\", \"stop\", \"go\"]\n",
    "\n",
    "command_encoder = tsr.preprocessing.LimitedVocabularyEncoder(\n",
    "    vocabulary=command_words,\n",
    "    encoding_type=\"onehot\",\n",
    ")\n",
    "\n",
    "target_labels = copy.copy(command_words)\n",
    "target_labels = target_labels + [\"silence\", \"unknown\"]\n",
    "\n",
    "random_labeler = tsr.preprocessing.RandomLabeler(field=\"word\", labels=target_labels)\n",
    "\n",
    "preprocessor = tsr.SoundPreprocessor(\n",
    "    input_transforms={\"audio\":lambda x, y: x.reshape((-1, 1))},\n",
    "    output_transforms={\n",
    "        \"command_probs\":lambda x, y: command_encoder.encode(x[\"word\"]),\n",
    "    },\n",
    "    input_length=input_length,\n",
    "    target_length=target_length,\n",
    "    downsampling_rate=1,\n",
    "    t_shift_max=200,\n",
    "    silence_fraction=0.1,\n",
    "    additive_bg_fraction=0.4,\n",
    "    bg_mag_range=(0.01, 0.25),\n",
    "    relabel_fraction=0.0,\n",
    "    bg_noise_samples=tsr.get_background_noise_samples(),\n",
    "    mean_subtract=True,\n",
    "    norm_type=\"rms\",\n",
    "    norm_damp=1e-4,\n",
    ")\n",
    "\n",
    "load_batch = tsr.data_loading.simple_sound_batch_loader\n",
    "\n",
    "train_labels = tsr.get_labels_df(\"train\")\n",
    "\n",
    "train_loading_kwargs = dict(\n",
    "    labels_df=train_labels,\n",
    "    preprocessor=preprocessor,\n",
    "    augment=True,\n",
    "    data_directory=os.path.join(tsr.data_dir, \"raw\", \"train\", \"audio\"),\n",
    "    forcing_kwargs={},\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example Wavelet 'Spectrograms'\n",
    "\n",
    "The resulting \"spectrograms\" look quite different from the regulr STFT spectrograms. This is mostly due to the very coarse frequency information. Since we are simply averaging the square magnitude for every wavelet feature we are lumping together all frequencies within a factor of 2 of each other into the same band. I have experimented with breaking these out into sub-bands either by applying a \"tree\" of wavelet filters by putting the longer detail coefficient vectors through their own wavelet expansion before concatenating them together but the simple 10 frequency band features from doing just one expansion works surprisingly well. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
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0G8+r6/bhSw+H73v6iHJ89tgReGPDATy3ai9mVpXjw+11OH7MAPzk/KMx7643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\n0oKy0ZMkSVpQXwM+BN0IU4WFSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f077451eeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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yzmWoxpTq3p8qHA9pwgh2Ky68l+frCyEDwfdZprE6rtsbvgH3v3cm5m8NZ287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\nHEVERESkJf8bN72meuvT6HsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0781da3c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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+6VCvm9mHJF0l6RL3wmMO3X2BpAWS1NHRwdhE1LRkIj4XOQBg9MRt1G1ZVQ5m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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0781ddad30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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JRrLc5u5zzOzrZnZ2mOwXwM5mNh/4HJA1NY0MDLd94mjGDGurdzEkw7F7j+n1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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0774143f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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zPqYO6oQ2mSkY17stTlS6caysCk/P3YwBnVvh8lHd8OScTWiVloQ+HbLgUdgG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\nAADAgGNCCAAAMOD+H7ufY8yx3wUGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f076fe77ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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Tn/wOF/33J3y+5hDOf/ZHzFkf/HAtX206go9XHQh6eyKKfJFWomfqgMlEFL3CHYw6lyq6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\nAADQo5joAQAA9Kj/BzIpEamatUaJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f076fe2c278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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EUaWe53vRIYOD/1982yQe+e7Bnm8jWZG/UJ//8WEJrTdmUI9my2bfdGJYc07A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\nAC31f/m96gNKzdapAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0774238048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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PonjxDQbPH94tLvn+9IwT4pJPIF/9eort8Q9uGW97HDDeT09cdgq2PzA97HL+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\nMTppjUJ8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f077452b668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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+w5UjszC5Tztc9MoKW9D15J8GoKLGjH/8dz0em9Efd+iB2rwbR+LlJTuwZvdR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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0774335cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "word= off\n"
     ]
    },
    {
     "data": {
      "image/png": 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PgdS+jO6RjaW7i3BKz7b42c/kgpF5bXDlmO44b2gnbD92wvF3+eq2cbj45Z99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\nGcVEDwAAYEYx0QMAAJhR/w8AWRzB3TxsCQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f076fd60e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "example_batch = load_batch(train_labels.index[:10], **train_loading_kwargs)\n",
    "\n",
    "spec_out = specgram_model.predict(example_batch[0])\n",
    "\n",
    "for b_i in range(len(example_batch[0][\"audio\"])):\n",
    "    print(\"word=\", command_encoder.decode(example_batch[1][\"command_probs\"][b_i]))\n",
    "    fig, axes = plt.subplots(2, 1, figsize=(12, 6))\n",
    "    axes[0].plot(example_batch[0][\"audio\"][b_i, ::10, :])\n",
    "    im = axes[1].imshow(spec_out[b_i].transpose(), aspect=\"auto\")\n",
    "    plt.colorbar(im, ax=list(axes))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wavelet Spectrogram Based Model\n",
    "\n",
    "Now to make a network architecture to turn these wavelet features into command predictions. Just 10 frequency channels seems a waste of a 2D CNN and so I will settle for a 1D CNN with 10 input channels. I use length 9 filters and doubling the number of filters with each layer and halving the temporal resolution until I hit a total timewise dimension of just 16 at which point a single length 9 convolution covers over half of the full input and should be sufficient to classify a word. Then I take the global max pool and feed that into a dense layer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def make_conv(\n",
    "        x,\n",
    "        n_filters,\n",
    "        kernel_size,\n",
    "        conv_strides,\n",
    "        leak,\n",
    "        pool_size,\n",
    "        pool_strides,\n",
    "        conv_kwargs=None,\n",
    "):\n",
    "    n_dim = len(x.shape)-1\n",
    "    if n_dim == 2:\n",
    "        conv = Conv1D\n",
    "        pool = MaxPooling1D\n",
    "    elif n_dim == 3:\n",
    "        conv = Conv2D\n",
    "        pool = MaxPooling2D\n",
    "    else:\n",
    "        raise ValueError()\n",
    "    \n",
    "    if conv_kwargs is None:\n",
    "        conv_kwargs={}\n",
    "    x = conv(\n",
    "        n_filters, \n",
    "        kernel_size=kernel_size,\n",
    "        strides=conv_strides,\n",
    "        padding=\"same\",\n",
    "        activation=None,\n",
    "        **conv_kwargs\n",
    "    )(x)\n",
    "    if not pool_size is None:\n",
    "        x = pool(\n",
    "            pool_size=pool_size,\n",
    "            strides=pool_strides,\n",
    "            padding=\"same\",\n",
    "        )(x)\n",
    "    else:\n",
    "        assert pool_strides is None\n",
    "    x = LeakyReLU(alpha=leak)(x)\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#power conv stack\n",
    "x = specgram\n",
    "x = make_conv(x, 16,  9,  1, 0.2, 2, 2)\n",
    "x = make_conv(x, 32, 9, 1, 0.2, 2, 2)\n",
    "x = make_conv(x, 64, 9, 1, 0.2, 2, 2)\n",
    "x = make_conv(x, 128, 9, 1, 0.2, 2, 2)\n",
    "x = make_conv(x, 256, 9, 1, 0.2, 2, 2)\n",
    "x = keras.layers.GlobalMaxPooling1D()(x)\n",
    "x = keras.layers.BatchNormalization()(x)\n",
    "x = keras.layers.Dense(100)(x)\n",
    "x = LeakyReLU(alpha=0.2)(x)\n",
    "\n",
    "command_probs = keras.layers.Dense(12, activation=\"softmax\", name=\"command_probs\")(x)\n",
    "\n",
    "model = keras.models.Model(sound_in, command_probs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def damped_log_loss(y_true, y_pred):\n",
    "    damp_param = 0.0001\n",
    "    clipped = (y_pred+damp_param)/(1.0+2.0*damp_param)\n",
    "    costs = -1.0*(y_true*K.log(clipped) + (1.0-y_true)*K.log(1.0-clipped))\n",
    "    return K.mean(costs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "optimizer = keras.optimizers.Adam()\n",
    "model.compile(loss=damped_log_loss, optimizer=optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dev_labels = tsr.get_labels_df(\"dev\")\n",
    "\n",
    "dev_loading_kwargs = dict(\n",
    "    labels_df=dev_labels,\n",
    "    preprocessor=preprocessor,\n",
    "    augment=False,\n",
    "    data_directory=os.path.join(tsr.data_dir, \"raw\", \"train\", \"audio\"),\n",
    "    forcing_kwargs={},\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sklearn.metrics\n",
    "import itertools\n",
    "from tf_speech_recognition.visualization import plot_confusion_matrix\n",
    "\n",
    "def evaluate_command_model_quality(\n",
    "    command_model,\n",
    "    show_plot=True,\n",
    "):\n",
    "    dev_true = []\n",
    "    dev_pred = []\n",
    "    \n",
    "    for i in range(len(dev_labels)//batch_size):\n",
    "        xi, yi, aug_dict = load_batch(\n",
    "            dev_labels.index[i*batch_size:(i+1)*batch_size], \n",
    "            **dev_loading_kwargs,\n",
    "        )\n",
    "        pred_res = command_model.predict(xi)\n",
    "        pred_yi = pred_res#np.hstack([pred_res[1][:, :11], np.sum(pred_res[1][:, 11:], axis=1, keepdims=True)]) \n",
    "        dev_true.append(np.argmax(yi[\"command_probs\"], axis=1))\n",
    "        dev_pred.append(np.argmax(pred_yi, axis=1))\n",
    "    \n",
    "    dev_true = np.hstack(dev_true)\n",
    "    dev_pred = np.hstack(dev_pred)\n",
    "    \n",
    "    mean_acc = np.mean(dev_true==dev_pred)\n",
    "    print(\"mean accuracy\", mean_acc)\n",
    "    if show_plot:\n",
    "        conf_mat = sklearn.metrics.confusion_matrix(dev_true, dev_pred, labels=np.arange(12))\n",
    "        fig, ax = plt.subplots(figsize=(12, 6))\n",
    "        plot_confusion_matrix(\n",
    "            conf_mat, \n",
    "            classes=target_labels,\n",
    "            normalize=True,\n",
    "            title='Confusion matrix',\n",
    "            cmap=plt.cm.Blues,\n",
    "            ax=ax,\n",
    "        )\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "beginning training\n",
      "\n",
      " epoch 1\n",
      "0.33644 0.17501 0.12962 0.10146 \n",
      "\n",
      "0.71 minutes per epoch\n",
      "mean accuracy 0.758263221154\n",
      "\n",
      " epoch 2\n",
      "0.08425 0.07176 0.06800 0.06435 \n",
      "\n",
      "0.67 minutes per epoch\n",
      "mean accuracy 0.829326923077\n",
      "\n",
      " epoch 3\n",
      "0.05954 0.05407 0.05088 0.04952 \n",
      "\n",
      "0.67 minutes per epoch\n",
      "mean accuracy 0.860276442308\n",
      "\n",
      " epoch 4\n",
      "0.04700 0.04443 0.04369 0.04322 \n",
      "\n",
      "0.67 minutes per epoch\n",
      "mean accuracy 0.869441105769\n",
      "\n",
      " epoch 5\n",
      "0.04233 0.03937 0.03794 0.03863 \n",
      "\n",
      "0.67 minutes per epoch\n",
      "mean accuracy 0.883563701923\n",
      "Normalized confusion matrix\n"
     ]
    },
    {
     "data": {
      "image/png": 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c/de6pCMlJYW//1yIZzX7fKHygVHKkDOx+eHqBFWB/2itn1VKTQM6AG8BA7TW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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d713a4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " epoch 6\n",
      "0.03464 0.03344 0.03423 0.03423 \n",
      "\n",
      "0.65 minutes per epoch\n",
      "mean accuracy 0.897385817308\n",
      "\n",
      " epoch 7\n",
      "0.03338 0.03145 0.03045 0.03123 \n",
      "\n",
      "0.65 minutes per epoch\n",
      "mean accuracy 0.889423076923\n",
      "\n",
      " epoch 8\n",
      "0.03181 0.02864 0.02826 0.02888 \n",
      "\n",
      "0.65 minutes per epoch\n",
      "mean accuracy 0.90625\n",
      "\n",
      " epoch 9\n",
      "0.02700 0.02764 0.02694 0.02615 \n",
      "\n",
      "0.65 minutes per epoch\n",
      "mean accuracy 0.90234375\n",
      "\n",
      " epoch 10\n",
      "0.02804 0.02334 0.02541 0.02550 \n",
      "\n",
      "0.65 minutes per epoch\n",
      "mean accuracy 0.913010817308\n",
      "Normalized confusion matrix\n"
     ]
    },
    {
     "data": {
      "image/png": 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p57t9rtCwMBISDpF49CgZGRksjJpPp/AuNjWdwrswd/YsAL5fvIjWbduhlKJT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\nBTHmYYnrO70Ed5byeqCHukGM9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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f076fcaef60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_losses = []\n",
    "model_quality_results = []\n",
    "\n",
    "def do_training_iteration(): \n",
    "    train_hashes = train_batcher.make_batch(batch_size)\n",
    "    xi, yi, aug_dict = load_batch(\n",
    "        train_hashes, \n",
    "        **train_loading_kwargs,\n",
    "    )\n",
    "    ctime = time.time()\n",
    "    yres = model.train_on_batch(xi, yi)\n",
    "    train_losses.append(yres)\n",
    "\n",
    "batch_size = 256\n",
    "batches_per_epoch = len(train_labels)//batch_size + 1\n",
    "\n",
    "train_batcher = tsr.data_loading.BalancedBatcher([train_labels.index,])\n",
    "\n",
    "print(\"beginning training\")\n",
    "plot_frequency = 5\n",
    "\n",
    "for epoch_idx in range(10):\n",
    "    stime = time.time()\n",
    "        \n",
    "    print(\"\\n epoch\", epoch_idx+1)\n",
    "    for iter_idx in range(batches_per_epoch):\n",
    "        do_training_iteration()\n",
    "        if (iter_idx % 50) == 0:\n",
    "            print(\"{:4.5f} \".format(np.mean(train_losses[-50:])), end=\"\")\n",
    "    print(\"\\n\")\n",
    "    etime = time.time()\n",
    "    print(\"{:4.2f} minutes per epoch\".format((etime-stime)/60.0))\n",
    "    show_plot = (epoch_idx % plot_frequency) == plot_frequency-1\n",
    "    mq_res = evaluate_command_model_quality(\n",
    "        command_model=model, \n",
    "        show_plot=show_plot\n",
    "    )\n",
    "    model_quality_results.append(mq_res)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While the accuracy of the resulting model is nothing spectacular it certainly demonstrates that the wavelet based features have significant power in terms of recognizing the desired target words. This is particularly impressive considering the extremely coarse frequency resolution of the input bands. I have experimented with breaking the wavelet features up into sub-bands in various ways and I do indeed get some performance improvements but not as much as I might have naively expected."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Custom Wavelet Filters\n",
    "\n",
    "Since we let the wavelet filters float as trainable parameters we should take a moment to see what the wavelet filters ultimately ended up looking like after a few training epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2CydaIZ9+UT+tHR7uW76becfmcXxxTsR9TSrIZGdVI21u44jEK8b4JzLdZJ/Sw80APTw3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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f07108716a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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gvhwu+r7OEAI46Rq9RmDfygGdpjH+iYzXTZuybsk9RvZJZESEv990Kj/9xEnd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\n6ibj+fcWY/wHA3syZFnF1Lox/gApGZYH32EZf68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bfw/n3eouUBkgnNp5x4EW6hpbuemB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\n8hBz/oZhGHnI/wLn74oaZSgolQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f07108d96a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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S9972Cl7bVM7LGw71eR/+tA6TR/TN5eNnZmEGLoft6Pr93/xv2PQvOOtumL1YLxOBrGKY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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d6774940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2T7UVf4ulXTa8ZMoszLkcps7v6950HZGEhR+s+LubiFTPuqYgTUFTNcB6/hZLOwSbTOG0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\nR7T4R3v+kameNvJPFnOAElXdpKqNwCO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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d6638dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1rgDuAlDVp4AyoCEv1k1Geg9CuDdF2Mf1/C3unxNyIf6Z3BrHcwXwx2Q77NY4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\n7r8o3fYnbnriOD5+xmLaDvW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SzwV2JzYSkXOB64CLVLU/T7Z5A1VH/A87E0rK89r1ucsa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\nZDoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d6502e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1rgDuAlDVp4AyoCEv1k1Geg9CuDdF2Mf1/C3unxNyIf6Z3BrHcwXwx2Q77NY4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\n7r8o3fYnbnriOD5+xmLaDvW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SzwV2JzYSkXOB64CLVLU/T7Z5A1VH/A87E0rK89r1ucsa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\nZDoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d6441f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1rgDuAlDVp4AyoCEv1k1Geg9CuDdF2Mf1/C3unxNyIf6Z3BrHcwXwx2Q77NY4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\n7r8o3fYnbnriOD5+xmLaDvW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SzwV2JzYSkXOB64CLVLU/T7Z5A1VH/A87E0rK89r1ucsa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\nZDoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d6380f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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1rgDuAlDVp4AyoCEv1k1Geg9CuDdF2Mf1/C3unxNyIf6Z3BrHcwXwx2Q77NY4\nczQ8QERc0c8g1dM8/3GxBmgWkUUiEsQZ0F2V0GYHcA6AiCzDEX87ecdLrJRzEs+/saYMEay6Z47I\nhfhncmvsNBS5HFgJfCvZfrs1zpxIJIxKouc/UvzLSpyv2GL+Y0dVw8A1wAPABpysnnUicoOIXOQ2\n+xxwpYi8BNwBfEQ1SZElIzPiVvBKpMTvo7Ha0j1zRSAHx8jk1hgRORe4DjhDVftz0O+URiMhoome\nf5Kwj4i46/hahsR4UNXVOAO58duuj3u9Hjgt33ZNWgYneCWPDDfV2YpeuSIXnv+ot8YichzwP8BF\nqtqagz6nPBoJD4l/mlRPsNW8DA/RsRP8QahMfuc/u7acPTbgmxOyFv8Mb42/BVQBd4vIiyKSGDc1\nxkokhPoSPf/Ui7jbgK/hCTp2OTN7fcmlqam2jF3tvVhkLXtyEfbJ5Nb43Fz0Ywyh0fBQrD9NqifY\nal6Gh+jclTLkA066Z384ysGeENMrg3k0bPJhM3yLkUe+Bre+I20TiYZGin+K1bzKSyzsY3iEFBO8\nYsQmetmgb/aY+BcjWx+FlrVJV+YC6A9H8GtkaBEXf/qYv4V9DE8QjUDn7qSZPjGa3Lr+Vt0ze0z8\ni41oFFo3OBNd+tqTNunpj+Angozw/JMLfEUwQE/Isn2MIqdrL2gk6QSvGLFZvub5Z4+Jf7HRvh1C\n3c7rzj1Jm3T1hymRiJMVAWlTPcE8f8MjDC7iMi9lk/rKIEG/j92W7pk1Jv7Fxt71Q68PJRf/7oEw\nfiL4YqI/Sqqnk+dv4m8UOUlW8ErE5xNm1ZZZumcOMPEvNlozEP/+MCVE8AUyS/WsCPrpsWwfo9hJ\nsYJXIraoS24w8S829q6DancFoxTi39UfIUAEXyDm+adP9Sy3SV6GF+hogWA1lNWmbTbblnPMCSb+\nxcbedTDneCifnjLm393vhH38/gTxT5PqORCOEonaxBijiOlocUI+kqxc2BBNdWW80dln53OWmPgX\nE6FeOLAVZi6H6iY49EbSZl1u2McfSBjwTTPJC6y4m1HkdO4aNeQDTsZPJKq0HjLvPxtM/IuJtldB\no9C4HGqa4FDyFQEHPf8SV/xjA74pUj3LB8s6W7qnUcSMMsErxuzaWLqniX82mPgXE7HB3plHOgtY\np/D8u91Uz8BgzN8H4ksZ9qkosQVdjCIn3A/dbRmJf5Mt55gTTPyLib3rIFAG0w9zBn279iZdoCU2\n4OuPiT843n+aAV/IPOyzbncHz71+YOz2G8Z4yTDTB2yiV64w8S8m9q6DGYc7ZRuqZzkhoO6RFbAd\nzz86NNALTtw/TVVPyGw1r2gsn4j1AAAgAElEQVRU+eQvnuczd744vr/BMMbDYI7/6J5/TVkJVaUB\nC/tkiYl/MdG63gn5gFPWFpKme3YPOAO+gwO94PwQpBrwLfGzVHay+HeXQPe+tCY8uWUf2/f30HKw\nl72ddnEZeWJwBa/MlvduqrVFXbLFxL9Y6N7vhHkalzvvq2c5z0nSPWMDvoMDveCIf6qYfzDA23xr\nqW1bC8/dmtaM25/aTonfSbVbu/3gWP8Kwxgfna7nH3N6RqGprtw8/ywx8S8WWtc5zzNj4p/G83dj\n/vj8Qxv96WL+Po7xbXPePHdryqygnQd6eHhjKx998yLKSnw897qJv5EnOlqgogFKyjNqPseWc8wa\nE/9iIVbTp/Eo57myAcSfVPy7Yp6/P2HAN02q51G+1+gtrXeWydv8YNJ2v3x2BwJ86JSFrJhbZ4O+\ngIicLyKvisgWEfliijbvE5H1IrJORH6ZbxsnBR270tb0SaSptpx9XQP02dyVcWPiXyzsfQUq6qFq\npvPe50+Z7tndF3I9//gB39Rhn8r+fcyWA7wy/3KomgVrfjqiTV8owq/W7OTcZY3MqSvnhAXTWLe7\nc0qnh4qIH7gRuABYDlwmIssT2jQD/wycpqpHAtfm3dDJwCgreCXSVOuke75hZR7GjYl/sdC63gn5\nxE9tr25yFrdIoK+/33nhyyzVs2L/KwDsrDgKTvgwbPkTHHhtWJs/vrKHA90DfOiUhQCsXDiNcFR5\nqSX5mgJThJOALaq6TVUHgDuBixPaXAncqKoHAVR1ZHqWMToZTvCKMSeW7mmhn3Fj4l8MRKPQuhEa\njxy+PYXn3zcw4LzwZ5bqWdL6ElEVWsqWwPEfdiaEPfe/w9r87KnXOayhklMX1wNw/PxpAFM97j8H\n2Bn3vsXdFs9SYKmI/EVEnhaR85MdSESuEpG1IrK2ra1tgsz1KH2d0N85trCPK/5W2nn8mPhPFKrw\n4L/CMzeN3ja2gMvM5cO318weUeJBVRkYiHn+ceKfJtVTdr/Ia8ymI1LmXGCHXwAv/NyZVQls2nuI\nF3a0c/nJC/D5nDuPuoogS2ZWsXb7lI77J6swllhNLAA0A2cClwE3i0jdiA+p3qSqK1V15YwZM3Ju\nqKcZwwSvGLGwjw36jh8T/4nilV/DX/8LHrxuaAJLKhIGe3sGwuzv6nc8/74OGOgZbNofjg4N7GaY\n6snuF3jVt3hokteJV0DPflh/H+CIP8AprtcfY+WCaTy/o53o1K2e2ALELys1F0iMw7UA96lqSFVf\nA17F+TEwMiWDFbwSKSvxU18ZZJd5/uPGxH8i6N4Hf/ynoQlbj38zfftYTZ8Zh/O3lg7e+t0nuOTH\nTyVN94xV9AQyS/Xs3ANdb7Al0ExvrLDbojNh+mJ48jsQ7h8cNIsVzIpxwoJpdPSG2NrWlclfPRlZ\nAzSLyCIRCQKXAqsS2vwWOAtARBpwwkDb8mql18lgBa9kNFm6Z1bkRPxHS4cTkVIR+ZW7/xkRWZiL\nfouW1Z9H+w9xQ+lneXb6RegLP4f9W1O337sOpi3knlfaee+P/8obnX28tq+bg/7pzv448e/uDxPA\nFfHEGb7JUj33OGUatgebh2r7+Hxw/tehbSM8+V12t/dRXuKnpjww7KMnLHDi/mtjcf/eg/CHz8Ev\nL4WukXFrVUV18twlqGoYuAZ4ANgA3KWq60TkBhG5yG32ALBfRNYDjwKfV9X9hbHYo3S0OGnNVbPG\n9LHZteXsOmjiP16yFv9M0uGAK4CDqroE+B7wjWz7LVo2/A7W3cuN0fdw+7YKPrnzbEIEiDz69ZQf\n0db1bIjO4x/vfomVC6bx48tPAGB9V5XTIG7Qt7s/QkCizpv4sI+/JHnYZ/cLID52lzcPr+2z9Dw4\n+n3w5Lfxta2jqa4MSVhEY1FDJfWVQda+dgD+dg/88ERYewtsfQRuPnswXBWORLnvxV1c+IM/c/SX\nH+RHj22lPzw5UkRVdbWqLlXVxar67+6261V1lftaVfWzqrpcVY9W1TsLa7EHOfga1M0fnsCQAQvq\nK9h5sGcqhyWzYmz/7eQMpsMBiEgsHS5uMVouBr7svr4H+KGIiI7DTew+1M6h9vT1aYahimoUjZ0g\nIogI4vPhDwTxl5QRKCunpKSccKiPUF834f4e+tr30v/GRqJtm/F3bCdSXg+NR1M+/1hmLDya8vKy\nEV3t37uTkl9/hp3RBTxYfyl/vGwlj2/ax0/vfxsff+Ueek7+DBVzjx7+oVAfun8rD4WW89HTFvEv\nFx5BOKr4fcLaA6WcBsPSPbsH4jz/YQO+KcI+u1+EhsPxBatG5uyf/x+w9RHev/sbbGr8wYiPiggn\nzyvnfZv+ATY8D7OPgw/cAxqBO/4Ofvo2nljxDa5b18TOA70snlHJCQum8Y37N/KrNTu44ewG3jKj\nG+k5AD37nLGLqhlQNYv2wHTaI2X0RXwMqJ8wQqlEKfdFKPNFCIgCiqAIziirAqqCijA0Fpv+FKqs\nmU517fS0bYwCc2CbU8l2jCyor6QvFKX1UD+zakdej0Z6ciH+ydLh3pSqjaqGRaQDqAfGoOIO6x+6\njRNfvn6cpo6dqAp7mE49nZRtC8FT0KGV3Fd9CV3HXckpy+bzWlsXu5/8GZe0/ZBS+nnmmO9yz7vO\nIBjwsWRmNav8X6T7/j/xys/+iSM/u4qasiGPvW/PBso0Qv+0I/i3dyxDRAj44YhZ1azdE4aSymGe\nvzO71/X8R0v1VHU8/yXnUNHpp70n4cehsh4u/CbN93yU/xNeBZw64u+/MvIrjo08T9dZX6PqLZ8Y\nGme48hEO3XoJpz37Sb4fPJ7qlaez5IRz8VVU8lrdH+l/ZRVH/G5Lyv9rnfuYaJ467NOc8qGv5qEn\nY1yowv5tcMzKMX90YX0lANv3d5v4j4NciH8m6XCZtEFErgKuApg/f37SzmYdfSbP6lfSmKMjuxOf\nO3nK8SFFo05sOhpy0h3DfUi4HwJBtKQCAuVQXkdw5uFUzm5mWm0te3v7aN+5gdCul6jd+jsubb+N\ntid+w02PvIPTfOu4yv8Su6qP4tDb/5OPLht+Il90ylFsafkYp6z7L778i/v40kffOxhiefIvj/NW\n4PxzzhkWdlkxr47fv7QbnT4LiUv37B424DtKqmfnbqck9OzjKOv1J50KHz7iXTwSuZEL2m6BNy6H\nWUcN7dzzMitafsEd4bOIll3EB+IGmAcqm3j/wJf4SPCXXFL3Kr5XvgevfA+ARUB0zom8VH0tLw7M\nZVt3GZu6Smnt9XH0tBBH1fSypLyLaSUhSnD+Hh8RwpQwgJ/+qJ8IflRBxfH2feLcAYh7NzD8G0+9\n5uvMpSen3GcUAb0Hob9jnJ5/BQCv7+/m5MPqR2ltJJIL8c80HW4e0CIiAaAWGJFArqo3ATcBrFy5\nMun9/LzmFcxrXpEDs8dGQ1UpC2acDMefDHwcdj5LzQNf4rqWXxIJVBA99xvMOenK4Rk4cSw5/1Ow\n7r8o3fYnbnriOD5+xmLaDvWzc+NaQr4Sjj76+GHtV8yt5ZfP7KCvfCblnSkGfEdL9XQHe5l9HBU7\n/Unr+bd2DXBd6KM8XvEVAre/Gz56P9QvdgaPf/cZqJjOg5Wf4Onfb+DEhdNZ2lgNwC1/eY31+yPM\n+Ptv4zt8JvQcgJ3POJlOS87FV9PECiD/35ThKQ64iVHTF435o7PryinxC9v394ze2BhBLrJ9MkmH\nWwV82H19CfDIeOL9RcW8kyi9YjVc9Rj+Tz+P7+SrUwo/ANWN6MzlvKt2M9+4fyNPbd3Pfz68icW6\ng2j90hGDXSvmOUGRfTI9IdUzQmAw7JMw4Ju46pc72EvjUVQEA0nX8N3T0Usb0/jbObc5YaOfvcu5\nY1hzM+x+Hjnv63zj8tOpLA1w9c+fo6s/zN7OPv7r4c2cu2wmZx3u1iKqmO5MHjv+g876w4aRCYPi\nP3bP3+8T5k2r4PX93Tk2amqQtefvxvBj6XB+4JZYOhyw1s2K+Clwu4hswfH4L82236JAxBkEzbT5\nYWdyxNpbaK4v4ZO/fJ6O3hCfr9xN6exzRrRtnllNRdDPjoE65h16w4mNiiR4/nE/Nr7AyJj/7hdg\nxjIIVlAe9CddxjFWE712/lHwwXvh1nfCzy525gcsPhuOvoSZIvzXZcfxgZuf5gv3vEww4CMUUf7t\nHYlJXYYxRg5sAwTqFozr4wvqK9i+zzz/8ZCTPP8M0uH6VPX/qOoSVT0plhk05TjsLCTcx0/PitAX\nitBY0kttqA1mLhvR1O8Tjppdy8aeSoj0O7FRYFtbF9VBN8Y9Wqpn64bBGH55iZ9QRAlFosOaxCZ4\nNdWWOz9kf3cntO9wfkje/t3BQnOnLK7n8+cdwR/+toffvLCLK09fxAJ3wM0wxs2BbU5Bt5LxDdgu\nqK/k9f3dk2p+Sb6wGb75ZMGp4Asw98DT3HHlydxygTNgNaKgm8uKebW81OG26dxNa2cff/jbHs5c\n4ubJjJbq2dvuLJABVKRYxH13Ry8VQT81Ze6xFr4ZPrIaPnD3iDjs1WccxtuPbmJRQyWfPGvJGP94\nw0jCgW3jivfHWFhfQfdAhH1dAzk0ampg4p9PSqtg7kmw7TFWzKvjCJ87rT2xoJvLinl1tIRdoT/0\nBj976nXCUeX85W5hsMSYf3zYJxJ2isWV1QBDi7gn5vq/0dFHU23CBK+5J8Cit4ywR0T44d8dxwPX\nnk5FMBe5AsaUZ5w5/jEWNDh3nxb3Hzsm/vlm8Vmw5yUnO2bvOiirTblu6Yq5dbTilFjoP9jCz595\nnbcua6Sx0o31p0v17O90nksd8Y95/t39w8cFdnf0OSGfDBERggE7bYwc0NvuFBjMQvyHcv0t7j9W\n7CrON4edCSi89ri7gMuRwxdwiWPutHIod2anvrJ1O+09Ia48/bCh2H6i+EeTiL/r+c+d5oSPXts3\n3EN6o6N3sDyuYeSVg+6CQlmI/5y6cvw+Mc9/HJj455vZxzve+NZHnAHZxtQZMyLC0rkziSKs27aL\nFXNrWblg2lB4JzHso1FnYRhwFsiAQc9/eVMNIvC3XR2DHwlFnKnxsYUxDCOvZJHmGSMY8DGnrtw8\n/3Fg4p9v/AFY+BZYd5/jnaeI98c4Zv50urWMUO8hPvaWw5zYfCRZbR/3deyHIcHzrywNsHhGFa/E\niX/roX5UMc/fKAwx8Z+2MKvDLKi3XP/xYOJfCA4705nSDikzfWKsmFtHF+XMLB3ggqPckrfRJOIf\nuwuIhX4SPH+AY+bU8nLLkPjvaXfK4Zr4GwXhwGvOOtXB7FKGF9ZX8to+S/ccKyb+hWDxWUOvk+T4\nx3PsvDp6KOPoBj8Bv/t1xQTen7CAOwwN+g56/rWDTY6aU0vroX5aO53c/j3xOf6GkW+yzPSJsaC+\ngkN94ZGFC420mPgXgvolznqlNXOHiXMyplUGWTC7kQXVcZOzIkkGfAc9f/euIInnf/Rcp69Y3D+2\nClJTnXn+RgHIMsc/Rnx1TyNzTPwLgQic+c/w5mszah4oq0H6Dw1tiKao6glxnr8b3ikbEv/YoG8s\n9LOno4/KoJ/qUsvZN/JMfxd07c2J57+wIVbd0wZ9x4Jd9YXi+A9m3ra02qmWGSNVqmf8vr5O8JdC\noHSwSWVpgCVxg7572vtoqisfsYKXYUw4B7c7zzkQ/7nTKhAxz3+smOfvBYJVMBDv+adI9YThMf84\nrz/G0XNqh8I+nX022GsUhhykecYoK/Ezu7bcPP8xYuLvBUqrIT7sE0lRzx+GQkJ9ncPi/TFig757\nO/vY024TvEZDRM4XkVdFZIuIfDFNu0tEREVk7EtSTUUG0zyzj/mDW93TPP8xYeLvBUqrnBhpLJVt\nMOwTV9I5MdUzhed/jDvo+8KOg7R19TPLMn1SIiJ+4EbgAmA5cJmIjJiYISLVwKeBZ/JroYc5sA0q\nZyQ9R8eDU93TPP+xYOLvBYJVQ0tOghP28QWGl4VITPVM4fkvn12DT+BPG1pRhdnm+afjJGCLqm5T\n1QHgTuDiJO2+CnwT6MuncZ4mR2meMRbWV3Cge4COXkv3zBQTfy8QE/GBLuc5Eho+2AsjUz37Dznh\nogQqgs5M34c37AWw0g7pmQPsjHvf4m4bRESOA+ap6u/THUhErhKRtSKytq2tLfeWeo0Dr+VU/GNr\nS+ww7z9jTPy9QGmV8xyL+0cjw+P9kCTVszPlHIKj59Zy0J0QYzH/tCRLgxqcRioiPuB7wOdGO5Cq\n3qSqK1V15YwZM3JoogcJ9UJnS87i/TC0mLvF/TPHxN8LBBPFPzRizd+kqZ5Jwj7gZPzEMPFPSwsw\nL+79XGB33Ptq4CjgMRHZDpwMrLJB31E4+LrznFPPP5brb+KfKSb+XiAWvskk7BMJOXcGA4dSDqbF\nxL+qNEB1WUnSNgYAa4BmEVkkIkGctadXxXaqaoeqNqjqQlVdCDwNXKSqawtjrkfIYZpnjIpggJnV\npVbdcwyY+HuBmPj3u+IfDScJ+8Ri/pGhO4QUnn9s0Ne8/vSoahi4BngA2ADcparrROQGEbmosNZ5\nmEHxz13YB5wyD+b5Z47N8PUCg2Eft15PLNsnHn9c2CehnHMiFcEAR8yqYbbV9BkVVV0NrE7Ydn2K\ntmfmwybPc2AblNVBxfScHnZBfQWPbbLB9Ewx8fcCiWGfaDhJzD8u7JOkqFsi//PBE2w5RqMw5DjN\nM8bChkranmuhuz9MpdWrGhW7+r3AYLZPfMw/IewTn+o5iucPMG96BY015vkbBWCCxD826LvjgMX9\nM8HE3wuMyPZJEvaJT/Uc9PzTl4s2jLwTHoCOnRPj+bu5/hb3z4ysxF9EpovIQyKy2X2elqTNsSLy\nlIisE5GXReT92fQ5JfH5oaRylLBP5jF/wygY7TuctaYnQPznD+b6m+efCdl6/l8EHlbVZuBh930i\nPcCHVPVI4Hzg+yJSl2W/U4/SqiHPf7RUzz63ln+amL9hFIQJSPOMUVNWQn1l0Dz/DMlW/C8GbnNf\n3wa8K7GBqm5S1c3u691AKzDFpziOg/jKnqOmeprnbxQpEyj+4Fb33GeefyZkK/6NqroHwH2ema6x\niJwEBIGtKfZb/ZNUBKsSwj6JA75xYZ++TufHIGADukaRcWAbBKuhsmFCDm+5/pkzqviLyJ9E5JUk\nj2TVDdMdpwm4Hfh7VY0ma2P1T9JQWp0wycs/fH98qmesnLOt0GUUG7F1eyfo3FxQX8nujj76QpEJ\nOf5kYtRkWFU9N9U+EdkrIk2quscV99YU7WqAPwD/qqpPj9vaqUxpNbS7BSYjoZHx/Ph6/mnq+hhG\nQTn4GjQeNWGHj63nu/NAD82NI6vaGkNkG/ZZBXzYff1h4L7EBm5NlN8AP1PVu7Psb+oSv5RjNMmA\n72CqZzjlQi6GUVAiYaeo2wTF+2GotLNl/IxOtuL/H8BbRWQz8Fb3PSKyUkRudtu8Dzgd+IiIvOg+\njs2y36lHfLZPNDIy1VMExG+ev1G8dLY45+cEiv9Cq+6ZMVnNgVbV/cA5SbavBT7mvv458PNs+jEY\nHvNPNsMXnNBPLOY/gReYYYyLCc70AairCFJbXmJ1/TPAZvh6hWA1RPqdGZLJZviC84MQjZjnbxQn\neRB/cLx/W893dEz8vUKsvs9AV/JUT3BCQdGQxfyN4uTAaxAoh+pZE9rNgvpK8/wzwMTfKwzW9D/k\nhn38I9v4SpxF3vsPmedvFB+xgm4TnIK8sL6CXQd7GQgnzSg3XEz8vUIwwfNPFfPvawfUPH+j+Ijl\n+E8w8+sriSq0HLTQTzpM/L1C/CLu0VDysI8vAD0H3PYm/kYREY06YZ88iP9Qxo+JfzpM/L1CTMz7\nu5xB3aQDvvHibxNcjCLi0G4nYSEPWWhDuf4W90+Hib9XGAz7HEpe1ROcu4Ge/c5rC/sYxUSeMn0A\nGqqCVAb95vmPgom/V4gf8E2X6hkTf1vIJSeIyPki8qqIbBGRESXLReSzIrLeXaviYRFZUAg7i559\nm53nPIi/iLCgvpKtbV0T3peXMfH3CvExf42kT/UE8/xzgIj4gRuBC4DlwGUisjyh2QvASlU9BrgH\n+GZ+rfQI2x6F6tlQOy8v3Z2wYBprth+wAm9pMPH3CkHX8+896DynSvWMYQO+ueAkYIuqblPVAeBO\nnDUsBlHVR1U1Fl94GpibZxuLn3A/bH0Ulp6Xt0qz5yybSV8oylNb9+elPy9i4u8V/AFngsyg+KdI\n9Yxhnn8umAPsjHvf4m5LxRXAH5PtmNJrVWz/s5OifPgFeevy5MPqqQj6+dOGvXnr02uY+HuJ0iro\nbXdep0r1BKfAW0lF/uyavCRzUzVpQ5HLgZXAt5Ltn9JrVWy633FcFp2ety7LSvy8eUkDj2xsRTXp\nVzblMfH3EsGqOM8/Raon2EIuuaMFiA9SzwV2JzYSkXOB64CLVLU/T7Z5A1VH/A87E0rK89r1ucsa\n2dPRx/o9nXnt1yuY+HuJ0ur04h+7G7B4f65YAzSLyCJ3XYpLcdawGEREjgP+B0f4ky5mNKVp3QDt\nO+Dw8/Pe9VlHOKvKPrzBvpZkmPh7idHEP97zN7JGVcPANcADwAbgLlVdJyI3iMhFbrNvAVXA3e5a\nFatSHG5qsskdAmk+L+9dz6guZcW8Oh7eaOKfjKzq+Rt5Jj7skzTVM+b5W45/rlDV1cDqhG3Xx71O\nucypAWx6AJqOhZqmgnR/7hEz+c5Dm2g91MfM6rKC2FCsmOfvJUqroa/DeZ0s2ye2zTx/oxjo3gc7\nn81rlk8i5yxrBOBR8/5HYOLvJUqrGEw2SZbnbzF/o5jY/CCgTn5/gVjWVM3s2jKL+yfBxN9LxOr7\nQPpUT/P8jWJg0/1Q3eSEfQqEiHD2spk8uXmfzfZNwMTfS8R79OkGfM3zNwpNeAC2PJLXWb2pOGdZ\nI72hCE9vs9m+8Zj4e4nSOM8/3Qxf8/yNQvP6n50KtEvzn+KZyCmH1VNe4rfQTwIm/l5iWNjHPH+j\niNn0AATKYNEZhbbEme3b3MDDG/babN84TPy9RPwCLekmeZnnbxQSVXj1j86s3mBxlBk5d9lMdnf0\nsfGNQ4U2pWjISvxFZLqIPCQim93naWna1ojILhH5YTZ9TmmGiX+aVE/L8zcKSdtGaH+9oFk+iZx1\neGy2rxV6i5Gt5/9F4GFVbQYedt+n4qvA41n2N7WJD/uY528UK5vud56LIN4fY2ZNGSvm1tps3ziy\nFf+Lgdvc17cB70rWSEROABqBB7Psb2oT7/lbzN8oVl69H5pWQM3sQlsyjHOWNfLiznb2dVntPche\n/BtVdQ+A+zwzsYGI+IDvAJ8f7WBTuuZ5JoyW7WN5/kah6d4PLc8Wldcf4+wjZqIKj5j3D2Qg/iLy\nJxF5Jcnj4tE+6/IJYLWq7hyt4ZSueZ4Jo+X5zzramVBT0ZA/mwwjni0PgUaLUvyPnF1DU20Zj1jK\nJ5BBYbd0hatEZK+INKnqHhFpApL9V08B3iIin8CpfhgUkS5VTTc+YCRjtFTPxWc5D8MoFK/+Eapm\nFXRWbypEhLOPmMlvX9hFfzhCaSBJiZQpRLZhn1XAh93XHwbuS2ygqh9Q1fmquhD4R+BnJvzjJBAE\nf9B5nczzN4xCEh6ALQ/D0reBrzizyM9ZNpPugQhPbztQaFMKTrbf0H8AbxWRzcBb3feIyEoRuTlb\n44wkxAZ9k8X8DaOQ/O0ud1Zv4ap4jsapixsoK/Hxi6dfJxyJFtqcgpKV+KvqflU9R1Wb3ecD7va1\nqvqxJO1vVdVrsulzyhML/SQr7GYYheLpH8N918C8N8GScwptTUrKSvxcc9YSHly/l6t//hw9A+FC\nm1QwivPezEjNoOc/teOVRpEQjcID18H9X4Aj3g4fug8CpYW2Ki3XnN3MVy8+kkc2tnLZT56Zsqmf\nJv5ew8I+RrEQ7odfXwFP/RBOugre97O8L9I+Xj54ykJ+fPkJvPpGJ+/90V/Zvq+70CblHRN/rxEL\n+9iAr1FIeg/C7e+BdffCW2+AC77pubvRtx05i19eeTKdvSHe86O/8sKOg4U2Ka+Y+HuNUov55xMR\nOV9EXhWRLSIyIktNREpF5Ffu/mdEZGH+rcwz7Tvhlgtg5zPwnpvhtM8UvGb/eDl+/jR+/X9Ppao0\nwGU/eZqH1k+d2j/mPnqN0mpAPOdleRER8QM34mSytQBrRGSVqq6Pa3YFcFBVl4jIpcA3gPfn39oJ\nIDwAnS3QvsMR/PYdzmPrIxDugw/eC4tOL7SVWXPYjCru/cSpXHHrGj5++1reuryR+dMrmDutgjl1\n5cydXs6cunKqyyaXw2Xi7zWC1RbyyR8nAVtUdRuAiNyJU88qXvwvBr7svr4H+KGIiI6ncPyvr4Q3\nXs7K4BGkNUOd/RqNe7jvIwPQ3cbgmtEA4oPq2TBzGZz/dWg8Mre2FpCGqlLuuOpkvrJqPWteP8Bj\nr7bRHx6eClpTFqCyNIBPBBHwieBzn0WcSWSpmIj7oruvPoW6iuC4P28q4jVWXAp18wptxVRhDhBf\nlqQFeFOqNqoaFpEOoB7YF99IRK4CrgKYP39+8t6mLYDIRGSepJEe8SV/+Fyhr5sHdfOdR82cSR1u\nrAgG+MYlxwCgquzrGqDlYA8tB3vZ1d7LroO99IcjRBWiqqj7HFWIRlP/yCoTs4CMz5fdT4qJv9do\nOsZ5GPkg2dWVeCVn0gZVvQm4CWDlypXJ1eDsfx2jecZEISLMqC5lRnUpx81PuUyJp7EBX8NITQsQ\nf5s1F9idqo2IBIBawGoHGEWPib9hpGYN0Cwii0QkCFyKU88qnvj6VpcAj4wr3m8YecbCPoaRAjeG\nfw3wAOAHblHVdSJyA7BWVVcBPwVuF5EtOB7/pYWz2DAyx8TfMNKgqquB1Qnbro973Qf8n3zbZRjZ\nYmEfwzCMKYiJv2EYxhTExN8wDGMKYuJvGIYxBZFizUoTkTbg9RS7G0iYQVlgismeYrIFisueRFsW\nqOqMfBvhoXO7WGwpFqcYKmsAAAc+SURBVDugeGxJZ0dG53XRin86RGStqq4stB0xismeYrIFisue\nYrIlFcVkY7HYUix2QPHYkgs7LOxjGIYxBTHxNwzDmIJ4VfxvKrQBCRSTPcVkCxSXPcVkSyqKycZi\nsaVY7IDisSVrOzwZ8zcMwzCyw6uev2EYhpEFJv6GYRhTEM+J/2gLaueh/1tEpFVEXonbNl1EHhKR\nze5zXlZ/EJF5IvKoiGwQkXUi8plC2SMiZSLyrIi85NryFXf7Indh883uQufjX3du7Db5ReQFEfl9\noW0ZjUKf1wm2bBeRv4nIiyKyNs99F8X1lcKOL4vILvf/8qKIXDjRdrj9Tsh17inxj1tQ+wJgOXCZ\niCzPsxm3AucnbPsi8LCqNgMPu+/zQRj4nKouA04GPun+PwphTz9wtqquAI4FzheRk3EWNP+ea8tB\nnAXP88VngA1x7wtpS0qK5LxO5CxVPbYAOe23UhzXVzI7wDl/jnUfq5Psnwgm5Dr3lPgTt6C2qg4A\nsQW184aqPsHIlZouBm5zX98GvCtPtuxR1efd14dwhG5OIexRhy73bYn7UOBsnIXN82YLgIjMBd4O\n3Oy+l0LZkgEFP6+LhWK5vlLYURAm6jr3mvgnW1B7ToFsiadRVfeA80UBM/NtgIgsBI4DnimUPW6Y\n5UWgFXgI2Aq0q2rYbZLP7+v7wD8BUfd9fQFtGY1iO68VeFBEnnMXni80Bb++4rhGRF52w0J5X9w3\nl9e518Q/o8WypxoiUgX8GrhWVTsLZYeqRlT1WJy1bk8CliVrNtF2iMg7gFZVfS5+cyFsyZBis+00\nVT0eJwz1SRE5vYC2FBM/AhbjhDX3AN/JZ+e5vs69Jv6ZLKhdCPaKSBOA+9yar45FpATnhPiFqt5b\naHsAVLUdeAwnPlnnLmwO+fu+TgMuEpHtOCGUs3HuBAphSyYU1Xmtqrvd51bgNzg/5IWkoOdzDFXd\n6zo4UeAn5PH/MhHXudfEP5MFtQtB/CLeHwbuy0enbhz7p8AGVf1uIe0RkRkiUue+LgfOxYlNPoqz\nsHnebFHVf1bVuaq6EOcceURVP1AIWzKkaM5rEakUkerYa+BtwCvpPzXhFOT6SiQmtC7vJk//lwm7\nzlXVUw/gQmATTjz5ugL0fwfOLV8Ix2O7Aiee/DCw2X2enidb3owTHngZeNF9XFgIe4BjgBdcW14B\nrne3HwY8C2wB7gZK8/x9nQn8vhhsGcXOgp7XcXYcBrzkPtbl25Ziub5S2HE78Df3HF8FNOXpfzIh\n17mVdzAMw5iCeC3sYxiGYeQAE3/DMIwpiIm/YRjGFMTE3zAMYwpi4m8YhjEFCYzexCgEIhJL4wKY\nBUSANvd9j6qeWhDDDCMOEYngpD/GeJeqbi+QOcYYsFRPDyAiXwa6VPXbhbbFMOIRkS5VrUqzP6BD\n9ZSMIsLCPh5ERLrc5zNF5HERuUtENonIf4jIB9y6+n8TkcVuuxki8msRWeM+TivsX2BMZkTkIyJy\nt4j8DnjQ3fZ599x7Wdy1Htzt17nrGPxJRO4QkX90tz8mIivd1w1uqY5Y8cBvxR3r4+72M93P3CMi\nG0XkF+7MWETkRBH5qzhrTTwrItUi8qSIHBtnx19E5Jh8/Y+KAQv7eJ8VOAXUDgDbgJtV9SR3wYdP\nAdcC/4lTh/zPIjIfeIDkRdcMY6yUu5VcAV5T1Xe7r08BjlHVAyLyNqAZpxaOAKvcYnHdOKUsjsPR\noueB50jPFUCHqp4oIqXAX0TkQXffccCROHWR/gKcJiLPAr8C3q+qa0SkBujFKfX9EeBaEVmKM9v7\n5az+Ex7DxN/7rFG3rKuIbMX1tHDisGe5r88FlruOEECNiFSrUxvcMLKhV51Krok8pKqxevhvcx8v\nuO+rcH4MqoHfqGoPgIhkUs/obcAxIhKr0VTrHmsAeFZVW9xjvQgsBDqAPaq6BkDdapgicjfwbyLy\neeCjOIu3TClM/L1Pf9zraNz7KP+/vbvnhSCKwjj+f1QUWsXqhVoUOl9AIREaFCoSRO8DaFREIZGo\n+QZIFBQqW6iU1Drxkgg5intlx8aqZJbc51fNbGbuzGZ2Tu6cnZzTur49wHhEvNR5Yla0p8qygM2I\n2KtuIGmdzqWr32ilpXvbxlqNiOO2sSb4ei+8k37/+u4YEfEs6ZTUEGUGqLtjWdc551+GE2Dlc6Wa\n6zSrwTGwmOvRI2lQ0gBwDkxJ6suVRCcr+9wCo3l5um2s5VziGElDufpoJzdAQ9JY3r6/UtZ7H9gm\nPT3/ia5ddfLMvwxrwK6ka9I1PweWuntKVoqIOJE0Alzm1OMjMBcRTUmHpCqVd8BFZbct4EjSPHBW\n+XyflM5p5j907/mhfWFEvEqaBXZyqfEXUhr0MSKuJD0AB7/0Vf8Vv+ppZn9C3a80S2qQmg4NR2rQ\nUhSnfcysOJIWSH1wN0oM/OCZv5lZkTzzNzMrkIO/mVmBHPzNzArk4G9mViAHfzOzAn0AwxsVA5rM\nZDoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f06d657be80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(1, 9):\n",
    "    lpv = K.get_value(model.get_layer(\"low_pass_{}\".format(i)).kernel)[:, 0, 0]\n",
    "    hpv = K.get_value(model.get_layer(\"high_pass_{}\".format(i)).kernel)[:, 0, 0]\n",
    "    \n",
    "    fig, axes = plt.subplots(1, 2)\n",
    "    \n",
    "    ax = axes[0]\n",
    "    ax.plot(lpv)\n",
    "    ax.plot(hpv)\n",
    "    \n",
    "    ax = axes[1]\n",
    "    ax.plot(np.abs(np.fft.rfft(lpv)))\n",
    "    ax.plot(np.abs(np.fft.rfft(hpv)))\n",
    "    axes[0].set_title(\"Filter Coefficients\")\n",
    "    axes[1].set_title(\"FFT magnitudes\")\n",
    "    axes[0].set_xlabel(\"Time\")\n",
    "    axes[1].set_xlabel(\"Frequency\")\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
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    "The wavelet filters surprisingly change very little with the filters deeper in the network changing less and less. In fact the filters change so little it makes me suspicious that my network is somehow suffering from poor normalization or poorly chosen learning rates. However it also makes sense that the orthogonality of the initial wavelet filters would make a potential well too deep for the network to escape. \n",
    "\n",
    "It is tempting to add small amounts of noise to the starting filter coefficients to see whether or not they tend to relax back towards the perfect reconstruction filters. "
   ]
  }
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  "nikola": {
   "category": "",
   "date": "2018-01-08",
   "description": "Wavelets are a natural alternative to short time fourier transforms for audio feature extraction. I experiment with wavelet inputs for the TensorFlow speech recognition challenge.",
   "link": "",
   "slug": "waveletSpectrogramsTFSR",
   "tags": "machine learning, kaggle, wavelets, neural networks, audio, speech recognition",
   "title": "Wavelet Spectrograms for Speech Recognition",
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