learned_inverse_stft.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BW7lpLAzSkpo"
      },
      "source": [
        "# Classification\n",
        "The AudioMNIST dataset contains recordings of spoken digits (0-9) by 60 speakers, with a total of 30,000 audio samples.\n",
        "\n",
        "This notebook trains a 1D transposed convolution layer to learn an inverse short-time Fourier transform that can reconstruct a waveform signal from its corresponding STFT matrix. The trained network is evaluated against 12 (20%) of the speakers, withheld as validation set from training."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TM9ccKrNAx2X",
        "outputId": "0d361d2b-4c60-424b-bf77-937195eadc80"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-02-22 17:51:59--  https://github.com/soerenab/AudioMNIST/archive/refs/heads/master.zip\n",
            "Resolving github.com (github.com)... 140.82.121.3\n",
            "Connecting to github.com (github.com)|140.82.121.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://codeload.github.com/soerenab/AudioMNIST/zip/refs/heads/master [following]\n",
            "--2023-02-22 17:51:59--  https://codeload.github.com/soerenab/AudioMNIST/zip/refs/heads/master\n",
            "Resolving codeload.github.com (codeload.github.com)... 140.82.121.10\n",
            "Connecting to codeload.github.com (codeload.github.com)|140.82.121.10|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: unspecified [application/zip]\n",
            "Saving to: ‘master.zip’\n",
            "\n",
            "master.zip              [<=>                 ] 948.50M  6.89MB/s    in 2m 5s   \n",
            "\n",
            "2023-02-22 17:54:04 (7.60 MB/s) - ‘master.zip’ saved [994575418]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "### Download AudioMNIST data\n",
        "!wget https://github.com/soerenab/AudioMNIST/archive/refs/heads/master.zip\n",
        "!unzip master.zip > /dev/null 2>&1 # Hide output"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "SeQe_Zn7TrbA"
      },
      "outputs": [],
      "source": [
        "### Imports\n",
        "import os\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import librosa\n",
        "import librosa.display\n",
        "import torch\n",
        "from torchvision.models import resnet50, ResNet50_Weights\n",
        "from torch.autograd import Variable\n",
        "import torch.optim as optim\n",
        "import torch.nn as nn\n",
        "from torch.utils import data\n",
        "from IPython.display import clear_output\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from IPython.display import Audio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "eJzngjZuMZug"
      },
      "outputs": [],
      "source": [
        "### Find all .wav files\n",
        "path_in = \"AudioMNIST-master/data/\"\n",
        "paths_wav = []\n",
        "\n",
        "for path, subdirs, files in os.walk(path_in):\n",
        "    for name in files:\n",
        "        if \".wav\" in name:\n",
        "          paths_wav.append(os.path.join(path, name))\n",
        "\n",
        "# Extract digit label from file names\n",
        "labels = [os.path.basename(f).split(\"_\")[0] for f in paths_wav]\n",
        "labels = np.array(labels).astype(np.uint8)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "BOfjrvyaUkAq"
      },
      "outputs": [],
      "source": [
        "### Define parameters for short-time fourier transform\n",
        "stft_param = {}\n",
        "stft_param[\"nfft\"] = 256\n",
        "stft_param[\"hop\"] = stft_param[\"nfft\"] // 2\n",
        "stft_param[\"signal_length\"] = 48000"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "4KzyU64lSpMP"
      },
      "outputs": [],
      "source": [
        "### Convert waveform to matrix with short-time fourier transform\n",
        "def wav_to_stft_matrix(signal, stft_param):\n",
        "\n",
        "  max_length = stft_param[\"signal_length\"]\n",
        "\n",
        "  # Pad or crop signal to desired length\n",
        "  dif = max_length - len(signal)\n",
        "  if dif > 0:\n",
        "      signal = np.hstack((signal, np.zeros(dif)))\n",
        "  else:\n",
        "      signal = signal[:max_length]\n",
        "\n",
        "  # Get stft matrix\n",
        "  D = librosa.stft(signal, n_fft=stft_param[\"nfft\"], hop_length=stft_param[\"hop\"])\n",
        "\n",
        "  return (signal, D)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "thmG2yCTYt9F",
        "outputId": "70b7e267-216b-47d3-a9c0-42d7cee09f87"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Split 30000 samples in to 24000 vs 6000 train/val\n"
          ]
        }
      ],
      "source": [
        "##### Create randomized training/validation split on speaker level\n",
        "\n",
        "# Determine speaker of each sample from filename\n",
        "speakers = [os.path.basename(f.split(\"_\")[1]) for f in paths_wav]\n",
        "\n",
        "paths_wav = np.array(paths_wav)\n",
        "speakers = np.array(speakers)\n",
        "\n",
        "# Isolate unique speaker IDs\n",
        "speakers_uq = np.unique(speakers)\n",
        "S = len(speakers_uq)\n",
        "\n",
        "# Select random speakers\n",
        "np.random.shuffle(speakers_uq)\n",
        "\n",
        "train_share = 0.8\n",
        "first_val = int(S * train_share)\n",
        "\n",
        "speakers_train = speakers_uq[:first_val]\n",
        "speakers_val = speakers_uq[first_val:]\n",
        "\n",
        "# Split samples according to speaker selection\n",
        "mask_train = np.in1d(speakers, speakers_train)\n",
        "paths_wav_train = paths_wav[mask_train]\n",
        "\n",
        "mask_val = np.in1d(speakers, speakers_val)\n",
        "paths_wav_val = paths_wav[mask_val]\n",
        "\n",
        "print(f\"Split {len(paths_wav)} samples in to {len(paths_wav_train)} vs {len(paths_wav_val)} train/val\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "P63B8ofyduV7"
      },
      "outputs": [],
      "source": [
        "### Plotting loss curves\n",
        "def plot_losses(losses_train, losses_val, losses_val_it):\n",
        "\n",
        "  losses_train = np.array(losses_train).astype(\"float\")\n",
        "  losses_val = np.array(losses_val).astype(\"float\")\n",
        "  \n",
        "  # Plot losses\n",
        "  plt.close()\n",
        "  clear_output()    \n",
        "\n",
        "  f, ax1 = plt.subplots(figsize = (12, 4)) \n",
        "\n",
        "  ax1.plot(losses_train)\n",
        "  ax1.set_ylabel(\"Training loss\", color=\"C0\")\n",
        "\n",
        "  ax2 = ax1.twinx()\n",
        "  ax2.plot(losses_val_it, losses_val, color=\"C1\")\n",
        "  ax2.set_ylabel(\"Validation loss\", color=\"C1\")\n",
        "\n",
        "  ax1.grid(True, axis=\"y\")\n",
        "  plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "nHcOHisaSy6e"
      },
      "outputs": [],
      "source": [
        "### Data loader\n",
        "class WaveformMatrixDataset(data.Dataset):\n",
        " \n",
        "    def __init__(self, paths_wav, stft_param, do_augment):\n",
        "        self.paths_wav = paths_wav\n",
        "        self.stft_param = stft_param\n",
        "        self.do_augment = do_augment\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.paths_wav)\n",
        "\n",
        "    def __getitem__(self, index):\n",
        "\n",
        "        signal, sr = librosa.load(self.paths_wav[index], sr=None)\n",
        "        (signal, D) = wav_to_stft_matrix(signal, self.stft_param)\n",
        "        \n",
        "        magnitude = np.abs(D)\n",
        "        phase = np.angle(D)\n",
        "\n",
        "        D = np.vstack((magnitude * np.cos(phase), \n",
        "                       magnitude * np.sin(phase)))\n",
        "\n",
        "        # Convert to pytorch tensor\n",
        "        X = Variable(torch.from_numpy(D)).float()\n",
        "        Y = Variable(torch.from_numpy(signal)).float()\n",
        "\n",
        "        name = os.path.basename(self.paths_wav[index])\n",
        "\n",
        "        return X, Y, name"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "YQ9cLSrQpW1F"
      },
      "outputs": [],
      "source": [
        "def get_data_loader(paths_wav, stft_param, B, do_shuffle, do_augment):\n",
        "  dataset = WaveformMatrixDataset(paths_wav, stft_param, do_augment)\n",
        "  loader = torch.utils.data.DataLoader(dataset,\n",
        "                                    num_workers=1,\n",
        "                                    batch_size=B,\n",
        "                                    shuffle=do_shuffle,\n",
        "                                    pin_memory=True,\n",
        "                                    # use different random seeds for each worker\n",
        "                                    # courtesy of https://github.com/xingyizhou/CenterNet/issues/233\n",
        "                                    worker_init_fn = lambda id: np.random.seed(torch.initial_seed() // 2**32 + id) )\n",
        "\n",
        "  return loader"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "9wm28QmHVzsB"
      },
      "outputs": [],
      "source": [
        "### Use a single transpose convolution layer\n",
        "def initialize_network(stft_param):\n",
        "\n",
        "    net = nn.ConvTranspose1d(in_channels = stft_param[\"nfft\"] + 2,\n",
        "                              out_channels = 1, \n",
        "                              kernel_size=stft_param[\"nfft\"], \n",
        "                              stride = stft_param[\"hop\"], \n",
        "                              padding = stft_param[\"nfft\"] // 2, \n",
        "                              output_padding = 0)\n",
        "    return net"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "UhiOXb9PZtP4",
        "outputId": "540ea7e1-406a-4490-9eeb-631daf7cb0a0"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "### Train network\n",
        "net = initialize_network(stft_param)\n",
        "\n",
        "B = 32 # batch size\n",
        "\n",
        "lr = 0.001 * 10 # learning rate\n",
        "lr_exponent = 0.9 # exponent for poly learning rate policy\n",
        "\n",
        "I = 100 # training iterations\n",
        "I_val = 10 # validate after this many iterations\n",
        "\n",
        "criterion = nn.L1Loss()\n",
        "optimizer = optim.AdamW(net.parameters(), lr=lr)\n",
        "\n",
        "# Get training data loader\n",
        "loader_train = get_data_loader(paths_wav_train, stft_param, B, do_shuffle=True, do_augment=True)\n",
        "loader_val = get_data_loader(paths_wav_val, stft_param, B, do_shuffle=False, do_augment=False)\n",
        "\n",
        "#\n",
        "net.train()\n",
        "net = net.cuda()\n",
        "\n",
        "losses_train = []\n",
        "\n",
        "losses_val = [] # Mean loss across full validation set\n",
        "losses_val_it = [] # Iteration index of validation loss values\n",
        "\n",
        "i = 0\n",
        "while i < I:\n",
        "\n",
        "  for X, Y, _ in loader_train:\n",
        "\n",
        "      if i >= I: break\n",
        "      i += 1\n",
        "\n",
        "      X = X.cuda(non_blocking=True)\n",
        "      Y = Y.cuda(non_blocking=True)\n",
        "\n",
        "      optimizer.zero_grad()\n",
        "\n",
        "      outputs = net(X)\n",
        "      outputs = torch.squeeze(outputs)\n",
        "\n",
        "      loss = criterion(outputs, Y)\n",
        "      loss.backward()\n",
        "      optimizer.step()\n",
        "\n",
        "      losses_train.append(loss.detach().item())\n",
        "\n",
        "      # Use poly learning policy\n",
        "      lr_i = optimizer.param_groups[0]['lr'] \n",
        "      optimizer.param_groups[0]['lr'] = lr * (1 - i / I)**lr_exponent\n",
        "\n",
        "      # Validate at current snapshot        \n",
        "      if i > 1 and (i % I_val) == 0:\n",
        "          \n",
        "          net.eval()\n",
        "\n",
        "          with torch.no_grad():\n",
        "\n",
        "            losses_val_snapshot = []\n",
        "\n",
        "            for X, Y, name in loader_val:\n",
        "\n",
        "              X = X.cuda(non_blocking=True)\n",
        "              Y = Y.cuda(non_blocking=True)    \n",
        "\n",
        "              outputs = net(X)\n",
        "              outputs = torch.squeeze(outputs)\n",
        "              \n",
        "              loss = criterion(outputs, Y)    \n",
        "\n",
        "              losses_val_snapshot.append(loss.detach().item())\n",
        "            \n",
        "            # Aggregate to mean validation loss at current snapshot\n",
        "            losses_val.append(np.mean(losses_val_snapshot))\n",
        "            losses_val_it.append(i-1)\n",
        "\n",
        "            plot_losses(losses_train, losses_val, losses_val_it)\n",
        "          \n",
        "          net.train()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### Validate with more detail\n",
        "with torch.no_grad():\n",
        "\n",
        "  net = net.eval()\n",
        "\n",
        "  # Pick random validation sample\n",
        "  X, Y, name = next(iter(loader_train))   \n",
        "\n",
        "  X = X.cuda(non_blocking=True)\n",
        "  Y = Y.cuda(non_blocking=True)    \n",
        "\n",
        "  outputs = net(X)\n",
        "  outputs = outputs.squeeze()\n",
        "\n",
        "  signal = Y[0].cpu().data.numpy()\n",
        "  signal_rec = outputs[0].cpu().data.numpy()\n",
        "\n",
        "\n",
        "  plt.plot(signal)\n",
        "  plt.title(\"Ground truth\")\n",
        "  plt.show()\n",
        "  plt.close()\n",
        "\n",
        "  sr = 48000\n",
        "\n",
        "  wn = Audio(data=signal, rate=sr)\n",
        "  display(wn)\n",
        "\n",
        "  plt.plot(signal_rec)\n",
        "  plt.title(\"Reconstructed\")\n",
        "  plt.show()\n",
        "  plt.close()\n",
        "\n",
        "  wn2 = Audio(data=signal_rec, rate=sr)\n",
        "  display(wn2)\n",
        "\n",
        "  plt.plot(signal - signal_rec)\n",
        "  plt.title(\"Difference\")\n",
        "  plt.show()\n",
        "  plt.close() \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 895
        },
        "id": "qS4GuAcoObs8",
        "outputId": "e5b2c041-f2a1-4164-b188-aadec94654fe"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
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              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}