ASMA_Tools_Natalia_V2.ipynb

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        "<a href=\"https://colab.research.google.com/github/nataliakotsani/ASMA/blob/main/ASMA_Tools_Natalia_V2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "source": [
        "#Habitual Frequency"
      ],
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        "id": "vmecGz4SZhQX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Select Button: Choose Files\n",
        "2. Select a file with a filename \"F0.wav\""
      ],
      "metadata": {
        "id": "jqB8A0IcGIWP"
      }
    },
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          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: praat-parselmouth in /usr/local/lib/python3.7/dist-packages (0.4.1)\n",
            "Requirement already satisfied: numpy>=1.7.0 in /usr/local/lib/python3.7/dist-packages (from praat-parselmouth) (1.21.6)\n"
          ]
        },
        {
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              "\n",
              "     <input type=\"file\" id=\"files-724fb1db-fa76-417a-870a-31c94e3b5223\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
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              "      Upload widget is only available when the cell has been executed in the\n",
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              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
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              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
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              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
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              "  return _uploadFilesContinue(outputId);\n",
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              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
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              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
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              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
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              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
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              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
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              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
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              "  for (const file of files) {\n",
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              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
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              "      let percentDone = fileData.byteLength === 0 ?\n",
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              "          Math.round((position / fileData.byteLength) * 100);\n",
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              "\n",
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          "ename": "MessageError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mMessageError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-19-c4f258843b64>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mgoogle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolab\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m \u001b[0muploaded\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupload\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[0m\u001b[1;32m     20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mfn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0muploaded\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\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[0;32m/usr/local/lib/python3.7/dist-packages/google/colab/files.py\u001b[0m in \u001b[0;36mupload\u001b[0;34m()\u001b[0m\n\u001b[1;32m     40\u001b[0m   \"\"\"\n\u001b[1;32m     41\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 42\u001b[0;31m   \u001b[0muploaded_files\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_upload_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmultiple\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\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     43\u001b[0m   \u001b[0;31m# Mapping from original filename to filename as saved locally.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m   \u001b[0mlocal_filenames\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\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[0;32m/usr/local/lib/python3.7/dist-packages/google/colab/files.py\u001b[0m in \u001b[0;36m_upload_files\u001b[0;34m(multiple)\u001b[0m\n\u001b[1;32m    125\u001b[0m     result = _output.eval_js(\n\u001b[1;32m    126\u001b[0m         'google.colab._files._uploadFilesContinue(\"{output_id}\")'.format(\n\u001b[0;32m--> 127\u001b[0;31m             output_id=output_id))\n\u001b[0m\u001b[1;32m    128\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'action'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'append'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    129\u001b[0m       \u001b[0;31m# JS side uses a generator of promises to process all of the files- some\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/google/colab/output/_js.py\u001b[0m in \u001b[0;36meval_js\u001b[0;34m(script, ignore_result, timeout_sec)\u001b[0m\n\u001b[1;32m     38\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mignore_result\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0m_message\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_reply_from_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_sec\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     41\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/google/colab/_message.py\u001b[0m in \u001b[0;36mread_reply_from_input\u001b[0;34m(message_id, timeout_sec)\u001b[0m\n\u001b[1;32m    100\u001b[0m         reply.get('colab_msg_id') == message_id):\n\u001b[1;32m    101\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;34m'error'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 102\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mMessageError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreply\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'error'\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[0m\u001b[1;32m    103\u001b[0m       \u001b[0;32mreturn\u001b[0m \u001b[0mreply\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    104\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mMessageError\u001b[0m: RangeError: Maximum call stack size exceeded."
          ]
        }
      ],
      "source": [
        "# Assistance for students in Singing and Music Aesthetics (ASMA) 2022\n",
        "# Version 2\n",
        "# Research Team:\n",
        "# Anastasia Georgaki (Coordinator)\n",
        "# Areti Andreopoulou, Iakovos Steinhauer, Vangelis Angelakis, Sofia Stavropoulou, Natalia Kotsani, Giorgos Dedousis, Kostas Katsantonis\n",
        "# Author: Natalia Kotsani\n",
        "\n",
        "!pip install praat-parselmouth\n",
        "import parselmouth\n",
        "import parselmouth\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import struct\n",
        "from scipy import signal as sg\n",
        "\n",
        "from google.colab import files\n",
        "\n",
        "uploaded = files.upload()\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "  print('User uploaded file'.format(\n",
        "      name=fn, length=len(uploaded[fn])))\n",
        "\n",
        "sns.set()\n",
        "snd = parselmouth.Sound('F0.wav')\n",
        "\n",
        "def draw_spectrogram(spectrogram, dynamic_range=70):\n",
        "    X, Y = spectrogram.x_grid(), spectrogram.y_grid()\n",
        "    sg_db = 10 * np.log10(spectrogram.values)\n",
        "    plt.pcolormesh(X, Y, sg_db, vmin=sg_db.max() - dynamic_range, cmap='afmhot')\n",
        "    plt.ylim([spectrogram.ymin, spectrogram.ymax])\n",
        "    plt.xlabel(\"time [s]\")\n",
        "    plt.ylabel(\"frequency [Hz]\")\n",
        "\n",
        "def draw_pitch(pitch):\n",
        "    pitch_values = pitch.selected_array['frequency']\n",
        "    pitch_values[pitch_values==0] = np.nan\n",
        "    plt.plot(pitch.xs(), pitch_values, 'o', markersize=5, color='w')\n",
        "    plt.plot(pitch.xs(), pitch_values, 'o', markersize=2)\n",
        "    plt.grid(False)\n",
        "    plt.ylim(0, pitch.ceiling)\n",
        "    plt.ylabel(\"fundamental frequency [Hz]\")\n",
        "\n",
        "pitch = snd.to_pitch()\n",
        "pre_emphasized_snd = snd.copy()\n",
        "pre_emphasized_snd.pre_emphasize()\n",
        "spectrogram = pre_emphasized_snd.to_spectrogram(window_length=0.03, maximum_frequency=8000)\n",
        "plt.figure()\n",
        "draw_spectrogram(spectrogram)\n",
        "plt.twinx()\n",
        "draw_pitch(pitch)\n",
        "plt.xlim([snd.xmin, snd.xmax])\n",
        "plt.savefig('f0.png')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Vowel Map"
      ],
      "metadata": {
        "id": "Kbamhj5yZkAJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. Select Button: Choose Files\n",
        "2. Select a file with a filename \"A1.wav\", \"A2.wav\", ..."
      ],
      "metadata": {
        "id": "pu17m3zuGb-O"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Assistance for students in Singing and Music Aesthetics (ASMA) 2022\n",
        "# Version 2\n",
        "# Research Team:\n",
        "# Anastasia Georgaki (Coordinator)\n",
        "# Areti Andreopoulou, Iakovos Steinhauer, Vangelis Angelakis, Sofia Stavropoulou, Natalia Kotsani, Giorgos Dedousis, Kostas Katsantonis\n",
        "# Author: Natalia Kotsani\n",
        "\n",
        "!pip install praat-parselmouth\n",
        "import parselmouth\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import struct\n",
        "from scipy import signal as sg\n",
        "from parselmouth.praat import call\n",
        "import statistics\n",
        "import os\n",
        "from pathlib import Path\n",
        "from google.colab import files\n",
        "\n",
        "def measureFormants(f0min, f0max, p):\n",
        "    snd = parselmouth.Sound(p)\n",
        "    pitch = call(snd, \"To Pitch (cc)\", 0, f0min, 15, 'no', 0.03, 0.45, 0.01, 0.35, 0.14, f0max)\n",
        "    pointProcess = call(snd, \"To PointProcess (periodic, cc)\", f0min, f0max)\n",
        "\n",
        "    formants = call(snd, \"To Formant (burg)\", 0.1, 5, 5500, 0.025, 30)\n",
        "    numPoints = call(pointProcess, \"Get number of points\")\n",
        "\n",
        "    f1_list = []\n",
        "    f2_list = []\n",
        "    f3_list = []\n",
        "    f4_list = []\n",
        "\n",
        "    for point in range(0, numPoints):\n",
        "        point += 1\n",
        "        t = call(pointProcess, \"Get time from index\", point)\n",
        "        f1 = call(formants, \"Get value at time\", 1, t, 'Hertz', 'Linear')\n",
        "        f2 = call(formants, \"Get value at time\", 2, t, 'Hertz', 'Linear')\n",
        "        f1_list.append(f1)\n",
        "        f2_list.append(f2)\n",
        "    \n",
        "    f1_list = [f1 for f1 in f1_list if str(f1) != 'nan']\n",
        "    f2_list = [f2 for f2 in f2_list if str(f2) != 'nan']\n",
        "\n",
        "    f1_mean = statistics.mean(f1_list)\n",
        "    f2_mean = statistics.mean(f2_list)\n",
        "\n",
        "    return (f1_mean, f2_mean)\n",
        "\n",
        "uploaded = files.upload()\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "  print('User uploaded file'.format(\n",
        "      name=fn, length=len(uploaded[fn])))\n",
        "\n",
        "path='/content/'\n",
        "\n",
        "files = [f for f in os.listdir(path) if os.path.isfile(os.path.join(path, f))]\n",
        "x=[]\n",
        "y=[]\n",
        "n=[]\n",
        "l=[\"A\", \"E\", \"I\", \"O\", \"U\", \"Α\", \"Ε\", \"Ι\", \"Ο\", \"Υ\"]\n",
        "\n",
        "for f in files:\n",
        "    filename = Path(f).stem\n",
        "    for i in l:\n",
        "      if i in filename:\n",
        "        f1,f2=measureFormants(100, 2000, f)\n",
        "        x.append(f1)\n",
        "        y.append(f2)\n",
        "        n.append('   '+filename)\n",
        "volume = 20\n",
        "fig, ax = plt.subplots()\n",
        "ax.scatter(y, x, s=volume, alpha=0.5, color='purple')\n",
        "plt.gca().invert_xaxis()\n",
        "plt.gca().invert_yaxis()\n",
        "plt.xlabel(\"F2\")\n",
        "plt.ylabel(\"F1\")\n",
        "plt.title(\"VOWELMAP\")\n",
        "for i, txt in enumerate(n):\n",
        "    ax.annotate(txt, (y[i], x[i]))\n"
      ],
      "metadata": {
        "id": "cXpBkPG_Zrfl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 84
        },
        "outputId": "479d2929-b145-4a25-802f-88a11e66deec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: praat-parselmouth in /usr/local/lib/python3.7/dist-packages (0.4.1)\n",
            "Requirement already satisfied: numpy>=1.7.0 in /usr/local/lib/python3.7/dist-packages (from praat-parselmouth) (1.21.6)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-dbce36e3-1c41-42bc-a088-71645f734bc7\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-dbce36e3-1c41-42bc-a088-71645f734bc7\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Phonetogram"
      ],
      "metadata": {
        "id": "dWVRmBqbZlzg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Assistance for students in Singing and Music Aesthetics (ASMA) 2022\n",
        "# Version 2\n",
        "# Research Team:\n",
        "# Anastasia Georgaki (Coordinator)\n",
        "# Areti Andreopoulou, Iakovos Steinhauer, Vangelis Angelakis, Sofia Stavropoulou, Natalia Kotsani, Giorgos Dedousis, Kostas Katsantonis\n",
        "# Author: Natalia Kotsani\n",
        "\n",
        "!pip install praat-parselmouth\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import struct\n",
        "import parselmouth\n",
        "from scipy import signal as sg\n",
        "from scipy.interpolate import interpolate\n",
        "from scipy.interpolate import interp1d\n",
        "import os\n",
        "from pathlib import Path\n",
        "import sys\n",
        "from matplotlib import ticker\n",
        "\n",
        "sns.set()\n",
        "path='/content/'\n",
        "files = [f for f in os.listdir(path) if os.path.isfile(os.path.join(path, f))]\n",
        "for f in files:\n",
        "  if not f.startswith('.'):\n",
        "    filename = Path(f).stem\n",
        "    snd = parselmouth.Sound(path+filename+'.wav')\n",
        "    pitch = snd.to_pitch(pitch_floor=75.0, pitch_ceiling=600.00, time_step=0.01)\n",
        "    intensity = snd.to_intensity(subtract_mean=True, minimum_pitch=75.0 * 2, time_step = 0.01)\n",
        "    pitch_values = pitch.selected_array['frequency']\n",
        "    pitch_values[pitch_values==0] = np.nan\n",
        "    intensity_values = (intensity.values).flatten()\n",
        "    if (pitch_values.size<intensity_values.size):\n",
        "       pitch_values = np.append(pitch_values, pitch_values[pitch_values.size-1])\n",
        "    if (pitch_values.size>intensity_values.size):\n",
        "       intensity_values = np.append(intensity_values, intensity_values[intensity_values.size-1])\n",
        "    plt.plot(pitch_values, intensity_values, 'o', markersize=5, color='purple' , alpha=0.3)\n",
        "\n",
        "x = np.array([110.00, 220.00, 440.00, 880.00])\n",
        "my_xticks = ['A2','A3', 'A4','A5']\n",
        "plt.xscale('log')\n",
        "ax = plt.gca()\n",
        "ax.xaxis.set_minor_locator(ticker.NullLocator())\n",
        "ax.xaxis.set_major_formatter(ticker.ScalarFormatter())\n",
        "plt.grid(False)\n",
        "plt.xlabel(\"Fundamental Frequency [Hz]\")\n",
        "plt.ylabel(\"Intensity [dB]\")\n",
        "plt.grid(True)\n",
        "plt.xticks(x, my_xticks)\n",
        "plt.title(\"PHONETOGRAM\")\n",
        "plt.savefig('VRP')"
      ],
      "metadata": {
        "id": "REtY6ObSZr3k"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Breathiness"
      ],
      "metadata": {
        "id": "bYdkWtuvZsOQ"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "FjGq-omTZtNR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Nasality"
      ],
      "metadata": {
        "id": "KJArWfsIZtun"
      }
    }
  ]
}