11_check_sync_accuracy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "11f634da-be87-4354-8b76-c31f8231aba6",
   "metadata": {},
   "source": [
    "# BPSD: Evaluate Synchronization Accuracy\n",
    "\n",
    "- Measure Positions from two different sources:\n",
    "- Manual measure annotations from Kempff recordings (WK64) transferred via audio-audio synchronization\n",
    "- Measure positions from score transferred via score-audio sync\n",
    "\n",
    "Johannes Zeitler (johannes.zeitler@audiolabs-erlangen.de), 2024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aff7a833-7787-40c0-878f-892373c894f0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from itertools import groupby\n",
    "import scipy\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "606906d6-d329-49e6-9313-14516f4937f4",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pieces = [f.split(\".\")[0] for f in os.listdir(os.path.join(\"../\", \"1_Audio\")) if \".wav\" in f]\n",
    "\n",
    "pieces.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "571778ab-daab-4fe9-ab4e-34a8a114dd3a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "dir_measures_sync = os.path.join(\"../\", \"2_Annotations\", \"ann_audio_measure\")\n",
    "dir_ann_audio_note = os.path.join(\"../\", \"4_misc\", \"ann_audio_note_noAnchor\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b45d7d6f-542b-4d42-8841-ef5b671853dd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8dde66a03de44fe1ab60d2ed63b585f8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/352 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pieces_error_transc_finetuned = {}\n",
    "\n",
    "for piece in tqdm(pieces):\n",
    "    all_absError = []\n",
    "    measures = pd.read_csv(os.path.join(dir_measures_sync, \"%s.csv\"%(piece)), sep=\";\")\n",
    "    \n",
    "    noteIn = pd.read_csv(os.path.join(dir_ann_audio_note, \"%s.csv\"%(piece)), sep=\";\")\n",
    "    \n",
    "    \n",
    "    start_pairs = [[start_m, start_s] for start_m, start_s in zip(noteIn.start_meas, noteIn.start)]\n",
    "    start_pairs_unique = np.array([pair for pair,_ in groupby(start_pairs)])\n",
    "    start_pairs_unique.sort(axis=0)        \n",
    "\n",
    "    meas_to_time_annot = scipy.interpolate.interp1d(start_pairs_unique[:,0], start_pairs_unique[:,1], \n",
    "                                              kind='linear', bounds_error=False, fill_value='extrapolate')\n",
    "    \n",
    "    \n",
    "    \n",
    "    measures[\"timeFromNote\"] = meas_to_time_annot(measures.measure)\n",
    "    \n",
    "    \n",
    "    measures[\"error\"] = measures.time - measures.timeFromNote\n",
    "    measures[\"squaredError\"] = measures.error**2\n",
    "    measures[\"absError\"] = np.abs(measures.error)\n",
    "    \n",
    "    isNote = []\n",
    "    \n",
    "    for _, row in measures.iterrows():\n",
    "        if min(np.abs(noteIn.start_meas-row.measure)) < 1e-2: isNote.append(True)\n",
    "        else: isNote.append(False)\n",
    "        \n",
    "    measures[\"isNote\"] = isNote\n",
    "    \n",
    "    MSE = np.mean(measures.squaredError[:-1])\n",
    "    RMSE = np.sqrt(MSE)\n",
    "    \n",
    "    MAE = np.mean(measures.absError[:-1])\n",
    "    \n",
    "    MSE_isNote = np.mean(measures.squaredError[:-1][np.where(measures.isNote[:-1])[0]])\n",
    "    RMSE_isNote = np.sqrt(MSE_isNote)\n",
    "    \n",
    "    MAE_isNote = np.mean(measures.absError[:-1][np.where(measures.isNote[:-1])[0]])\n",
    "    \n",
    "    grossError = np.mean(measures.absError[:-1] > 0.07)\n",
    "    \n",
    "    grossError_isNote = np.mean(measures.absError[:-1][np.where(measures.isNote[:-1])[0]] > 0.07)\n",
    "    \n",
    "    \n",
    "    for err in measures.absError:\n",
    "        all_absError.append(err)\n",
    "\n",
    "    #break\n",
    "\n",
    "   \n",
    "    pieces_error_transc_finetuned[piece] = {\"MSE\": MSE,\n",
    "                           \"MSE_isNote\": MSE_isNote,\n",
    "                           \"RMSE\": RMSE, \n",
    "                           \"RMSE_isNote\": RMSE_isNote,\n",
    "                           \"MAE\": MAE,\n",
    "                           \"MAE_isNote\": MAE_isNote,\n",
    "                           \"grossError\": grossError,\n",
    "                           \"grossError_isNote\": grossError_isNote,\n",
    "                           \"absErr\": [err for err in measures.absError],\n",
    "                           \"absErr_isNote\": [err for err in measures.absError[np.where(measures.isNote)[0]]]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "368883d8-46a7-4a6c-83a0-a83f0e3bd34a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "performers = list(set([p.split(\"_\")[-1] for p in pieces]))\n",
    "performers.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "700b5312-d32d-41f8-ae3f-a906de4a6970",
   "metadata": {},
   "outputs": [],
   "source": [
    "sonatas = list(set([p.split(\"_\")[1] for p in pieces]))\n",
    "sonatas.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "343e9e07-14f6-472d-a66a-569c3382fa9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "MAE_all = np.zeros((len(sonatas), len(performers)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "949ee6e8-17a4-45c5-a716-95d5b08fb146",
   "metadata": {},
   "outputs": [],
   "source": [
    "for iSon, sonata in enumerate(sonatas):\n",
    "    for iPerf, performer in enumerate(performers):\n",
    "\n",
    "        MAE_all[iSon, iPerf] = pieces_error_transc_finetuned[\"Beethoven_%s_%s\"%(sonata, performer)][\"grossError_isNote\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b42b42ad-19aa-42f7-875a-02245d0608d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x2000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,20))\n",
    "plt.imshow(MAE_all, aspect=\"auto\", interpolation=\"None\")\n",
    "plt.yticklabels = sonatas\n",
    "plt.grid()\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e7c0970e-9b55-4149-a3a1-5984471d5b97",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "absErr_performers = []\n",
    "absErr_isNote_performers = []\n",
    "for performer in performers:\n",
    "    absErr_performers.append([])\n",
    "    absErr_isNote_performers.append([])\n",
    "    \n",
    "for piece in pieces:\n",
    "    absErr = pieces_error_transc_finetuned[piece][\"absErr\"]\n",
    "    absErr_isNote = pieces_error_transc_finetuned[piece][\"absErr_isNote\"]\n",
    "\n",
    "    for i, perf in enumerate(performers):\n",
    "        if perf in piece:\n",
    "            absErr_performers[i] += absErr\n",
    "            absErr_isNote_performers[i] += absErr_isNote\n",
    "            \n",
    "for i in range(len(absErr_performers)):\n",
    "    absErr_performers[i] = np.array(absErr_performers[i])\n",
    "    absErr_isNote_performers[i] = np.array(absErr_isNote_performers[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8bcdb522-55fc-4524-9187-55b2ca5bd1e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.boxplot(absErr_performers, vert=False)\n",
    "plt.xlim([0., .06])\n",
    "plt.yticks(np.arange(len(performers))+1, performers)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "21534112-c44c-4773-bd41-7fdc1cc06d53",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.boxplot(absErr_isNote_performers, vert=False)\n",
    "plt.xlim([0., .06])\n",
    "plt.yticks(np.arange(len(performers))+1, performers)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a38a9899-2aef-418a-ab9e-a7a60af2bbcd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Version & mean & median & 95 & mean_isNote & median_isNote & 95_isNote \\\\\n",
      "AB96 & 27.82 & 18.00 & 46.00 & 18.34 & 17.00 & 40.00 \\\\\n",
      "AS35 & 24.78 & 15.00 & 54.00 & 18.17 & 13.00 & 40.33 \\\\\n",
      "DB84 & 29.08 & 19.00 & 60.00 & 19.35 & 18.00 & 54.00 \\\\\n",
      "FG58 & 22.74 & 16.00 & 41.00 & 16.72 & 14.00 & 40.00 \\\\\n",
      "FG67 & 25.07 &  9.50 & 40.00 & 17.44 &  8.29 & 40.00 \\\\\n",
      "FJ62 & 25.24 & 19.00 & 60.00 & 18.54 & 18.00 & 45.00 \\\\\n",
      "JJ90 & 23.70 & 17.00 & 43.00 & 16.01 & 16.00 & 40.00 \\\\\n",
      "MB97 & 30.03 & 20.00 & 60.00 & 20.14 & 19.67 & 47.00 \\\\\n",
      "MC22 & 27.12 & 20.00 & 63.50 & 21.16 & 20.00 & 60.00 \\\\\n",
      "VA81 & 23.99 & 16.71 & 56.00 & 17.08 & 16.00 & 41.00 \\\\\n",
      "WK64 & 20.21 & 13.00 & 40.00 & 14.47 & 11.00 & 40.00 \\\\\n",
      "all & 25.44 & 17.00 & 53.00 & 17.95 & 16.00 & 40.00 \\\\\n"
     ]
    }
   ],
   "source": [
    "print(\"Version & mean & median & 95 & mean_isNote & median_isNote & 95_isNote \\\\\\\\\")\n",
    "for i, performer in enumerate(performers):\n",
    "    print(\"%s & %5.2f & %5.2f & %5.2f & %5.2f & %5.2f & %5.2f \\\\\\\\\"%(performer, np.mean(absErr_performers[i])*1e3, np.median(absErr_performers[i])*1e3, np.sort(absErr_performers[i])[int(.95*len(absErr_performers[i]))]*1e3,\n",
    "                                                          np.mean(absErr_isNote_performers[i])*1e3, np.median(absErr_isNote_performers[i])*1e3, np.sort(absErr_isNote_performers[i])[int(.95*len(absErr_isNote_performers[i]))]*1e3))\n",
    "    \n",
    "all_absErr = np.concatenate(absErr_performers)\n",
    "all_absErr_isNote = np.concatenate(absErr_isNote_performers)\n",
    "\n",
    "print(\"%s & %5.2f & %5.2f & %5.2f & %5.2f & %5.2f & %5.2f \\\\\\\\\"%(\"all\", np.mean(all_absErr)*1e3, np.median(all_absErr)*1e3, np.sort(all_absErr)[int(.95*len(all_absErr))]*1e3,\n",
    "                                                          np.mean(all_absErr_isNote)*1e3, np.median(all_absErr_isNote)*1e3, np.sort(all_absErr_isNote)[int(.95*len(all_absErr_isNote))]*1e3))\n",
    "    "
   ]
  }
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