{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "35367849-a425-404c-bbbd-d8d7138f1838",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "\n",
    "with open('../speech.txt','r') as result:\n",
    "    r = result.read()\n",
    "    \n",
    "r = r.replace('<span class=\"interim\"></span>','').replace('\\n','. ')\n",
    "\n",
    "l=nltk.word_tokenize(r)\n",
    "pos = nltk.pos_tag(l)\n",
    "\n",
    "html = ''\n",
    "for x in pos:\n",
    "    if x[0] == '.':\n",
    "        html += \"<span class='dot'>.<span><br> \"\n",
    "    else:\n",
    "        html += \"<span class='\"+x[1]+\"'> \"+x[0]+\"<span>\"\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0d1737d0-cda2-4208-9585-487ef809bdff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"<span class='CC'>and<span> <span class='RB'>again<span> <span class='VBP'>are<span> <span class='PRP'>we<span> <span class='VBP'>are<span> <span class='dot'>.<span><br> <span class='NN'>let<span> <span class='POS'>'s<span> <span class='VB'>see<span> <span class='IN'>if<span> <span class='PRP'>it<span> <span class='VBZ'>works<span> <span class='RB'>again<span> <span class='IN'>with<span> <span class='DT'>these<span> <span class='JJ'>fantastic<span> <span class='NN'>xt500<span> <span class='dot'>.<span><br> \""
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "cfe7aecd-bcff-4e3b-81c2-0622434cf62b",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('index.html','w') as index:\n",
    "    index.write(html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "8d2195b3-dc7a-4cdc-b599-5570766df12d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "02f79b41-8238-4fa1-9530-a84b5069bce0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6e3cf8e-3493-463b-807a-89342e7c8731",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac322fc4-db27-42a3-aef0-ac0fbe3e26fb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e02a152-1c3c-4e2c-b1aa-1a1f3172810c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "264c688c-aba4-4cf5-8f6d-b9b35c3a0969",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}