noise_reduction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<_io.BufferedRandom name='./reduced_noise.wav'>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "from pydub import AudioSegment\n",
    "import noisereduce as nr\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Load audio file\n",
    "sound = AudioSegment.from_file('./test2.wav', format=\"wav\")\n",
    "\n",
    "# Convert audio file to a numpy array\n",
    "samples = np.array(sound.get_array_of_samples())\n",
    "\n",
    "# Apply noise reduction\n",
    "reduced_noise = nr.reduce_noise(y=samples, sr=sound.frame_rate)\n",
    "\n",
    "\n",
    "# Plot the original and reduced audio signals\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.title(\"Original Signal\")\n",
    "plt.plot(samples)\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.title(\"Reduced Noise\")\n",
    "plt.plot(reduced_noise)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "reduced_sound = AudioSegment(\n",
    "    reduced_noise.tobytes(),\n",
    "    frame_rate=sound.frame_rate,\n",
    "    sample_width=sound.sample_width,\n",
    "    channels=sound.channels\n",
    ")\n",
    "\n",
    "# Save the reduced noise audio to a file\n",
    "reduced_sound.export(\"./reduced_noise.wav\", format=\"wav\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'d:\\\\final_year_project\\\\major_project_fe_react\\\\fastApi'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os \n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "ename": "PermissionError",
     "evalue": "[WinError 32] The process cannot access the file because it is being used by another process: 'reduced_noise.wav'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mPermissionError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32md:\\final_year_project\\major_project_fe_react\\fastApi\\test.ipynb Cell 3\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      <a href='vscode-notebook-cell:/d%3A/final_year_project/major_project_fe_react/fastApi/test.ipynb#W2sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mos\u001b[39;00m\n\u001b[0;32m      <a href='vscode-notebook-cell:/d%3A/final_year_project/major_project_fe_react/fastApi/test.ipynb#W2sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m path\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mreduced_noise.wav\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/d%3A/final_year_project/major_project_fe_react/fastApi/test.ipynb#W2sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m os\u001b[39m.\u001b[39;49mremove(\u001b[39mf\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39m{\u001b[39;49;00mpath\u001b[39m}\u001b[39;49;00m\u001b[39m'\u001b[39;49m)\n",
      "\u001b[1;31mPermissionError\u001b[0m: [WinError 32] The process cannot access the file because it is being used by another process: 'reduced_noise.wav'"
     ]
    }
   ],
   "source": [
    "import os\n",
    "path=\"reduced_noise.wav\"\n",
    "os.remove(f'{path}')\n",
    "# os.remove(\"reduced_noise.wav\")"
   ]
  }
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