Intonation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "private_outputs": true,
      "provenance": [],
      "authorship_tag": "ABX9TyO0OFGiXG8C50+ShnumsLpS",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/MK316/Myapps/blob/main/Intonation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Intonation contour: visible intonation (pitch track)"
      ],
      "metadata": {
        "id": "PiOwHuIhmfUn"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "s-mB6lyMyFr5",
        "cellView": "form"
      },
      "outputs": [],
      "source": [
        "#@markdown 📌 Run this code before you start\n",
        "%%capture\n",
        "!pip install pyqrcode gradio pandas gtts requests librosa matplotlib pydub"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown Generate speech and show intonation\n",
        "from gtts import gTTS\n",
        "from pydub import AudioSegment\n",
        "from io import BytesIO\n",
        "from IPython.display import Audio\n",
        "import librosa\n",
        "import librosa.display\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import os\n",
        "\n",
        "# Function to generate and save a WAV file\n",
        "def generate_and_save_wav(word, filename='output.wav'):\n",
        "    tts = gTTS(text=word, lang='en')\n",
        "    mp3_fp = BytesIO()\n",
        "    tts.write_to_fp(mp3_fp)\n",
        "    mp3_fp.seek(0)\n",
        "    sound = AudioSegment.from_file(mp3_fp, format=\"mp3\")\n",
        "    sound.export(filename, format=\"wav\")\n",
        "    return filename\n",
        "\n",
        "# Function to extract and plot the pitch contour\n",
        "def plot_pitch_contour(audio_file_path):\n",
        "    y, sr = librosa.load(audio_file_path, sr=None)\n",
        "    fmin = librosa.note_to_hz('C2')\n",
        "    fmax = librosa.note_to_hz('C6')\n",
        "    pitch, voiced_flag, voiced_probs = librosa.pyin(y, fmin=fmin, fmax=fmax, sr=sr)\n",
        "    pitch[~np.isfinite(pitch)] = 0\n",
        "\n",
        "    plt.figure(figsize=(14, 5))\n",
        "    librosa.display.waveshow(y, sr=sr)\n",
        "    times = librosa.times_like(pitch, sr=sr)\n",
        "    for i in range(len(pitch)):\n",
        "        if pitch[i] > 0:\n",
        "            plt.plot(times[i], pitch[i], 'ro')\n",
        "\n",
        "    plt.title('Pitch Contour')\n",
        "    plt.xlabel('Time (s)')\n",
        "    plt.ylabel('Pitch (Hz)')\n",
        "    plt.ylim(0, 350)\n",
        "    plt.show()\n",
        "\n",
        "# Get user input\n",
        "mytext = input('Type a word or sentence: ')\n",
        "\n",
        "# Generate speech and save to a WAV file\n",
        "audio_file = generate_and_save_wav(mytext)\n",
        "\n",
        "# Play the audio\n",
        "print(f\"Generated speech for: {mytext}\")\n",
        "Audio(audio_file)\n",
        "\n",
        "# Display the pitch contour\n",
        "print(f\"Pitch contour for: {mytext}\")\n",
        "plot_pitch_contour(audio_file)\n"
      ],
      "metadata": {
        "cellView": "form",
        "id": "UalGmYflpNUr"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}