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thebishorup/NLTK -- Real Time Sentiment Analysis of a Phone Call.ipynb

Created July 8, 2020 05:07
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NLTK -- Real Time Sentiment Analysis of a Phone Call.ipynb
{
"cells": [
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "!pip install textblob\n!pip install nltk",
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": "Collecting textblob\n Using cached textblob-0.15.3-py2.py3-none-any.whl (636 kB)\nRequirement already satisfied: nltk>=3.1 in d:\\anaconda\\lib\\site-packages (from textblob) (3.4.5)\nRequirement already satisfied: six in c:\\users\\user\\appdata\\roaming\\python\\python37\\site-packages (from nltk>=3.1->textblob) (1.12.0)\nInstalling collected packages: textblob\nSuccessfully installed textblob-0.15.3\nRequirement already satisfied: nltk in d:\\anaconda\\lib\\site-packages (3.4.5)\nRequirement already satisfied: six in c:\\users\\user\\appdata\\roaming\\python\\python37\\site-packages (from nltk) (1.12.0)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "import nltk",
"execution_count": 3,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "nltk.download('punkt')",
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": "[nltk_data] Downloading package punkt to\n[nltk_data] C:\\Users\\User\\AppData\\Roaming\\nltk_data...\n[nltk_data] Package punkt is already up-to-date!\n",
"name": "stderr"
},
{
"output_type": "execute_result",
"execution_count": 4,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "nltk.download('averaged_perceptron_tagger')",
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"text": "[nltk_data] Downloading package averaged_perceptron_tagger to\n[nltk_data] C:\\Users\\User\\AppData\\Roaming\\nltk_data...\n[nltk_data] Unzipping taggers\\averaged_perceptron_tagger.zip.\n",
"name": "stderr"
},
{
"output_type": "execute_result",
"execution_count": 6,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "nltk.download('brown')",
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"text": "[nltk_data] Downloading package brown to\n[nltk_data] C:\\Users\\User\\AppData\\Roaming\\nltk_data...\n[nltk_data] Unzipping corpora\\brown.zip.\n",
"name": "stderr"
},
{
"output_type": "execute_result",
"execution_count": 14,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "nltk.download()",
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"text": "showing info https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml\n",
"name": "stdout"
},
{
"output_type": "execute_result",
"execution_count": 7,
"data": {
"text/plain": "True"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from textblob import TextBlob as blob",
"execution_count": 8,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb = blob('Hello world!')",
"execution_count": 9,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb",
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 10,
"data": {
"text/plain": "TextBlob(\"Hello world!\")"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb.tags",
"execution_count": 12,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 12,
"data": {
"text/plain": "[('Hello', 'NNP'), ('world', 'NN')]"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb.noun_phrases",
"execution_count": 15,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 15,
"data": {
"text/plain": "WordList(['hello'])"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb.sentiment",
"execution_count": 16,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 16,
"data": {
"text/plain": "Sentiment(polarity=0.0, subjectivity=0.0)"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb = blob('This is fun doing this NLP.')",
"execution_count": 19,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tb.sentiment",
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 20,
"data": {
"text/plain": "Sentiment(polarity=0.3, subjectivity=0.2)"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Real Time Voice Recording"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "import speech_recognition as sr",
"execution_count": 21,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "r = sr.Recognizer()",
"execution_count": 22,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "with sr.Microphone() as source:\n print('Say something ...')\n \n audio = r.listen(source, timeout = 2)\n \n try:\n text = r.recognize_google(audio)\n tb = blob(text)\n print(text)\n print(tb.sentiment)\n except:\n print('Sorry, try again ...')",
"execution_count": 26,
"outputs": [
{
"output_type": "stream",
"text": "Say something ...\nit was fantastic game\nSentiment(polarity=0.0, subjectivity=0.65)\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "iteration = 10\nindex = 0\n\nwhile (index < iteration):\n with sr.Microphone() as source:\n print('Say something ...')\n\n audio = r.listen(source, timeout = 2)\n\n try:\n text = r.recognize_google(audio)\n tb = blob(text)\n print(text)\n print(tb.sentiment)\n except:\n print('Sorry, try again ...')\n\n index = index + 1",
"execution_count": 28,
"outputs": [
{
"output_type": "stream",
"text": "Say something ...\n",
"name": "stdout"
},
{
"output_type": "error",
"ename": "WaitTimeoutError",
"evalue": "listening timed out while waiting for phrase to start",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mWaitTimeoutError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-28-a3c2e0c1349c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Say something ...'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[0maudio\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlisten\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msource\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mD:\\Anaconda\\lib\\site-packages\\speech_recognition\\__init__.py\u001b[0m in \u001b[0;36mlisten\u001b[1;34m(self, source, timeout, phrase_time_limit, snowboy_configuration)\u001b[0m\n\u001b[0;32m 616\u001b[0m \u001b[0melapsed_time\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[0mseconds_per_buffer\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 617\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mtimeout\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0melapsed_time\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 618\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mWaitTimeoutError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"listening timed out while waiting for phrase to start\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 619\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 620\u001b[0m \u001b[0mbuffer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msource\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstream\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msource\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCHUNK\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mWaitTimeoutError\u001b[0m: listening timed out while waiting for phrase to start"
]
}
]
},
{
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"trusted": true
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