In this project, we are going to analyze the sentiment of the call. We are first going to convert the speech to text and then analyze the sentiment using TextBlob. TextBlob is a Python library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.
NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum.
Installing nltk does not install everything in nltk. We will have to download some things separately. We are going to download punkt, averaged_perceptron_tagger and brow. nltk.download() opens a GUI by which you can view the packages which are already downloaded and even update or download new packages manually.
🔊 Watch till last for a detailed description
03:44 Installing the libraries
11:00 Real-time voice recording
16:00 Recording the voice
20:00 Analysing the output
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