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Sentiment analysis on formatted text

In this exercise, you'll calculate the sentiment on the customer channel of call_2.wav (file).

You've split the customer channel and saved it to call_2_channel_2.wav (file).

But from your experience with sentiment analysis, you know it can change sentence to sentence.

To calculate it sentence to sentence, you split the split using NLTK's sent_tokenize() module.

But transcribe_audio() doesn't return sentences. To try sentiment anaylsis with sentences, you've tried a paid API service to get call_2_channel_2_paid_api_text which has sentences.

This exercise is part of the course

Spoken Language Processing in Python

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

from nltk.sentiment.vader import SentimentIntensityAnalyzer

# Create SentimentIntensityAnalyzer instance
sid = SentimentIntensityAnalyzer()

# Transcribe customer channel of call 2
call_2_channel_2_text = transcribe_audio(____)

# Display text and sentiment polarity scores
print(call_2_channel_2_text)
print(sid.____(call_2_channel_2_text))
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