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.
Este ejercicio forma parte del curso
Spoken Language Processing in Python
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
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))