From what I have seen you can fine tune a Bert model to detect emotions by labelling single sentences. But if the text you want to evaluate is a large script with many sentences, do I need to split the script into sentences and get a classification for each one? If I did it that way I could find the average score for each emotion for the the sentences in the script. The problem with doing it that way is the the context between sentences is lost. A context like sarcasm often means that sentences have to be connected in order to understand that it is sarcastic. I would be interested to get some advice on this.
Asked
Active
Viewed 10 times
