Sentiment Analysis with Text and Audio Using AWS Generative AI Services: Approaches, Challenges, and Solutions

This post is co-written by Instituto de Ciência e Tecnologia Itaú (ICTi) and AWS.

Sentiment analysis has grown increasingly important in modern enterprises, providing insights into customer opinions, satisfaction levels, and potential frustrations. As interactions occur largely through text (such as social media, chat applications, and ecommerce reviews) or voice (such as call centers and telephony), organizations need robust methods to interpret these signals at scale. By accurately identifying and classifying a customer’s emotional state, companies can deliver more proactive, customized experiences, positively impacting customer satisfaction and loyalty.

Despite its strategic value, implementing comprehensive sentiment analysis solutions presents several challenges. Language ambiguity, cultural nuances, regional dialects, sarcastic expressions, and high volumes of real-time data all demand scalable and flexible architectures. Additionally, in voice-based sentiment analysis, critical features such as intonation and prosody can be lost if the audio is transcribed and treated purely as text. Amazon Web Services (AWS ...