Best APIs for Sentiment Analysis in 2022

Sentiment Analysis is a technique used in Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) to detect the sentiment of specific speech segments or text. It works by outputting a number between -1 and 1, representing negative, neutral, or positive sentiments. The field has seen significant advancements due to machine learning and deep learning research. Sentiment Analysis is used in various industries for tasks such as customer service analysis, virtual meeting sentiment tracking, and product improvement. Some popular APIs for Sentiment Analysis include Twinword, AssemblyAI, IBM Watson, Amazon Comprehend, and Google Cloud Natural Language API. Limitations of current models include the inability to accurately detect more nuanced sentiments and the lack of audio-specific datasets for training.