Speech or audio annotation is a crucial process for training advanced AI and machine learning models to understand and interpret human communication. It encompasses transcription, which converts speech into written text, and part-of-speech tagging to label words with their grammatical roles.

Named entity recognition (NER) identifies and categorizes specific entities like names, dates, and locations. Dialog act annotation classifies segments of conversation based on intent, such as questions or statements. Speech emotion recognition analyzes vocal tones to detect emotions, while acoustic event detection identifies background sounds or events within audio recordings. Together, these annotation techniques create rich, structured data that enable smarter, more intuitive AI systems.