Data labeling involves tagging pieces of data—such as voice recordings or text transcripts—with specific identifiers like intent, sentiment, or speaker role. These labels are crucial for training AI models to recognize patterns, understand natural language, and make accurate predictions. High-quality labeled data is key to improving performance and reliability.
