Windowing is a signal processing technique that divides continuous audio into small overlapping segments before analysis. This enables efficient extraction of speech features and reduces processing artifacts.
Voice AI systems apply Windowing during speech recognition, speaker identification, noise reduction, and audio analysis to improve model accuracy and real-time processing performance.