Feature Extraction converts raw audio into meaningful numerical representations that machine learning models can process. Common features include Mel-frequency cepstral coefficients (MFCCs), spectrograms, and embeddings.
Feature Extraction is one of the first stages of every Voice AI pipeline. High-quality features improve speech recognition, speaker identification, emotion detection, and speech synthesis performance.