Voice Separation and Pitch Correction for Electroacoustic Audio

The audio data is segmented into multiple frequency bands using filter banks, allowing independent processing of different frequency components. This segmentation enables selective application of electroacoustic effects to specific voice components while preserving background sounds, thereby improving flexibility without requiring complete reprocessing of the entire audio signal.

The patent extracts the fundamental frequency component from the voice signal using spectral analysis and pitch detection algorithms. By isolating and manipulating only the fundamental frequency components rather than the entire spectrum, the system achieves high-quality electroacoustic effects with reduced processing complexity compared to full-signal processing approaches.

The patent applies preliminary processing steps including filtering and feature extraction before neural network processing. By pre-processing the audio signal to enhance relevant features and reduce noise, the neural network requires fewer iterations and less computational power to achieve high separation quality, thereby reducing overall processing time.

The system applies neural network processing selectively to specific frequency bands and time segments where voice separation is most needed, rather than processing the entire audio signal uniformly. This partial processing approach maintains high separation quality in critical regions while significantly reducing total computational time and resource requirements.