Year: 2025
Type: conference-paper
Abstract: We introduce BANC, a neural binaural audio codec designed for efficient speech compression in single and two-speaker scenarios while preserving the spatial location information of each speaker. Our key contributions are as follows: 1) The ability of our proposed model to compress and decode overlapping speech. 2) A novel architecture that compresses speech content and spatial cues separately, ensuring the preservation of each speaker’s spatial context after decoding. 3) BANC’s proficiency in reducing the bandwidth required for compressing binaural speech by 48% compared to compressing individual binaural channels. In our evaluation, we employed speech enhancement, room acoustics, and perceptual metrics to assess the accuracy of BANC’s clean speech and spatial cue estimates.
Authors: Anton Ratnarajah, Shi-Xiong Zhang, Dong Yu
Institution: University of Maryland, College Park
Language: English
Topic: Speech and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4408347294