This patent addresses a limitation of conventional acoustic echo cancellation in calls and teleconferencing: speech and background ambience are typically processed together, making it difficult to remove echo effectively while also preserving the environmental sounds that contribute to a natural and immersive communication experience. The proposed approach first separates both the far-end signal and the locally captured microphone signal into speech and noise/ambience components. It then treats these components independently, comparing far-end speech with near-end speech to remove speech echo, and far-end noise with near-end noise to remove the corresponding echoed ambience. The resulting local speech and local environmental sound are therefore estimated separately and can either be transmitted independently or recombined depending on the communication system. Neural source-separation or denoising models can be used for the initial decomposition, followed by conditioned models that determine which parts originate locally and which are echoes of the remote signal. By breaking the problem into these simpler stages, the approach is intended to make neural echo-cancellation systems easier to train while also allowing background ambience to be deliberately preserved rather than automatically suppressed, supporting more natural and potentially spatial or immersive audio communication.