Evaluating Multi-Channel Multi-Device Speech Separation Algorithms in the Wild: A Hardware-Software Solution

Abstract

Evaluation methods for multi-channel speech separation algorithms in the real world are becoming increasingly important as the number of applications involving audio assistants and hearing aid devices continues to grow. To make such evaluations easier, this paper presents a multi-microphone hardware platform, WHISPER, built specifically for this purpose and its subsequent use for evaluating speech processing algorithms. The platform can also be constructed as an ad-hoc wireless acoustic sensor network (WASN) with high synchronization precision. Using WHISPER, we describe real-world experiments where an example speech separation algorithm is applied to mixtures of varying number of talkers and signal-to-noise ratios. The results when compared with those from a simulated environment, show the usefulness of WASNs and that simulations tend to underestimate the difficulty of speech separation in real-world scenarios. This work represents an important step towards developing a hardware-software framework for evaluating speech processing algorithms in the wild.