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Audio quality assessment is critical for assessing the perceptual realism of sounds. However, the time and expense of obtaining "gold standard" human judgments limit the availability of such data. For AR&VR, good perceived sound quality and localizability of sources are among the key elements to ensure complete immersion of the user. Our work introduces SAQAM which uses a multi-task learning framework to assess listening quality (LQ) and spatialization quality (SQ) between any given pair ofarXiv:2206.12297v1 fatcat:eorn6n2m6jedbn4aym53bpu4v4