In this paper, we introduce SPHERE (Spatial and Perceptual Human Evaluation and Rating Estimator), a multidimensional no-reference perceptual evaluation framework for binaural speech. SPHERE defines nine distinct perceptual and spatial attributes that characterize the immersive listening experience. We detail the crowdsourcing protocol and evaluation template used to collect ground-truth human ratings. To demonstrate the tractability of automating this framework, we evaluate six baseline configurations across single-branch and Siamese architectures utilizing Mel-spectrograms, complex STFTs, and pretrained spatial embeddings (PhaseCoder). Experimental results demonstrate that these baseline estimators achieve strong correlation with human subjective ratings, proving the feasibility of automated multidimensional spatial audio quality assessment.

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