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This paper proposes a new non-intrusive measure for objective speech quality assessment in telephony applications and evaluates its performance. The measure is based on estimating perception-based objective auditory distances between voiced parts of the degraded speech under test and an appropriately formulated artificial reference model of clean speech signals. The reference model is extracted from one or many pre-formulated speech reference books. The reference books are formed by optimally clustering large number of parametric speech vectors extracted from a database of clean speech signals, using an efficient K dimensional tree structure. The measured auditory distances are then mapped into objective listening quality scores. Reported evaluation results show that the proposed measure offers sufficiently accurate and low-complexity assessment method of speech quality, making it suitable for real time applications.