## 2 Spatial Audio Quality Assessment  
The evaluation of spatial audio is a complex topic. One must be careful to define parameters that are descriptive enough to capture the essence of any given stimuli without overwhelming a listening test subject. It is necessary to consider many different aspects--for example, timbre, spatialization, naturalism and fidelity as well as the impact of listener preference. In binaural audio, the addition of HRTFs can dramatically impact a signal due to the sharp peaks and notches found in their frequency response. Previous studies have tended toward HRTF evaluation via localisation tests [9; 10; 11]. Findings have offered conflicting results as to the performance of individual HRTFs compared to non-individual measurements. Some find clear benefits [12; 13; 14] whilst others show little improvement [15]. Results often depend on the inclusion of features such as head-tracking and the type of stimuli used. More recent studies have begun to explore HRTF preference through: methods of database optimization [19]; the examination of perceptual repeatability and variability [20; 21]; and the creation of global similarity metrics [22; 23]. However, in each case, perceived spatial performance was used as a stand-alone metric for comparison. Impulsive or noisy stimuli was presented over a known trajectory and participants were asked to rate the spatial effectiveness of each sample. Considering a more general listening scenario, it is important to evaluate beyond just the spatial attributes of a rendered source [24]. In this paper, we wish to examine the impact of HRTF selection by the more general evaluation of spatial audio stimuli within a real-world context. Previous work standardised attributes for the subjective assessment of sound quality in an ITU Recommendation in 2003 [25; 26]. However, the recommendation lacks sufficient attributes for the assessment of spatial audio [7]. Early examples of subjective binaural evaluation [24; 27] lack clarity and consider only general spatial or timbral colouration. [PERSON] [28] and [PERSON] [24] introduce perception based binaural models as a measure of binaural signal quality. Similar objective metrics have been published since [29; 30]. Whilst such models are useful for monitoring authenticity, they operate by comparing a test signal to a given reference signal and as such do not directly assess a listener's Quality of Experience (QoE). Alternative work has identified comprehensive lists of attributes tailored for the perceptual evaluation of spatial audio. Whilst the processes with which these lists were compiled vary by author, all result in a similar collection of holistic terms. A brief summary follows. [PERSON] proposes a set of spatial attributes based on the Repertory Grid method in which subjects identify differences in triads of stimuli [31]. [PERSON] presents a structured method for the development of any descriptive language [32]. In an example, 12 expert listeners produce an exhaustive list of eight spatial and four timbral attributes for evaluating different spatial sound reproduction systems. [PERSON] developed the Spatial Audio Quality Inventory (SAQI) which presents a vocabulary containing all perceptual attributes [33]. It is derived from a focus group of 21 German speaking virtual acoustics experts. [PERSON] focused on the acoustics of concert halls developing a broad list of attributes from the results of an individual vocabulary profiling experiment [34]. [PERSON] examined the search terms used in online sound effect libraries and compiled a list of the most popular discriminators [35]. [PERSON] was a little more specific and identified eight qualities for describing the perceived differences between non-individual HRTF sets in binaural renderings [36]. He first followed an individual vocabulary profiling procedure, similar to [PERSON], before refining his terms through a series of focus groups.