Singing Ability Assessment: Development and validation of a singing test based on item response theory and a general open-source software environment for singing data.

We describe the development of the Singing Ability Assessment (SAA) open-source test environment. The SAA captures and scores different aspects of human singing ability and melodic memory in the context of item response theory. Taking perspectives from both melodic recall and singing accuracy literature, we present results from two online experiments (N = 247; N = 910). On-the-fly audio transcription is produced via a probabilistic algorithm and scored via latent variable approaches. Measures of the ability to sing long notes indicate a three-dimensional principal components analysis solution representing pitch accuracy, pitch volatility and changes in pitch stability (proportion variance explained: 35%; 33%; 32%). For melody singing, a mixed-effects model uses features of melodic structure (e.g., tonality, melody length) to predict overall sung melodic recall performance via a composite score [R2c = .42; R2m = .16]. Additionally, two separate mixed-effects models were constructed to explain performance in singing back melodies in a rhythmic [R2c = .42; R2m = .13] and an arhythmic [R2c = .38; R2m = .11] condition. Results showed that the yielded SAA melodic scores are significantly associated with previously described measures of singing accuracy, the long note singing accuracy measures, demographic variables, and features of participants' hardware setup. Consequently, we release five R packages which facilitate deploying melodic stimuli online and in laboratory contexts, constructing audio production tests, transcribing audio in the R environment, and deploying the test elements and their supporting models. These are published as open-source, easy to access, and flexible to adapt.

The Jack and Jill Adaptive Working Memory Task: Construction, Calibration and Validation.

Visuospatial working memory (VSWM) is essential to human cognitive abilities and is associated with important life outcomes such as academic performance. Recently, a number of reliable measures of VSWM have been developed to help understand psychological processes and for practical use in education. We sought to extend this work using Item Response Theory (IRT) and Computerised Adaptive Testing (CAT) frameworks to construct, calibrate and validate a new adaptive, computerised, and open-source VSWM test. We aimed to overcome the limitations of previous instruments and provide researchers with a valid and freely available VSWM measurement tool. The Jack and Jill (JaJ) VSWM task was constructed using explanatory item response modelling of data from a sample of the general adult population (Study 1, N = 244) in the UK and US. Subsequently, a static version of the task was tested for validity and reliability using a sample of adults from the UK and Australia (Study 2, N = 148) and a sample of Russian adolescents (Study 3, N = 263). Finally, the adaptive version of the JaJ task was implemented on the basis of the underlying IRT model and evaluated with another sample of Russian adolescents (Study 4, N = 239). JaJ showed sufficient internal consistency and concurrent validity as indicated by significant and substantial correlations with established measures of working memory, spatial ability, non-verbal intelligence, and academic achievement. The findings suggest that JaJ is an efficient and reliable measure of VSWM from adolescent to adult age.

An efficient and adaptive test of auditory mental imagery.

The ability to silently hear music in the mind has been argued to be fundamental to musicality. Objective measurements of this subjective imagery experience are needed if this link between imagery ability and musicality is to be investigated. However, previous tests of musical imagery either rely on self-report, rely on melodic memory, or do not cater in range of abilities. The Pitch Imagery Arrow Task (PIAT) was designed to address these shortcomings; however, it is impractically long. In this paper, we shorten the PIAT using adaptive testing and automatic item generation. We interrogate the cognitive processes underlying the PIAT through item response modelling. The result is an efficient online test of auditory mental imagery ability (adaptive Pitch Imagery Arrow Task: aPIAT) that takes 8 min to complete, is adaptive to participant's individual ability, and so can be used to test participants with a range of musical backgrounds. Performance on the aPIAT showed positive moderate-to-strong correlations with measures of non-musical and musical working memory, self-reported musical training, and general musical sophistication. Ability on the task was best predicted by the ability to maintain and manipulate tones in mental imagery, as well as to resist perceptual biases that can lead to incorrect responses. As such, the aPIAT is the ideal tool in which to investigate the relationship between pitch imagery ability and musicality.