An easy way to improve scoring of memory span tasks: The edit distance, beyond "correct recall in the correct serial position"

Identifying Links Between Latent Memory and Speech Recognition Factors

OBJECTIVES

The link between memory ability and speech recognition accuracy is often examined by correlating summary measures of performance across various tasks, but interpretation of such correlations critically depends on assumptions about how these measures map onto underlying factors of interest. The present work presents an alternative approach, wherein latent factor models are fit to trial-level data from multiple tasks to directly test hypotheses about the underlying structure of memory and the extent to which latent memory factors are associated with individual differences in speech recognition accuracy. Latent factor models with different numbers of factors were fit to the data and compared to one another to select the structures which best explained vocoded sentence recognition in a two-talker masker across a range of target-to-masker ratios, performance on three memory tasks, and the link between sentence recognition and memory.

DESIGN

Young adults with normal hearing (N = 52 for the memory tasks, of which 21 participants also completed the sentence recognition task) completed three memory tasks and one sentence recognition task: reading span, auditory digit span, visual free recall of words, and recognition of 16-channel vocoded Perceptually Robust English Sentence Test Open-set sentences in the presence of a two-talker masker at target-to-masker ratios between +10 and 0 dB. Correlations between summary measures of memory task performance and sentence recognition accuracy were calculated for comparison to prior work, and latent factor models were fit to trial-level data and compared against one another to identify the number of latent factors which best explains the data. Models with one or two latent factors were fit to the sentence recognition data and models with one, two, or three latent factors were fit to the memory task data. Based on findings with these models, full models that linked one speech factor to one, two, or three memory factors were fit to the full data set. Models were compared via Expected Log pointwise Predictive Density and post hoc inspection of model parameters.

RESULTS

Summary measures were positively correlated across memory tasks and sentence recognition. Latent factor models revealed that sentence recognition accuracy was best explained by a single factor that varied across participants. Memory task performance was best explained by two latent factors, of which one was generally associated with performance on all three tasks and the other was specific to digit span recall accuracy at lists of six digits or more. When these models were combined, the general memory factor was closely related to the sentence recognition factor, whereas the factor specific to digit span had no apparent association with sentence recognition.

CONCLUSIONS

Comparison of latent factor models enables testing hypotheses about the underlying structure linking cognition and speech recognition. This approach showed that multiple memory tasks assess a common latent factor that is related to individual differences in sentence recognition, although performance on some tasks was associated with multiple factors. Thus, while these tasks provide some convergent assessment of common latent factors, caution is needed when interpreting what they tell us about speech recognition.

Characterizing correlations in partial credit speech recognition scoring with beta-binomial distributions

Partial credit scoring for speech recognition tasks can improve measurement precision. However, assessing the magnitude of this improvement with partial credit scoring is challenging because meaningful speech contains contextual cues, which create correlations between the probabilities of correctly identifying each token in a stimulus. Here, beta-binomial distributions were used to estimate recognition accuracy and intraclass correlation for phonemes in words and words in sentences in listeners with cochlear implants (N = 20). Estimates demonstrated substantial intraclass correlation in recognition accuracy within stimuli. These correlations were invariant across individuals. Intraclass correlations should be addressed in power analysis of partial credit scoring.

Great minds think alike: New measures to quantify the similarity of recalls

Given the recent interest in how memory operates in social contexts, it is more important than ever to meaningfully measure the similarity between recall sequences of different individuals. Similarity of recall sequences of different individuals has been quantified using primarily order-agnostic and some order-sensitive measures specific to memory research without agreement on any one preferred measure. However, edit distance measures have not been used to quantify the similarity of recall sequences in collaborative memory studies. In the current study, we review a broad range of similarity measures, highlighting commonalities and differences. Using simulations and behavioral data, we show that edit distances do measure a memory-relevant factor of similarity and capture information distinct from that captured by order-agnostic measures. We answer illustrative research questions which demonstrate potential applications of edit distances in collaborative and individual memory settings and reveal the unique impact collaboration has on similarity.

Should Intelligence Tests Be Speeded or Unspeeded? A Brief Review of the Effects of Time Pressure on Response Processes and an Experimental Study with Raven's Matrices

Intelligence tests are often performed under time constraints for practical reasons, but the effects of time pressure on reasoning performance are poorly understood. The first part of this work provides a brief review of major expected effects of time pressure, which includes forcing participants to skip items, convoking a mental speed factor, constraining response times, qualitatively altering cognitive processing, affecting anxiety and motivation, and interacting with individual differences. The second part presents data collected with Raven's matrices under three conditions of speededness to provide further insight into the complex effects of time pressure, with three major findings. First, even mild time pressure (with enough time available for all participants to complete the task at a leisurely pace) induced speeding throughout the whole task, starting with the very first item, and participants sped up more than was actually required. Second, time pressure came with lower confidence and poorer strategy use and a substantial decrease of accuracy (d = 0.35), even when controlling for response time at the item level-indicating a detrimental effect on cognitive processing beyond speeding. Third, time pressure disproportionately reduced response times for difficult items and participants with high ability, working memory capacity, or need for cognition, although this did not differentially affect ability estimates. Overall, both the review and empirical sections show that the effects of time pressure go well beyond forcing participants to speed or skip the last few items and make even mild time constraints inadvisable when attempting to measure maximal performance, especially for high-performing samples.