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My son will be a graduate student this fall working toward a Ph. He reads Kafka for fun. My daughter has a graduate degree in education and teaches seventh-grade English. She reads Y. We average a book a month and over the past year have explored a variety of genres including essays, biography, literary fiction and young adult.

Match of the Day (novel) | Tardis | Fandom

The most successful selections have been fiction. My turn is up in May. Do you have any suggestions of a page turner that will also generate a good discussion among such a disparate group of avid readers? At first I thought I should steer you away from fictional family dramas. Then I reconsidered. You sound very well adjusted.

The experiment ran on PsychoPy version 1. The study used the same static faces, dynamic faces, and voices as Smith et al. One of the three videos was used to create static pictures of faces. The static picture for each talker was the first frame of the video. Another of the three video files was used to construct the dynamic stimuli by muting the sound.

This is wider than the normal range of human hearing Feinberg et al. Four versions of the experiment were created, so that trials could be constructed using different combinations of stimuli. Each version consisted of 12 trials in total, and each trial featured three stimuli. The position of the same-identity other-modality stimulus at test Position 1 or 2 was also randomly and equally varied.

None of the faces or voices appeared more than once in each experimental version. Each of the four versions was used for the between-subjects manipulation of facial stimuli static or dynamic , so in total there were eight versions of the experiment. In the dynamic facial stimulus condition, participants were accurately informed that the face and the voice were saying different sentences, to prevent the use of speech-reading Kamachi et al.

The participants completed two counterbalanced experimental blocks. The procedure is illustrated in Fig. First, participants received a practice trial, followed by six randomly ordered trials. In one block of trials, participants saw a face first. After a 1-s gap, they heard the first voice. In the other block of trials, participants heard a voice first, and then saw two faces, presented one after the other. The procedure used in Experiment 1. All data were analyzed using multilevel models so that both participants and stimuli could be treated as random effects.

The random effects were fully crossed; every participant encountered all 36 stimuli 18 faces, 18 voices in each version of the experiment. Multilevel modeling avoids aggregating data see Smith et al. Accordingly, multilevel modeling was the most appropriate analysis, because it takes into account the variability associated with individual performance and different stimuli.

The variance associated with stimuli may be particularly important when investigating face—voice matching. Disregarding this source of variance would risk the ecological fallacy see Robinson, , by falsely assuming that the observed patterns for participant means also occur at the level of individual trials. Matching accuracy was analyzed using multilevel logistic regression with the lme4, version 1. This is the same method of analysis used in Smith et al.

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Four nested models were compared, all fitted using restricted maximum likelihood, and with accuracy 0 or 1 as the dependent variable. The first model included a single intercept; the second included the main effects of each factor Order, Position, and Facial Stimulus Type. The third added the two-way interactions, and the final model included the three-way interaction. This method of analysis allowed us to test for individual effects in a way similar to traditional analysis of variance ANOVA.

However, as F tests derived from multilevel models tend not to be accurate, we report the likelihood ratio tests provided by lme4. These are more robust and are obtained by dropping each effect in turn from the appropriate model e.

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Table 1 shows the likelihood chi-square statistic G 2 and p value associated with dropping each effect. Table 1 also reports the coefficients and standard errors on a log odds scale for each effect in the full three-way interaction model. Variability for the first stimulus in each trial the voice in the A—V condition, and the face in the V—A condition was modeled separately from the foil stimulus.

The random effect for the first stimuli captures the variability of both faces and voices, because corresponding faces and voices are highly correlated. For foils we modeled separate random effects for faces and voices, because the corresponding voice or face was never present. In the three-way model, the estimated SD of the first-stimulus random effect was.

The estimated SD for the participant effect was less than. A similar pattern held for the null model. Thus, although individual differences were negligible in this instance, a conventional by-participants analysis that did not simultaneously incorporate the variance associated with the stimuli could be extremely misleading. The main effect of position was significant, along with the three-way interaction between position, order, and facial stimulus type. The confidence intervals were obtained by simulating the posterior distributions of the cell means in R arm package, version 1.

Face—voice matching accuracy on visual—auditory panel A and auditory—visual panel B trials for sequentially presented faces and voices in a two-alternative forced choice task. The basis of the three-way interaction appears to relate to performance when the matching other-modality stimulus appears in Position 2 in the V—A condition. In that condition there was no position effect in the dynamic facial stimulus condition. Using the standard crossmodal matching task Lachs, employed in audiovisual speech perception research, in Experiment 1 we observed above-chance dynamic face—voice matching, but chance-level static face—voice matching.

Novel captures Cardiff on Match Day

Although there was no significant difference between static and dynamic face—voice matching accuracy, and although static face—voice matching was close to being above chance level, this pattern of results appears to support the conclusion that the source identity information shared by dynamic articulating faces and voices explains accurate face—voice matching.

The results are consistent with those of two previous studies Kamachi et al. The presence of a position effect in Experiment 1 additionally suggests that memory load might be hindering performance, especially in the static facial stimulus condition. In order to clarify the effect of procedural differences across previous studies, in Experiment 2 we used a modified version of the presentation procedure from Experiment 1. Experiment 2 presented two different face—voice combinations. This time, the face and voice in each combination were presented simultaneously, instead of sequentially.

By reducing the memory load, we hypothesized that matching accuracy might be higher when faces and voices were presented simultaneously, and above chance for static face—voice matching.

The methods for Experiment 2 were identical to those of Experiment 1 , with the exceptions outlined below. None of the participants had taken part in Experiment 1. The procedure used in Experiment 2 is illustrated in Fig. Participants in the V—A condition saw a face accompanied by a recording of a voice. In the A—V condition, participants heard a voice accompanied by a face, then a 1-s intervening gap, before hearing the same voice accompanied by a different face. Procedure used in Experiment 3. Face—voice matching accuracy was analyzed using the same method as in Experiment 1. Table 2 shows the likelihood chi-square statistic G 2 and p value associated with dropping each effect in turn from the appropriate model.

Matching novel face and voice identity using static and dynamic facial images

The coefficients and standard error on a log odds scale for each effect in the full three-way interaction model are also reported in Table 2. We observed a similar pattern of SD s for the random effects. The estimated SD for the participant effect was. Only the main effect of position was significant. Face—voice matching accuracy on visual—auditory panel A and auditory—visual panel B trials for simultaneously presented faces and voices in a two-alternative forced choice task.


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As is clear from Fig. There is, however, no three-way interaction. Overall, the pattern of results observed in Experiment 2 is largely similar to that observed in Experiment 1 , when all of the stimuli were presented sequentially. The participants in Experiment 2 exhibited a bias toward selecting the first face—voice combination they encountered.