Four experiments examined the effects of language characteristics on voice identification. In Experiment 1, monolingual English listeners identified bilinguals' voices much better when they spoke English than when they spoke German. The opposite outcome was found in Experiment 2, in which the listeners were monolingual in German. In Experiment 3, monolingual English listeners also showed better voice identification when bilinguals spoke a familiar language (English) than when they spoke an unfamiliar one (Spanish). However, English-Spanish bilinguals hearing the same voices showed a different pattern, with the English-Spanish difference being statistically eliminated. Finally, Experiment 4 demonstrated that, for English-dominant listeners, voice recognition deteriorates systematically as the passage being spoken is made less similar to English by rearranging words, rearranging syllables, and reversing normal text. Taken together, the four experiments confirm that language familiarity plays an important role in voice identification.
In recent years there has been notable interest in additive models of sensory integration. Binaural additivity has emerged as a main hypothesis in the loudness-scaling literature and has recently been asserted by authors using an axiomatic approach to psychophysics. Restrictions of the range of stimuli used in the majority of former experiments, and inherent weaknesses of the axiomatic study by Levelt, Riemersma, and Bunt (1972) are discussed as providing reasons for the present investigation. A limited binaural additivity (LBA) model is proposed that assumes contralateral binaural inhibition for interaural intensity differences that exceed a critical level. Experimental data are reported for 12 subjects in a loudness-matching task designed to test the axioms of cancellation and of commutativity, both necessary to the existence of strict binaural additivity. In a 2 X 2 design, frequencies of 200 Hz and 2 kHz were used, and mean intensity levels were 20 dB apart. Additivity was found violated in 33 out of 48 possible tests. The LBA model is shown to predict the systematic nonadditivity in the loudness judgments and to conform to results from other studies.
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