A phonetically based metric of sound similarity

Mielke, Jeff

doi:10.1016/j.lingua.2011.04.006

Cited by 48 publications

(52 citation statements)

References 21 publications

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“…4 Another way of defining similarity is in terms of perception. Similarity is likely evaluated by listeners on the basis of multiple sources of information, and forming a complete understanding of how people judge the similarity of two speech sounds is not trivial (see Steriade, 2001Steriade, /2008Wilson, 2006;Mielke, 2012;Cristia et al, in press). For simplicity, I take the relatively straightforward notion of mutual confusability as an approximation of perceptual similarity.…”

Section: Saltatory Phonological Alternations: a Case Of Excessive Modmentioning

confidence: 99%

Evidence for a learning bias against saltatory phonological alternations

White

2014

Cognition

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This study provides new experimental evidence that people learn phonological alternations in a biased way. Adult participants were exposed to alternations between phonetically dissimilar sounds (i.e., those differing in both voicing and manner, such as [p] and [v] By comparison, a control group of participants found it easier to learn the opposite pattern, where similar sounds alternated but dissimilar sounds did not. The results are taken as evidence that learners have a soft bias, considering alternations between perceptually similar sounds to be more likely.

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Section: Saltatory Phonological Alternations: a Case Of Excessive Modmentioning

confidence: 99%

Evidence for a learning bias against saltatory phonological alternations

White

2014

Cognition

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“…In Table 1, we show distances derived from the articulatory and acoustic measurements plotted in Figure 1, which are calculated from data reported in Mielke (2012). Naturally, the Exposure onset has a distance of zero, because it was in the training set.…”

Section: Figmentioning

confidence: 99%

“…As a first approximation, we used distance measures derived from articulatory data collected for an independent study, reported in Mielke (2012). In that study, four phonetically trained American English native talkers produced common sounds of the world's languages in three vocalic contexts (a_a, i_i, u_u).…”

Section: Linguistically Informed Distance Measuresmentioning

confidence: 99%

Similarity in the generalization of implicitly learned sound patterns

Cristià

Mielke

Daland

et al. 2013

Laboratory Phonology

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It is likely that generalization of implicitly learned sound patterns to novel words and sounds is structured by a similarity metric, but how may this metric best be captured? We report on an experiment where participants were exposed to an artificial phonology, and frequency ratings were used to probe implicit abstraction of onset statistics. Non-words bearing an onset that was presented during initial exposure were subsequently rated most frequent, indicating that participants generalized onset statistics to new non-words. Participants also rated non-words with untrained onsets as somewhat frequent, indicating generalization to onsets that had not been used during the exposure phase. While generalization could be accounted for in terms of featural distance, it was insensitive to natural class structure. Generalization to untrained sounds was predicted better by models requiring prior linguistic knowledge (either traditional distinctive features or articulatory phonetic information) than by a model based on a linguistically naïve measure of acoustic similarity.

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“…This kind of comparison enables us to identify patterns that hold generally across speakers of a given language. Statistical comparisons of RMSD values across test conditions of interest allow for an evaluation of similarity or difference between those conditions, adding to the similarity tools proposed in Mielke (2012).…”

Section: Discussionmentioning

confidence: 99%