Investigating Perceptual Biases, Data Reliability, and Data Discovery in a Methodology for Collecting Speech Errors From Audio Recordings

Alderete, John; Davies, Monica

doi:10.1177/0023830918765012

Cited by 17 publications

(31 citation statements)

References 77 publications

(122 reference statements)

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“…The methods used to collect errors can be characterized with four methodological decisions and practices (see Alderete & Davies (2018) for a more detailed explanation of these methods). First, speech errors were collected primarily from audio recordings of natural conversations.…”

Section: Methodsmentioning

confidence: 99%

“…We do this by both reviewing the empirical generalizations that characterize regularity in sublexical speech errors, and also by contributing new evidence on regularity in English speech errors. In particular, we will investigate phonological regularity in the Simon Fraser University Speech Error Database (SFUSED), a database of naturalistic speech errors collected in a way that is demonstrably less prone to methodological problems found in prior studies (Alderete & Davies, 2018). It turns out that these problems have had an effect on the characterization of phonological regularity, and so our revised characterization of regularity informs the models designed to account for it.…”

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confidence: 99%

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Phonological regularity, perceptual biases, and the role of phonotactics in speech error analysis

Alderete

Tupper

2018

WIRES Cognitive Science

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Speech errors involving manipulations of sounds tend to be phonologically regular in the sense that they obey the phonotactic rules of well-formed words. We review the empirical evidence for phonological regularity in prior research, including both categorical assessments of words and regularity at the granular level involving specific segments and contexts. Since the reporting of regularity is affected by human perceptual biases, we also document this regularity in a new data set of 2,228 sublexical errors that was collected using methods that are demonstrably less prone to bias. These facts validate the claim that sound errors are overwhelmingly regular, but the new evidence suggests speech errors admit more phonologically ill-formed words than previously thought. Detailed facts of the phonological structure of errors, including this revised standard, are then related to model assumptions in contemporary theories of phonological encoding. This article is categorized under: Linguistics > Linguistic Theory Linguistics > Computational Models of Language Psychology > Language.

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Section: Methodsmentioning

confidence: 99%

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confidence: 99%

Phonological regularity, perceptual biases, and the role of phonotactics in speech error analysis

Alderete

Tupper

2018

WIRES Cognitive Science

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“…Word retrieval failures and speech errors can occur at any one of these points during the spread of activation (e.g., a semantically related word may inadvertently receive more activation than the target word, resulting in a “semantic” error). Examination of such retrieval failures can provide insight into language processing and the structure of the mental lexicon, as errors do not occur randomly (Baars, 1992; Fay & Cutler, 1977); however, word retrieval failures and speech errors are infrequent in daily communication of typical adults, even when experimentally induced in laboratory settings (but see Alderete & Davies, 2019; Vitevitch et al, 2015 for methods to overcome this issue). Hence, researchers have often relied on word retrieval failures and speech errors from clinical populations, such as persons with aphasia, to provide a rich data source of word retrieval errors.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Interplay of Semantics and Phonology During Failures of Word Retrieval by People With Aphasia Using a Multiplex Lexical Network

2020

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Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental lexicon. Network measures at different levels of analysis (degree, network distance, and closeness centrality) were used to investigate the influence of network structure on picture naming accuracy and errors by people with Anomic, Broca's, Conduction, and Wernicke's aphasia. Our results reveal that word retrieval is influenced by the multiplex lexical network structure in at least two ways—(a) the accuracy of production and error type on incorrect productions were influenced by the degree and closeness centrality of the target word, and (b) error type also varied in terms of network distance between the target word and produced error word. Taken together, the analyses demonstrate that network science techniques, particularly the use of the multiplex lexical network to simultaneously represent semantic and phonological relationships among words, reveal how the structure of the mental lexicon influences language processes beyond traditionally examined psycholinguistic variables. We propose a framework for how the multiplex lexical network approach allows for understanding the influence of mental lexicon structure on word retrieval processes, with an eye toward a better understanding of the nature of clinical impairments, like aphasia.

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“…The corpus thus reflects a better sample of the true population of speech errors than other studies that do not use audio recordings and do not use pairs of trained listeners. As documented in Alderete and Davies (2018), prior studies have detection rates (an error on average every 5 to 6 minutes) that undershoot our detection rates by a wide margin. Our corpus also has a relatively low rate of uncommon but highly salient errors, like sound exchanges, and higher rates of phonotactic violations, which are further indicators of higher data reliability (Alderete & Tupper, 2018).…”

Section: The Corpus: Sfused Cantonese 10mentioning

confidence: 74%

“…This latter corpus is reported to have 13 whole syllable errors, which is 0.36% of all sound errors, far lower than Chen's estimate for Mandarin. While it could be the case that Mandarin and English simply have different rates of syllable errors, recall that speech error data collection is plagued with methodological problems (Alderete & Davies, 2018;Ferber, 1995), and so it seems more prudent to first understand why the Chen corpus (2000) has such a low rate of sound errors.…”

Section: 4mentioning

confidence: 99%

Tone slips in Cantonese: Evidence for early phonological encoding

Alderete¹

2019

Preprint

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This article examines speech errors in Cantonese with the aim of fleshing out a larger speech production architecture for encoding phonological tone. A corpus was created by extracting 2,462 speech errors, including 668 tone errors, from audio recordings of natural conversations. The structure of these errors was then investigated in order to distinguish two contemporary approaches to tone in speech production. In the tonal frames account, tone is encoded like metrical stress, represented in abstract structural frames for a word. Because tone cannot be mis-selected in tonal frames, tone errors are expected to be rare and non-contextual, as observed with stress. An alternative is that tone is actively selected in phonological encoding like phonological segments. This approach predicts that tone errors will be relatively common and exhibit the contextual patterns observed with segments, like perseveration and anticipation. In our corpus, tone errors are the second most common type of error, and the majority of errors exhibit contextual patterns that parallel segmental errors. Building on prior research, a two-stage model of phonological tone encoding is proposed, following the patterns seen in tone errors: Tone is phonologically selected concurrently with segments, but then sequentially assigned after segments to a syllable.

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Investigating Perceptual Biases, Data Reliability, and Data Discovery in a Methodology for Collecting Speech Errors From Audio Recordings

Cited by 17 publications

References 77 publications

Phonological regularity, perceptual biases, and the role of phonotactics in speech error analysis

Phonological regularity, perceptual biases, and the role of phonotactics in speech error analysis

Quantifying the Interplay of Semantics and Phonology During Failures of Word Retrieval by People With Aphasia Using a Multiplex Lexical Network

Tone slips in Cantonese: Evidence for early phonological encoding

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