Combining quantitative narrative analysis and predictive modeling - an eye tracking study

As a part of a larger interdisciplinary project on Shakespeare sonnets’ reception (Jacobs et al., 2017; Xue et al., 2017), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrative Analysis (QNA). Using a machine learning- based predictive modeling approach five ‘surface’ features (word length, orthographic neighborhood density, word frequency, orthographic dissimilarity and sonority score) were detected as important predictors of total reading time and fixation probability in poetry reading. The fact that one phonological feature, i.e., sonority score, also played a role is in line with current theorizing on poetry reading. Our approach opens new ways for future eye movement research on reading poetic texts and other complex literary materials (cf. Jacobs, 2015c)

Visual to auditory silent matching task in adults who do and do not stutter

textThe purpose of the present study was to investigate the role of phonological working memory in adults who do and do not stutter through a visual to auditory silent matching task. This task also explored the possible relationship between auditory processing and its ability to affect performance on the task. Participants were 13 adults who stutter (mean age = 28 years), matched in age, gender, handedness, and education level with 13 adults who do not stutter (mean age = 28 years). For the nonvocal visual to auditory task, participants silently read an initial target nonword and matched that target nonword to four subsequent auditory nonword choices. The participants completed this task for 4- syllable and 7- syllable nonwords (N = 8 per set). Results indicated that adults who stutter were significantly less accurate than adults who do not stutter at both syllable lengths. Our present findings support previous research that suggests less efficient phonological working memory in adults who stutter.Communication Sciences and Disorder

Listeners normalize speech for contextual speech rate even without an explicit recognition task

Speech can be produced at different rates. Listeners take this rate variation into account by normalizing vowel duration for contextual speech rate: An ambiguous Dutch word /m?t/ is perceived as short /mAt/ when embedded in a slow context, but long /ma:t/ in a fast context. Whilst some have argued that this rate normalization involves low-level automatic perceptual processing, there is also evidence that it arises at higher-level cognitive processing stages, such as decision making. Prior research on rate-dependent speech perception has only used explicit recognition tasks to investigate the phenomenon, involving both perceptual processing and decision making. This study tested whether speech rate normalization can be observed without explicit decision making, using a cross-modal repetition priming paradigm. Results show that a fast precursor sentence makes an embedded ambiguous prime (/m?t/) sound (implicitly) more /a:/-like, facilitating lexical access to the long target word "maat" in a (explicit) lexical decision task. This result suggests that rate normalization is automatic, taking place even in the absence of an explicit recognition task. Thus, rate normalization is placed within the realm of everyday spoken conversation, where explicit categorization of ambiguous sounds is rare

Alcohol Language Corpus

The Alcohol Language Corpus (ALC) is the first publicly available speech corpus comprising intoxicated and sober speech of 162 female and male German speakers. Recordings are done in the automotive environment to allow for the development of automatic alcohol detection and to ensure a consistent acoustic environment for the alcoholized and the sober recording. The recorded speech covers a variety of contents and speech styles. Breath and blood alcohol concentration measurements are provided for all speakers. A transcription according to SpeechDat/Verbmobil standards and disfluency tagging as well as an automatic phonetic segmentation are part of the corpus. An Emu version of ALC allows easy access to basic speech parameters as well as the us of R for statistical analysis of selected parts of ALC. ALC is available without restriction for scientific or commercial use at the Bavarian Archive for Speech Signals

Orthography influences the perception and production of speech.

One intriguing question in language research concerns the extent to which orthographic information impacts on spoken word processing. Previous research has faced a number of methodological difficulties and has not reached a definitive conclusion. Our research addresses these difficulties by capitalizing on recent developments in the area of word learning. Participants were trained to criterion on a set of associations between novel pictures and novel spoken words. Spelling-sound consistent or spelling-sound inconsistent spellings were introduced on the 2nd day, and the influence of these spellings on speech processing was assessed on the 3rd day. Results showed significant orthographic effects on speech perception and speech production in a situation in which spelling–sound consistency was manipulated with perfect experimental control. Results are discussed in terms of a highly interactive language system in which there is a rapid and automatic flow of activation in both directions between orthographic and phonological representations