Frost, R.

Kidd, E.

Stärk, K.

English

MPG.PuRe

• Word length: 78% monosyllabic, 17% disyllabic, (37% mono-, 40% disyllabic for unique word tokens)Introduction• One of the first challenges in language acquisition is speech segmentation• Multiple cues have been found to aid segmentation1,2→ Stress3→ Highly frequent function words4,5→ Transitional probabilities6,7• Availability and reliabitlity of cues differs between languages → RQ: which segmentation cues are available in German CDS?Method• Corpus analysis, performed on data from German CHILDES8• Coded ~16,000 words (~4,000 utterances) = ca. 1 day of input9• Coded for: primary word stress, word length (number of syllables), word category (function/content word), syllable structure, TPsResults• Stress: 97% of words contained word-initial stress (87% of unique word tokens (frequency-controlled), 86% excluding monosyllabic words)A Corpus Analysis of the Word Segmentation Cues in German Child-Directed SpeechKatja Stärk1,2, Evan Kidd1,3,4 & Rebecca L.A. Frost1Please contact me:Katja.Staerk@mpi.nl1) Max-Planck-Institute for Psycholinguistics, Nijmegen, The Netherlands   2) IMPRS for Language Sciences, Nijmegen, The Netherlands   3) Research School of Psychology, The Australian National University, Canberra, Australia   4) ARC Centre of Excellence for the Dynamics of Language, Canberra, AustraliaSummary• First corpus analysis on word segmentation cues in German• Multiple segmentation cues are available→ Stress as almost perfect cue to wordhood in German CDS→ High proportion of high frequency function words, which may act as anchors during segmentation4,5→ Statistical cues to segmentation (TPs) are present but seem to be weaker than stress cue@katjastaerk• Word category: 62% of all words were monosyllabic function words; 45/50 most frequent words were function words (90%) • Syllable structure: Varied depending on syllable position within words: intermediate syllables were often open, wheras initial and final syllables tended to be closedREF:  1) Aslin et al. (1996). Models of Word Segmentation in Fluent Maternal Speech to Infants;  2) Lehiste (1970). Suprasegmentals;  3) Friederici, et al. (2007). Curr. Biol.;  4) Bortfeld et al. (2005). Psych. Sci.; 5) Frost et al. (2019). JEP: LMC; 6) Saffran et al. (1996). Science;  7) Aslin et al. (1998). Psych. Sci.; 8) MacWhinney (2000). The CHILDES Project;  9) Rowland et al., (unpubl.). The Language 0-5 ProjectLCICD 201910 most frequent word types:das, du, ist, da, ja, die, mal, was, der, so• Transitional probabilities (TPs): We found two main effects and an interaction, controlling for the frequency of the syllable pairoverall initial intermediate final1 CVC 3777 CVV 3190 CV 338 CVC 33052 CVV 3482 CVC 3008 CVV 157 CVV 26333 CV 2993 CV 1324 CVC 120 CV 17484 CVVC 1449 CVVC 1318 CCVV 42 CVVC 13125 CVVV 1061 CVVV 1025 CCV 39 CVVV 1004Forwards TPs Backwards TPsWithin-word M = 0.296 M = 0.364(SD = 0.388) (SD = 0.436)Between-words M = 0.097 M = 0.124(SD = 0.207) (SD = 0.224)→ TPs were higher within than between words(β = -0.222, SE = 0.006, t = -38.524, p < .001)→ TPs were higher backwards than forwards(β = 0.025, SE = 0.003, t = 8.851, p < .001)→ There was a larger difference within/between-words for the backwards TPs   (β = -0.025, SE = 0.006, t = 8.851, p < .001)

A corpus analysis of the word segmentation cues in German child-directed speech

http://hdl.handle.net/21.11116/0000-0004-6E1B-4

A corpus analysis of the word segmentation cues in German child-directed speech

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