Does morphological complexity affect word segmentation? Evidence from computational modeling

10.31234/osf.io/hzmyf ◽

2021 ◽

Author(s):

Georgia Loukatou ◽

Sabine Stoll ◽

Damián Ezequiel Blasi ◽

Alejandrina Cristia

Keyword(s):

Computational Modeling ◽

Word Segmentation ◽

Inflectional Morphology ◽

Computational Studies ◽

Morphological Complexity ◽

Artificial Languages ◽

Segmentation Algorithms ◽

Word Boundaries ◽

Continuous Stream ◽

Distributional Cues

How can infants detect where words or morphemes start and end in the continuous stream of speech? Previous computational studies have investigated this question mainly for English, where morpheme and word boundaries are often isomorphic. Yet in many languages, words are often multimorphemic, such that word and morpheme boundaries do not align. Our study employed corpora of two languages that differ in the complexity of inflectional morphology, Chintang (Sino-Tibetan) and Japanese (in Experiment 1), as well as corpora of artificial languages ranging in morphological complexity, as measured by the ratio and distribution of morphemes per word (in Experiments 2 and 3). We used two baselines and three conceptually diverse word segmentation algorithms, two of which rely purely on sublexical information using distributional cues, and one that builds a lexicon. The algorithms’ performance was evaluated on both word- and morpheme-level representations of the corpora.Segmentation results were better for the morphologically simpler languages than for the morphologically more complex languages, in line with the hypothesis that languages with greater inflectional complexity could be more difficult to segment into words. We further show that the effect of morphological complexity is relatively small, compared to that of algorithm and evaluation level. We therefore recommend that infant researchers look for signatures of the different segmentation algorithms and strategies, before looking for differences in infant segmentation landmarks across languages varying in complexity.

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Is there a bilingual disadvantage for word segmentation? A computational modeling approach

Journal of Child Language ◽

10.1017/s0305000921000568 ◽

2021 ◽

pp. 1-28

Author(s):

Laia FIBLA ◽

Nuria SEBASTIAN-GALLES ◽

Alejandrina CRISTIA

Keyword(s):

Language Acquisition ◽

Young Children ◽

Computational Modeling ◽

Word Segmentation ◽

Computational Results ◽

Modeling Approaches ◽

Modeling Approach ◽

Segmentation Algorithms ◽

Language Effects ◽

Bilingual Corpora

Abstract Since there are no systematic pauses delimiting words in speech, the problem of word segmentation is formidable even for monolingual infants. We use computational modeling to assess whether word segmentation is substantially harder in a bilingual than a monolingual setting. Seven algorithms representing different cognitive approaches to segmentation are applied to transcriptions of naturalistic input to young children, carefully processed to generate perfectly matched monolingual and bilingual corpora. We vary the overlap in phonology and lexicon experienced by modeling exposure to languages that are more similar (Catalan and Spanish) or more different (English and Spanish). We find that the greatest variation in performance is due to different segmentation algorithms and the second greatest to language, with bilingualism having effects that are smaller than both algorithm and language effects. Implications of these computational results for experimental and modeling approaches to language acquisition are discussed.

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Reading Longer Words: Insights Into Multisyllabic Word Reading

Perspectives of the ASHA Special Interest Groups ◽

10.1044/persp2.sig1.86 ◽

2017 ◽

Vol 2 (1) ◽

pp. 86-94 ◽

Cited By ~ 2

Author(s):

Lindsay Heggie ◽

Lesly Wade-Woolley

Keyword(s):

Systematic Approach ◽

Word Reading ◽

Explicit Instruction ◽

Working Memory Capacity ◽

Reading Difficulties ◽

Instructional Programs ◽

Morphological Knowledge ◽

Morphological Complexity ◽

Reading Accuracy ◽

Grade 3

Students with persistent reading difficulties are often especially challenged by multisyllabic words; they tend to have neither a systematic approach for reading these words nor the confidence to persevere (Archer, Gleason, & Vachon, 2003; Carlisle & Katz, 2006; Moats, 1998). This challenge is magnified by the fact that the vast majority of English words are multisyllabic and constitute an increasingly large proportion of the words in elementary school texts beginning as early as grade 3 (Hiebert, Martin, & Menon, 2005; Kerns et al., 2016). Multisyllabic words are more difficult to read simply because they are long, posing challenges for working memory capacity. In addition, syllable boundaries, word stress, vowel pronunciation ambiguities, less predictable grapheme-phoneme correspondences, and morphological complexity all contribute to long words' difficulty. Research suggests that explicit instruction in both syllabification and morphological knowledge improve poor readers' multisyllabic word reading accuracy; several examples of instructional programs involving one or both of these elements are provided.

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