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The morphological structure of complex words impacts how they are processed during visual word recognition. This impact varies over the course of reading acquisition and for different languages and writing systems. Many theories of morphological processing rely on a decomposition mechanism, in which words are decomposed into explicit representations of their constituent morphemes. In distributed accounts, in contrast, morphological sensitivity arises from the tuning of finer-grained representations to useful statistical regularities in the form-to-meaning mapping, without the need for explicit morpheme representations. In this theoretically guided review, we summarize research into the mechanisms of morphological processing, and discuss findings within the context of decomposition and distributed accounts. Although many findings fit within a decomposition model of morphological processing, we suggest that the full range of results is more naturally explained by a distributed approach, and discuss additional benefits of adopting this perspective.

This review article presents evidence for the claim that frequency effects are pervasive in children's first language acquisition, and hence constitute a phenomenon that any successful account must explain. The article is organized around four key domains of research: children's acquisition of single words, inflectional morphology, simple syntactic constructions, and more advanced constructions. In presenting this evidence, we develop five theses. (i) There exist different types of frequency effect, from effects at the level of concrete lexical strings to effects at the level of abstract cues to thematic-role assignment, as well as effects of both token and type, and absolute and relative, frequency. High-frequency forms are (ii) early acquired and (iii) prevent errors in contexts where they are the target, but also (iv) cause errors in contexts in which a competing lower-frequency form is the target. (v) Frequency effects interact with other factors (e.g. serial position, utterance length), and the patterning of these interactions is generally informative with regard to the nature of the learning mechanism. We conclude by arguing that any successful account of language acquisition, from whatever theoretical standpoint, must be frequency sensitive to the extent that it can explain the effects documented in this review, and outline some types of account that do and do not meet this criterion.

The brain tracks and encodes multi‐level speech features during spoken language processing. It is evident that this speech tracking is dominant at low frequencies (<8 Hz) including delta and theta bands. Recent research has demonstrated distinctions between delta‐ and theta‐band tracking but has not elucidated how they differentially encode speech across linguistic levels. Here, we hypothesised that delta‐band tracking encodes prediction errors (enhanced processing of unexpected features) while theta‐band tracking encodes neural sharpening (enhanced processing of expected features) when people perceive speech with different linguistic contents. EEG responses were recorded when normal‐hearing participants attended to continuous auditory stimuli that contained different phonological/morphological and semantic contents: (1) real‐words, (2) pseudo‐words and (3) time‐reversed speech. We employed multivariate temporal response functions to measure EEG reconstruction accuracies in response to acoustic (spectrogram), phonetic and phonemic features with the partialling procedure that singles out unique contributions of individual features. We found higher delta‐band accuracies for pseudo‐words than real‐words and time‐reversed speech, especially during encoding of phonetic features. Notably, individual time‐lag analyses showed that significantly higher accuracies for pseudo‐words than real‐words started at early processing stages for phonetic encoding (<100 ms post‐feature) and later stages for acoustic and phonemic encoding (>200 and 400 ms post‐feature, respectively). Theta‐band accuracies, on the other hand, were higher when stimuli had richer linguistic content (real‐words > pseudo‐words > time‐reversed speech). Such effects also started at early stages (<100 ms post‐feature) during encoding of all individual features or when all features were combined. We argue these results indicate that delta‐band tracking may play a role in predictive coding leading to greater tracking of pseudo‐words due to the presence of unexpected/unpredicted semantic information, while theta‐band tracking encodes sharpened signals caused by more expected phonological/morphological and semantic contents. Early presence of these effects reflects rapid computations of sharpening and prediction errors. Moreover, by measuring changes in EEG alpha power, we did not find evidence that the observed effects can be solitarily explained by attentional demands or listening efforts. Finally, we used directed information analyses to illustrate feedforward and feedback information transfers between prediction errors and sharpening across linguistic levels, showcasing how our results fit with the hierarchical Predictive Coding framework. Together, we suggest the distinct roles of delta and theta neural tracking for sharpening and predictive coding of multi‐level speech features during spoken language processing.

We know a great deal about children’s first steps into reading. Here, we explore how they become more sophisticated readers, learning to read complex words. Theoretical accounts predict that one key factor is morphological awareness, or awareness of the minimal units of meaning in language. And yet empirical studies have yet to clarify whether morphological awareness has a stronger relation to the development of reading skill for words with multiple morphemes in particular (i.e., morphological decoding) or to the reading of a whole range of words. We examined this question in this study by contrasting the role of morphological awareness in the development of morphological decoding and of broader word reading skill. Participants were 197 English-speaking children who were followed from Grade 3 to 4. We conducted longitudinal analyses that included stringent autoregressive controls to capture the determinants of gains over time, as well as controls for vocabulary and phonological awareness. Structural equation modeling (SEM) path analysis with this set of controls revealed that morphological awareness predicted significant unique gains in morphological decoding from Grade 3 to 4 with no such unique contributions to broader word reading skill. These findings clarify the role of morphological awareness in supporting children in developing the ability to read morphologically complex words, supporting a more targeted role for morphology in theories of word reading development.

Morphological knowledge refers to the ability to recognize and use morphemes correctly in syntactic contexts and word formation. This is crucial for learning a morphologically rich language like Finnish, which features both agglutinative and fusional morphology. In Finnish, agglutination occurs in forms like aamu: aamu+lla (‘morning: in the morning’), where a suffix is transparently added. Fusional features, as seen in ilta: illa+lla (‘evening: in the evening’), involve allomorphic stem changes that reduce transparency. We investigated the challenges posed by stem allomorphy for word recognition in isolation and in context for L2 learners and L1 speakers of Finnish. In a lexical decision task, L2 speakers had longer response times and higher error rates for semitransparent inflections, while L1 speakers showed longer response times for both transparent and semitransparent inflection types. In sentence reading, L2 speakers exhibited longer fixation times for semitransparent forms, whereas L1 speakers showed no significant effects. The results suggest that the challenges in L2 inflectional processing are more related to fusional than agglutinative features of the Finnish language.

The relative importance of phonological versus morphological processes in reading varies depending on the writing system's orthographic consistency and morphological complexity. This study investigated the interplay between phonology and morphology in Hebrew reading acquisition, a language offering a unique opportunity for such examination with its rich, complex Semitic morphological system and dual writing versions differing in orthographic consistency—transparent-pointed and deep-unpointed versions. Ninety-eight second graders and 81 fourth graders participated in pseudoword-reading tasks designed to distinguish between the different processes: pointed morphologically based pseudowords (pointed MPW), reflecting phonological and morphological processing; unpointed morphologically based pseudowords (unpointed MPW), reflecting only morphological processing; and pointed non-words (pointed NW), with no internal morphological structure, reflecting only phonological processing. Real pointed-word reading accuracy and fluency were also assessed. Results showed the highest accuracy in reading unpointed MPW, with a similar accuracy level observed between unpointed MPW and pointed MPW in second grade, while a significant difference emerged in fourth grade. An age-by-processing type interaction revealed decreasing accuracy in pointed MPW and increasing accuracy in unpointed MPW with age. Additionally, morphological processing significantly enhanced the accuracy and fluency of reading pointed words beyond phonological processing, despite the comprehensive phonological information provided by the transparent, pointed script. These findings suggest that the contribution of morphology exceeds that of phonology as early as second grade, with this trend strengthening through fourth grade, emphasizing children's early prioritization of morphological transparency over orthographic consistency in learning to read Hebrew Semitic orthography.

Hebrew allows the representation of the meaning of a few words in one dense form by using bound morphemes that linearly attach to the word. By manipulating words’ density in text, that is, decomposing them into isolated words which changes the length of the text, it was possible to check the impact of density on reading comprehension in novice readers. Each of the 292 s graders from a low SES background, of whom 79 were struggling readers (poor decoders) and the rest were typical readers, were tested in two reading comprehension tests: dense and decomposed. They also were tested in other literacy measures (word recognition, decoding, morphological awareness, vocabulary, and spelling) to learn about their reading proficiency and awareness of morphemes. The results showed a significant interaction between text type and reading ability group, while controlling for vocabulary, indicating that text density levels had varying effects on reading performance in each reading ability group. This interaction manifested as typical readers benefiting more from decomposed texts, evidenced by improved comprehension scores for these texts compared to dense texts. In contrast, struggling readers’ comprehension scores did not significantly differ between the two text types, suggesting that text density did not influence their reading performance to the same extent. Furthermore, typical readers exhibited better performance across all literacy measures, including morphological awareness. Findings suggest that a certain level of phonological decoding and morphological awareness are needed to benefit from decomposed texts. Morphological density adds another layer of difficulty for novice readers, who need to unfold the word’s structure and reveal the full meaning – a process that is assumed to be cognitively complex. They also highlight the importance of morpheme awareness in dense, morphologically complex languages like Hebrew at an early age.

Skilled reading comprehension is an important goal of educational instruction and models of reading development. In this study, the authors investigated how core skills surrounding morphemes, that is, the minimal units of meaning in language, support the development of reading comprehension. The authors specifically contrast the roles of morphological awareness and morphological analysis; the first refers to the awareness of and ability to manipulate morphemes in language, and the second refers to the use of morphemes in inferring the meaning of unfamiliar morphologically complex (multimorphemic) words. The authors evaluated these morphological skills in 197 English-speaking students who were followed from grade 3 to grade 4; the analyses used stringent autoregressor controls to home in on predictors of gains over time. In addition to morphological awareness and morphological analysis, the authors assessed students’reading comprehension and controls for word reading, vocabulary, phonological awareness, nonverbal ability, and age. Multivariate autoregressive path analysis revealed that morphological analysis, but not morphological awareness, predicted gains in reading comprehension. Morphological awareness, for its part, predicted gains in morphological analysis. Taken together, the findings allude to a developmental trajectory whereby students’use of morphemes to infer the meanings of unfamiliar complex words supports the development of reading comprehension over time. The development of this skill, in turn, appears to be supported by a more general awareness of morphemes in language. These findings contribute to theory and reading instruction by clarifying the ways in which morphological skills support the development of students’ reading comprehension.

Sanskrit processing has seen a surge in the use of data-driven approaches over the past decade. Various tasks such as segmentation, morphological parsing, and dependency analysis have been tackled through the development of state-of-the-art models despite working with relatively limited datasets compared to other languages. However, a significant challenge lies in the availability of annotated datasets that are lexically, morphologically, syntactically, and semantically tagged. While syntactic and semantic tags are preferable for later stages of processing such as sentential parsing and disambiguation, lexical and morphological tags are crucial for low-level tasks of word segmentation and morphological parsing. The Digital Corpus of Sanskrit (DCS) is one notable effort that hosts over 650,000 lexically and morphologically tagged sentences from around 250 texts but also comes with its limitations at different levels of a sentence like chunk, segment, stem and morphological analysis. To overcome these limitations, we look at alternatives such as Sanskrit Heritage Segmenter (SH) and Saṃsādhanī tools, that provide information complementing DCS’ data. This work focuses on enriching the DCS dataset by incorporating analyses from SH, thereby creating a dataset that is rich in lexical and morphological information. Furthermore, this work also discusses the impact of such datasets on the performances of existing segmenters, specifically the Sanskrit Heritage Segmenter.