CLASSIC Utterance Boundary
A Chunking-Based Model of Early Naturalistic Word Segmentation
Datos Bibliográficos
| ID | 5087746 |
|---|---|
| Autores | Francesco Cabiddu (0000-0001-9692-4897, Cardiff University, autor de correspondencia), Lewis Bott (0000-0002-4926-1231, Cardiff University), Gary Jones (0000-0003-3867-9947, Nottingham Trent University), Chiara Gambi (0000-0002-1568-7779, Cardiff University) |
| Año | 2023 |
| Volumen | 73 |
| Número | 3 |
| Páginas | 942-975 |
| Fecha de publicación | 2023-09-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Language Learning (JOURNAL) |
| Identificadores de la revista | ISSN: 0023-8333 • E-ISSN: 1467-9922 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/lang.12559 |
| OpenAlex | W4319161892 |
| Idioma | EN |
| Citas recibidas | 3 |
| Referencias citadas | 102 |
Word segmentation is a crucial step in children's vocabulary learning. While computational models of word segmentation can capture infants' performance in small-scale artificial tasks, the examination of early word segmentation in naturalistic settings has been limited by the lack of measures that can relate models' performance to developmental data. Here, we extended CLASSIC (Chunking Lexical and Sublexical Sequences in Children; Jones et al., 2021), a corpus-trained chunking model that can simulate several memory and phonological and vocabulary learning phenomena to allow it to perform word segmentation using utterance boundary information, and we have named this extended version CLASSIC utterance boundary (CLASSIC-UB). Further, we compared our model to the performance of children on a wide range of new measures, capitalizing on the link between word segmentation and vocabulary learning abilities. We showed that the combination of chunking and utterance-boundary information used by CLASSIC utterance boundary allowed a better prediction of English-learning children's output vocabulary than did other models
Chunking (psychology) · Linguistics · Natural language processing · Segmentation · Speech recognition · Speech segmentation · Text segmentation · Utterance · Vocabulary · Word (group theory) · Artificial Intelligence · Computer Science · Language Development and Disorders · Psychology · Reading and Literacy Development · Speech and dialogue systems
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| Obras citantes distintas | 3 |
|---|---|
| Citas por año | 3 |
| Intervalo de citas | 2025 - 2025 (1) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 3 |