Word Segmentation
The Role of Distributional Cues
Bibliographic Data
| ID | 5774014 |
|---|---|
| Authors | Jenny Saffran (0000-0003-3749-8773, University of Rochester), Jenny R Saffran, Elissa L Newport (0000-0002-2783-5062, University of Rochester), Richard N Aslin, Richard Ν Aslin (0000-0003-4092-1712, University of Rochester) |
| Year | 1996 |
| Volume | 35 |
| Issue | 4 |
| Pages | 606-621 |
| Publication date | 1996-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Memory and Language (JOURNAL) |
| Journal identifiers | ISSN: 0749-596X • E-ISSN: 1096-0821 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1006/jmla.1996.0032 |
| OpenAlex | W2115867364 |
| Language | EN |
| Citations received | 181 |
| References cited | 5 |
One of the infant's first tasks in language acquisition is to discover the words embedded in a mostly continuous speech stream. This learning problem might be solved by using distributional cues to word boundaries-for example, by computing the transitional probabilities between sounds in the language input and using the relative strengths of these probabilities to hypothesize word boundaries. The learner might be further aided by language-specific prosodic cues correlated with word boundaries. As a first step in testing these hypotheses, we briefly exposed adults to an artificial language in which the only cues available for word segmentation were the transitional probabilities between syllables. Subjects were able to learn the words of this language. Furthermore, the addition of certain prosodic cues served to enhance performance. These results suggest that distributional cues may play an important role in the initial word segmentation of language learners
Constructed language · Cue-dependent forgetting · Speech segmentation · Text segmentation · Language and cultural evolution · Language Development and Disorders · Speech and dialogue systems
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| Unique citing works | 181 |
|---|---|
| Citations per year | 6,03 |
| Citation span | 1996 - 2026 (31) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 177 |