Biomedical subjects

Marina Nespor

Publications and source records attributed to Marina Nespor.

6 recordsLinked to original sources

PubMed2006

An interaction between prosody and statistics in the segmentation of fluent speech.

Sensitivity to prosodic cues might be used to constrain lexical search. Indeed, the prosodic organization of speech is such that words are invariably aligned with phrasal prosodic edges, providing a cue to segmentation. In this paper we devise an experimental paradigm that allows us to investigate the interaction between statistical and prosodic cues to extract words from a speech stream. We provide evidence that statistics over the syllables are computed independently of prosody. However, we also show that trisyllabic sequences with high transition probabilities that straddle two prosodic constituents appear not to be recognized. Taken together, our findings suggest that prosody acts as a filter, suppressing possible word-like sequences that span prosodic constituents.

Adult↗

PubMed2006

The "soul" of language does not use statistics: reflections on vowels and consonants.

This paper reviews studies of language processing with the aim of establishing whether any type of statistical information embedded in linguistic signals can be exploited by the language learner. The constraints as to the information that can be so used, we will argue, should be used to inform theories of language acquisition. We present two experiments with their respective controls. Both show that consonants (Cs) are much more suitable than vowels (Vs) to parse speech streams using statistical dependencies. These experiments use streams composed of items in which statistical information is carried either by the sequence of consonants or by the sequence of vowels. Both kinds of items are simultaneously present is the speech stream but, crucially, their overlap is only partial. Since the location of dips in transitional probabilities (TPs) between adjacent syllables differ for the first and the second type of sequences, we can explore whether consonants and vowels are equally efficient segments to parse signals. Our results show that "consonant words" (CW) are significantly preferred over "vowel words" (VW). We discuss the implication of our results for models of language acquisition.

Adult↗

PubMed2006

How to hit Scylla without avoiding Charybdis: comment on Perruchet, Tyler, Galland, and Peereman (2004).

M. Peña, L. L. Bonatti, M. Nespor, and J. Mehler argued that humans compute nonadjacent statistical relations among syllables in a continuous artificial speech stream to extract words, but they use other computations to determine the structural properties of words. Instead, when participants are familiarized with a segmented stream, structural generalizations about words are quickly established. P. Perruchet, M. D. Tyler, N. Galland, and R. Peereman criticized M. Peña et al.'s work and dismissed their results. In this article, the authors show that P. Perruchet et al.'s criticisms are groundless.

Adult↗

PubMed2006

Why is language unique to humans?

Cognitive neuroscience has focused on language acquisition as one of the main domains to test the respective roles of statistical vs. rule-like computation. Recent studies have uncovered that the brain of human neconates displays a typical signature in response to speech sounds even a few hours after birth. This suggests that neuroscience and linguistics converge on the view that, to a large extent, language acquisition arises due to our genetic endowment. Our research has also shown how statistical dependencies and the ability to draw structural generalizations are basic processes that interact intimately. First, we explore how the rhythmic properties of language bias word segmentation. Second, we demonstrate that natural speech categories play specific roles during language acquisition: some categories are optimally suited to compute statistical dependencies while other categories are optimally suited for the extraction of structural generalizations.

Animals↗

PubMed2005

Linguistic constraints on statistical computations: the role of consonants and vowels in continuous speech processing.

Speech is produced mainly in continuous streams containing several words. Listeners can use the transitional probability (TP) between adjacent and non-adjacent syllables to segment "words" from a continuous stream of artificial speech, much as they use TPs to organize a variety of perceptual continua. It is thus possible that a general-purpose statistical device exploits any speech unit to achieve segmentation of speech streams. Alternatively, language may limit what representations are open to statistical investigation according to their specific linguistic role. In this article, we focus on vowels and consonants in continuous speech. We hypothesized that vowels and consonants in words carry different kinds of information, the latter being more tied to word identification and the former to grammar. We thus predicted that in a word identification task involving continuous speech, learners would track TPs among consonants, but not among vowels. Our results show a preferential role for consonants in word identification.

Humans↗

PubMed2002

Signal-driven computations in speech processing.

Learning a language requires both statistical computations to identify words in speech and algebraic-like computations to discover higher level (grammatical) structure. Here we show that these computations can be influenced by subtle cues in the speech signal. After a short familiarization to a continuous speech stream, adult listeners are able to segment it using powerful statistics, but they fail to extract the structural regularities included in the stream even when the familiarization is greatly extended. With the introduction of subliminal segmentation cues, however, these regularities can be rapidly captured.

Adult↗