This paper reviews evidence concerning the nature of grouping in music and language and their interactions with other linguistic and musical systems. I present brief typological surveys of the relationship between constituency and acoustic parameters in language and music, drawing from a wide variety of languages and musical genres. The two domains both involve correspondence between auditory discontinuities and group boundaries, reflecting the Gestalt principles of proximity and similarity, as well as a nested, hierarchical organization of constituents. Typically, computational-level theories (...) of musical grouping take the form of a function from acoustic properties through grouping representations to syntactic or interpretive constituents. Linguistic theories tend to be cast as functions in the opposite direction. This study argues that the difference in orientation is not grounded in principled differences in information flow between the two domains, and that reconceptualizing one or both theories allows for gains in analytical understanding. There are also obvious differences between musical and linguistic grouping. Grappling with those differences requires one to think in detail about modularity, information flow, levels of description, and the functional nature of cognitive domains. (shrink)

Statistical learning is often taken to lie at the heart of many cognitive tasks, including the acquisition of language. One particular task in which probabilistic models have achieved considerable success is the segmentation of speech into words. However, these models have mostly been tested against English data, and as a result little is known about how a statistical learning mechanism copes with input regularities that arise from the structural properties of different languages. This study focuses on statistical word segmentation in (...) Arabic, a Semitic language in which words are built around consonantal roots. We hypothesize that segmentation in such languages is facilitated by tracking consonant distributions independently from intervening vowels. Previous studies have shown that human learners can track consonant probabilities across intervening vowels in artificial languages, but it is unknown to what extent this ability would be beneficial in the segmentation of natural language. We assessed the performance of a Bayesian segmentation model on English and Arabic, comparing consonant-only representations with full representations. In addition, we examined to what extent structurally different proto-lexicons reflect adult language. The results suggest that for a child learning a Semitic language, separating consonants from vowels is beneficial for segmentation. These findings indicate that probabilistic models require appropriate linguistic representations in order to effectively meet the challenges of language acquisition. (shrink)

Processes governing the creation, perception and production of spoken words are sensitive to the patterns of speech sounds in the language user’s lexicon. Generative linguistic theory suggests that listeners infer constraints on possible sound patterning from the lexicon and apply these constraints to all aspects of word use. In contrast, emergentist accounts suggest that these phonotactic constraints are a product of interactive associative mapping with items in the lexicon. To determine the degree to which phonotactic constraints are lexically mediated, we (...) observed the effects of learning new words that violate English phonotactic constraints on phonotactic perceptual repair processes in nonword consonant-consonant-vowel stimuli. Subjects who learned such words were less likely to “repair” illegal onset clusters and report them as legal ones. Effective connectivity analyses of MRI-constrained reconstructions of simultaneously collected magnetoencephalography and EEG data showed that these behavioral shifts were accompanied by changes in the strength of influences of lexical areas on acoustic-phonetic areas. These results strengthen the interpretation of previous results suggesting that phonotactic constraints on perception are produced by top-down lexical influences on speech processing. (shrink)

This paper reconsiders the diphone-based word segmentation model of Cairns, Shillcock, Chater, and Levy (1997) and Hockema (2006), previously thought to be unlearnable. A statistically principled learning model is developed using Bayes’ theorem and reasonable assumptions about infants’ implicit knowledge. The ability to recover phrase-medial word boundaries is tested using phonetic corpora derived from spontaneous interactions with children and adults. The (unsupervised and semi-supervised) learning models are shown to exhibit several crucial properties. First, only a small amount of language exposure (...) is required to achieve the model’s ceiling performance, equivalent to between 1 day and 1 month of caregiver input. Second, the models are robust to variation, both in the free parameter and the input representation. Finally, both the learning and baseline models exhibit undersegmentation, argued to have significant ramifications for speech processing as a whole. (shrink)

When infants and toddlers are confronted with sequences of sounds, they are required to segment the sounds into meaningful units to achieve sufficient understanding. Rhythm has been regarded as a crucial cue for segmentation of speech sounds. Although previous intermodal methods indicated that infants and toddlers could detect differences in speech sounds based on stress-timed and syllable-timed units, these methods could not clearly indicate how infants and toddlers perform sound segmentation. Thus, the present study examined whether Japanese infants and toddlers (...) could segment word speech sounds comprising basic morae, on the basis of concurrent basic mora units within syllable units, using the new intermodal matching procedure. The results indicated that, regardless of their ages and linguistic abilities, Japanese infants and toddlers aged 6–25 months tended to segment Japanese words comprising basic morae sounds on the basis of concurrent basic mora units within syllable units. This implies that infants' and toddlers' use of syllable units for segmentation of speech sounds at an early age could be evident among many infants and toddlers learning various languages. Although this finding should be interpreted carefully, the present study demonstrated the utility of the new intermodal matching procedure for examining segmentation of speech sounds and word sounds by infants and toddlers, on the basis of specific rhythm units. (shrink)

Poverty of the Stimulus Arguments have convinced many linguists and philosophers of language that a domain specific language acquisition device (LAD) is necessary to account for language learning. Here we review empirical evidence that casts doubt on the necessity of this domain specific device. We suggest that more attention needs to be paid to the early stages of language acquisition. Many seemingly innate language-related abilities have to be learned over the course of several months. Further, the language input contains rich (...) stochastic information that can be accessed by domain-general learning mechanisms. Computer simulation has shown how mechanisms that are not domain specific can exploit the information contained in language. We conclude that (i) Poverty of the Stimulus Arguments need to be conceptually clarified and (ii) more empirical research needs to be carried out before we can rule out that data driven general purpose mechanisms can account for language learning. (shrink)

Prelinguistic infants must find a way to isolate meaningful chunks from the continuous streams of speech that they hear. BootLex, a new model which uses distributional cues to build a lexicon, demonstrates how much can be accomplished using this single source of information. This conceptually simple probabilistic algorithm achieves significant segmentation results on various kinds of language corpora - English, Japanese, and Spanish; child- and adult-directed speech, and written texts; and several variations in coding structure - and reveals which statistical (...) characteristics of the input have an influence on segmentation performance. BootLex is then compared, quantitatively and qualitatively, with three other groups of computational models of the same infant segmentation process, paying particular attention to functional characteristics of the models and their similarity to human cognition. Commonalities and contrasts among the models are discussed, as well as their implications both for theories of the cognitive problem of segmentation itself, and for the general enterprise of computational cognitive modeling. (shrink)