Links Between Implicit Learning of Sequential Patterns and Spoken Language Processing

Links Between Implicit Learning of Sequential Patterns and Spoken Language Processing Christopher M. Conway (cmconway@indiana.edu) David B. Pisoni (pisoni@indiana.edu) Department of Psychological & Brain Sciences, 1101 E. 10th Street Bloomington, IN 47405 USA Abstract the perception of spoken materials in noise; the more predictable a sentence is, the easier it is to perceive it (Kalikow et al., 1977). Therefore, the ability to extract probabilistic or statistical patterns in the speech stream may be a factor that is important for language learning and spoken language processing: the better able one is at implicitly learning the sequential patterns in language, the better one should be at processing upcoming spoken materials in an utterance, especially under highly degraded listening conditions. In this paper, we examine the hypothesis that a domain- general ability to implicitly encode complex sequential patterns underlies aspects of spoken language processing. This kind of incidental, probabilistic sequence learning has been investigated in some depth over the last few years under the rubrics of “implicit”, “procedural”, or “statistical” learning (Cleeremans, Destrebecqz, & Boyer, 1998; Conway & Christiansen, 2006; Saffran, Aslin, & Newport, 1996; Stadler & Frensch, 1998). To help elucidate the link between implicit learning and language processing, we used a new experimental methodology that was developed to assess sequence memory and learning based on Milton Bradley’s Simon memory game (e.g., Pisoni & Cleary, 2004). In this task, participants see sequences of colored lights and/or sounds and are required to simply reproduce each sequence by pressing colored response panels in correct order. Not only can the Simon memory game task be used to assess learning and memory of fixed sequences, but it can also be used to measure implicit sequence learning of more complex rule-governed or probabilistic patterns (Karpicke & Pisoni, 2004). In the present experiment, we used a version of the Simon memory game that incorporates visual- only stimuli that contained structural regularities, and correlated participants’ performance on the implicit learning task with their ability to perceive spoken sentences that varied in terms of the final word’s predictability, under degraded listening conditions. Before describing the study in full, we first briefly review previous evidence related to implicit learning and language processing. Spoken language consists of a complex, time-varying signal that contains sequential patterns that can be described in terms of statistical relations among language units. Previous research has suggested that a domain-general ability to learn structured sequential patterns may underlie language acquisition. To test this prediction, we examined the extent to which implicit sequence learning of probabilistically- structured patterns in normal-hearing adults is correlated with performance on a spoken sentence perception task under degraded listening conditions. Our data revealed that performance on the sentence perception task correlated with implicit sequence learning, but only when the sequences were composed of stimuli that were easy to encode verbally. The evidence is consistent with the hypothesis that implicit learning of phonological sequences is an important cognitive ability that contributes to spoken language processing abilities. Keywords: Implicit learning, artificial grammar learning, sequence learning, speech perception, language. Introduction It has long been recognized that language comprehension involves the coding and manipulation of sequential patterns (Lashley, 1951; see also Conway & Christiansen, 2001). Spoken language can be thought of as patterns of sound symbols occurring in a sequential stream. Many of the sequential patterns of language are fixed, that is, they occur in a consistent, regular order (e.g., words are fixed sequences of phonemes). Thus, being able to encode and store in memory fixed sequences of sounds would appear to be a key aspect of language learning. Empirical work with normal-hearing adults and children supports this view, showing a strong link between sequence memory, word learning, and vocabulary development (for a review, see Baddeley, 2003). Although short-term verbal memory is undoubtedly important for learning fixed sequences in language, such as words or idioms, the learning of more complex, highly variable patterns in language may require a different kind of cognitive mechanism altogether (Conway & Christiansen, 2001). For instance, in addition to fixed sequential patterns of sounds, spoken language also contains sequences that can be described in terms of complex statistical relations among language units. Rarely is a spoken utterance perfectly predictable; most often, the next word in a sentence can only be partially predicted based on the preceding context (Rubenstein, 1973). It is known that sensitivity to such probabilistic information in the speech stream can improve Implicit Sequence Learning and Language Implicit learning involves automatic, unconscious learning mechanisms that extract regularities and patterns that are present across a set of exemplars, typically without direct awareness of what has been learned. Many researchers believe that implicit learning is one of the