AbstractMuch previous research on distributional learning and phonetic categorization assumes that categories are either faithful reproductions or parametric summaries of experienced frequency distributions, acquired through a Hebbian learning process in which every experience contributes equally to the category representation. We suggest that category representations may instead be formed via error-driven predictive learning. Rather than passively storing tagged category exemplars or updating parametric summaries of token counts, learners actively anticipate upcoming events and update their beliefs in proportion to how surprising/unexpected these events turn out to be. As a result, rare category members exert a disproportionate influence on the category representation. We present evidence for this hypothesis from a distributional learning experiment on acquiring a novel phonetic category, and show that the results are well described by a classic error-driven learning model (Rescorla, R. A. & A. R. Wagner. 1972. A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In A. H. Black & W. F. Prokasy (eds.), Classical conditioning II: Current research and theory, 64–99. New York, NY: Appleton-Century-Crofts).

No abstract

Phonotactic generalisations can be computed at different levels of granularity, from a coarse-grained legal/illegal dichotomy (blick, dwick ≻ *bnick, *lbick) to a fine-grained gradient of acceptability (blick ≻ dwick ≻ bnick ≻ lbick). This article investigates the sensitivity of the English metrical parse to the granularity of medial onset phonotactics. We present two experiments that feature pseudo-words with medial consonants and CC clusters varying in word-edge frequency and sonority (e.g. vatablick, vatadwick, vatabnick, vatalbick). The metrical parse is inferred from a hyphenation experiment and an online stress-assignment experiment. The results of both studies indicate that the parse is stochastic, and guided by relatively fine-grained phonotactic dependencies. Vocabulary simulations suggest that this level of granularity may arise because the gradient parser consistently outperforms the coarse-grained alternative across the developing lexicon.

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: there is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like.

Komo [xom] is an endangered and under-documented language spoken along the Ethio-Sudanese border. This paper presents the results of the first phonetic investigation of the Komo vowel system and reports on a related perception experiment carried out in the field. Our first aim is to provide an acoustic description of the Advanced Tongue Root (ATR) feature in Komo, which is contrastive in the high vowels and allophonic in the non-high vowels. To this end, we present acoustic measurements of 2, 688 vowel tokens produced by 16 speakers. Our second aim is to examine the influence of Komo's typologically unique vowel harmony system on listeners' perception of the [ATR] feature. Komo ATR harmony displays two competing processes triggered by the high vowels (Otero, 2015): [ + ATR] spreads leftward to non-high vowels (e.g., /CaCi/ → [CəCi]), while [-ATR] spreads rightward to high vowels (e.g., /CɪCi/ → [CɪCɪ]). Sixteen Komo listeners and 16 native English-speaking controls performed an AX task with disyllabic (pseudo)words featuring context vowels and [±ATR] vowel continua. Patterns in the results suggest that (a) Komo listeners (but not controls) were influenced by the [ATR] value of the context, and (b) targets of [ + ATR] harmony were processed differently from targets of [-ATR] harmony.