The Sapir-Whorf hypothesis holds that our thoughts are shaped by our native language, and that speakers of different languages therefore think differently. This hypothesis is controversial in part because it appears to deny the possibility of a universal groundwork for human cognition, and in part because some findings taken to support it have not reliably replicated. We argue that considering this hypothesis through the lens of probabilistic inference has the potential to resolve both issues, at least with respect to certain prominent findings in the domain of color cognition. We explore a probabilistic model that is grounded in a presumed universal perceptual color space and in language-specific categories over that space. The model predicts that categories will most clearly affect color memory when perceptual information is uncertain. In line with earlier studies, we show that this model accounts for language-consistent biases in color reconstruction from memory in English speakers, modulated by uncertainty. We also show, to our knowledge for the first time, that such a model accounts for influential existing data on cross-language differences in color discrimination from memory, both within and across categories. We suggest that these ideas may help to clarify the debate over the Sapir-Whorf hypothesis.

Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge.

We describe and analyze a simple and effective algorithm for sequence segmentation applied to speech processing tasks. We propose a neural architecture that is composed of two modules trained jointly: a recurrent neural network (RNN) module and a structured prediction model. The RNN outputs are considered as feature functions to the structured model. The overall model is trained with a structured loss function which can be designed to the given segmentation task. We demonstrate the effectiveness of our method by applying it to two simple tasks commonly used in phonetic studies: word segmentation and voice onset time segmentation. Results suggest the proposed model is superior to previous methods, obtaining state-of-the-art results on the tested datasets.

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Interactive models of language production predict that it should be possible to observe long-distance interactions; effects that arise at one level of processing influence multiple subsequent stages of representation and processing. We examine the hypothesis that disruptions arising in nonform-based levels of planning-specifically, lexical selection-should modulate articulatory processing. A novel automatic phonetic analysis method was used to examine productions in a paradigm yielding both general disruptions to formulation processes and, more specifically, overt errors during lexical selection. This analysis method allowed us to examine articulatory disruptions at multiple levels of analysis, from whole words to individual segments. Baseline performance by young adults was contrasted with young speakers' performance under time pressure (which previous work has argued increases interaction between planning and articulation) and performance by older adults (who may have difficulties inhibiting nontarget representations, leading to heightened interactive effects). The results revealed the presence of interactive effects. Our new analysis techniques revealed these effects were strongest in initial portions of responses, suggesting that speech is initiated as soon as the first segment has been planned. Interactive effects did not increase under response pressure, suggesting interaction between planning and articulation is relatively fixed. Unexpectedly, lexical selection disruptions appeared to yield some degree of facilitation in articulatory processing (possibly reflecting semantic facilitation of target retrieval) and older adults showed weaker, not stronger interactive effects (possibly reflecting weakened connections between lexical and form-level representations). (PsycINFO Database Record