Publications

Abstract

Do individuals differ in how efficiently they process non-native sounds? To what extent do these differences relate to individual variability in sound-learning aptitude? We addressed these questions by assessing the sound-learning abilities of Dutch native speakers as they were trained on non-native tone contrasts. We used fMRI repetition suppression to the non-native tones to measure participants' neuronal processing efficiency before and after training. Although all participants improved in tone identification with training, there was large individual variability in learning performance. A repetition suppression effect to tone was found in the bilateral inferior frontal gyri (IFGs) before training. No whole-brain effect was found after training; a region-of-interest analysis, however, showed that, after training, repetition suppression to tone in the left IFG correlated positively with learning. That is, individuals who were better in learning the non-native tones showed larger repetition suppression in this area. Crucially, this was true even before training. These findings add to existing evidence that the left IFG plays an important role in sound learning and indicate that individual differences in learning aptitude stem from differences in the neuronal efficiency with which non-native sounds are processed.

Abstract

This commentary on Gow and Olson [2015. Sentential influences on acoustic-phonetic processing: A Granger causality analysis of multimodal imaging data. Language, Cognition and Neuroscience. doi:10.1080/23273798.2015.1029498] questions in three ways their conclusion that speech perception is based on interactive processing. First, it is not clear that the data presented by Gow and Olson reflect normal speech recognition. Second, Gow and Olson's conclusion depends on still-debated assumptions about the functions performed by specific brain regions. Third, the results are compatible with feedforward models of speech perception and appear inconsistent with models in which there are online interactions about phonological content. We suggest that progress in the neuroscience of speech perception requires the generation of testable hypotheses about the function(s) performed by inter-regional connections

Abstract

Speech perception involves prediction, but how is that prediction implemented? In cognitive models prediction has often been taken to imply that there is feedback of activation from lexical to pre-lexical processes as implemented in interactive-activation models (IAMs). We show that simple activation feedback does not actually improve speech recognition. However, other forms of feedback can be beneficial. In particular, feedback can enable the listener to adapt to changing input, and can potentially help the listener to recognise unusual input, or recognise speech in the presence of competing sounds. The common feature of these helpful forms of feedback is that they are all ways of optimising the performance of speech recognition using Bayesian inference. That is, listeners make predictions about speech because speech recognition is optimal in the sense captured in Bayesian models.

Abstract

The social significance of recognizing the person who talks to us is obvious, but the neural mechanisms that mediate talker identification are unclear. Regions along the bilateral superior temporal sulcus (STS) and the inferior frontal cortex (IFC) of the human brain are selective for voices, and they are sensitive to rapid voice changes. Although it has been proposed that voice recognition is supported by prototype-centered voice representations, the involvement of these category-selective cortical regions in the neural coding of such "mean voices" has not previously been demonstrated. Using fMRI in combination with a voice identity learning paradigm, we show that voice-selective regions are involved in the mean-based coding of voice identities. Voice typicality is encoded on a supra-individual level in the right STS along a stimulus-dependent, identity-independent (i.e., voice-acoustic) dimension, and on an intra-individual level in the right IFC along a stimulus-independent, identity-dependent (i.e., voice identity) dimension. Voice recognition therefore entails at least two anatomically separable stages, each characterized by neural mechanisms that reference the central tendencies of voice categories.

Abstract

Are there bi-directional influences between speech perception and music perception? An answer to this question is essential for understanding the extent to which the speech and music that we hear are processed by domain-general auditory processes and/or by distinct neural auditory mechanisms. This review summarizes a large body of behavioral and neuroscientific findings which suggest that the musical experience of trained musicians does modulate speech processing, and a sparser set of data, largely on pitch processing, which suggest in addition that linguistic experience, in particular learning a tone language, modulates music processing. Although research has focused mostly on music on speech effects, we argue that both directions of influence need to be studied, and conclude that the picture which thus emerges is one of mutual interaction across domains. In particular, it is not simply that experience with spoken language has some effects on music perception, and vice versa, but that because of shared domain-general subcortical and cortical networks, experiences in both domains influence behavior in both domains.

Abstract

Multivariate pattern classification methods are increasingly applied to neuroimaging data in the context of both fundamental research and in brain-computer interfacing approaches. Such methods provide a framework for interpreting measurements made at the single-trial level with respect to a set of two or more distinct mental states. Here, we define an approach in which the output of a binary classifier trained on data from an auditory mismatch paradigm can be used for online tracking of perception and as a neurofeedback signal. The auditory mismatch paradigm is known to induce distinct perceptual states related to the presentation of high- and low-probability stimuli, which are reflected in event-related potential (ERP) components such as the mismatch negativity (MMN). The first part of this paper illustrates how pattern classification methods can be applied to data collected in an MMN paradigm, including discussion of the optimization of preprocessing steps, the interpretation of features and how the performance of these methods generalizes across individual participants and measurement sessions. We then go on to show that the output of these decoding methods can be used in online settings as a continuous index of single-trial brain activation underlying perceptual discrimination. We conclude by discussing several potential domains of application, including neurofeedback, cognitive monitoring and passive brain-computer interfaces

Abstract

Brain-computer interfaces (BCIs) are systems that use real-time analysis of neuroimaging data to determine the mental state of their user for purposes such as providing neurofeedback. Here, we investigate the feasibility of a BCI based on speech perception. Multivariate pattern classification methods were applied to single-trial EEG data collected during speech perception by native and non-native speakers. Two principal questions were asked: 1) Can differences in the perceived categories of pairs of phonemes be decoded at the single-trial level? 2) Can these same categorical differences be decoded across participants, within or between native-language groups? Results indicated that classification performance progressively increased with respect to the categorical status (within, boundary or across) of the stimulus contrast, and was also influenced by the native language of individual participants. Classifier performance showed strong relationships with traditional event-related potential measures and behavioral responses. The results of the cross-participant analysis indicated an overall increase in average classifier performance when trained on data from all participants (native and non-native). A second cross-participant classifier trained only on data from native speakers led to an overall improvement in performance for native speakers, but a reduction in performance for non-native speakers. We also found that the native language of a given participant could be decoded on the basis of EEG data with accuracy above 80%. These results indicate that electrophysiological responses underlying speech perception can be decoded at the single-trial level, and that decoding performance systematically reflects graded changes in the responses related to the phonological status of the stimuli. This approach could be used in extensions of the BCI paradigm to support perceptual learning during second language acquisition

Abstract

What is the relative salience of different aspects of word meaning in the developing lexicon? The current study examines the time-course of retrieval of semantic and color knowledge associated with words during toddler word recognition: at what point do toddlers orient towards an image of a yellow cup upon hearing color-matching words such as “banana” (typically yellow) relative to unrelated words (e.g., “house”)? Do children orient faster to semantic matching images relative to color matching images, e.g., orient faster to an image of a cookie relative to a yellow cup upon hearing the word “banana”? The results strongly suggest a prioritization of semantic information over color information in children’s word-referent mappings. This indicates that, even for natural objects (e.g., food, animals that are more likely to have a prototypical color), semantic knowledge is a more salient aspect of toddler's word meaning than color knowledge. For 24-month-old Dutch toddlers, bananas are thus more edible than they are yellow.

Abstract

Recent evidence shows that listeners use abstract prelexical units in speech perception. Using the phenomenon of lexical retuning in speech processing, we ask whether those units are necessarily phonemic. Dutch listeners were exposed to a Dutch speaker producing ambiguous phones between the Dutch syllable-final allophones approximant [r] and dark [l]. These ambiguous phones replaced either final /r/ or final /l/ in words in a lexical-decision task. This differential exposure affected perception of ambiguous stimuli on the same allophone continuum in a subsequent phonetic-categorization test: Listeners exposed to ambiguous phones in /r/-final words were more likely to perceive test stimuli as /r/ than listeners with exposure in /l/-final words. This effect was not found for test stimuli on continua using other allophones of /r/ and /l/. These results confirm that listeners use phonological abstraction in speech perception. They also show that context-sensitive allophones can play a role in this process, and hence that context-insensitive phonemes are not necessary. We suggest there may be no one unit of perception

Abstract

This study reports effects of a high-variability training procedure on nonnative learning of a Japanese geminate-singleton fricative contrast. Thirty native speakers of Dutch took part in a 5-day training procedure in which they identified geminate and singleton variants of the Japanese fricative /s/. Participants were trained with either many repetitions of a limited set of words recorded by a single speaker (low-variability training) or with fewer repetitions of a more variable set of words recorded by multiple speakers (high-variability training). Both types of training enhanced identification of speech but not of nonspeech materials, indicating that learning was domain specific. High-variability training led to superior performance in identification but not in discrimination tests, and supported better generalization of learning as shown by transfer from the trained fricatives to the identification of untrained stops and affricates. Variability thus helps nonnative listeners to form abstract categories rather than to enhance early acoustic analysis.

Abstract

Three experiments investigated whether extrinsic vowel normalization takes place largely at a categorical or a precategorical level of processing. Traditional vowel normalization effects in categorization were replicated in Experiment 1: Vowels taken from an [ɪ]-[ε] continuum were more often interpreted as /ɪ/ (which has a low first formant, F (1)) when the vowels were heard in contexts that had a raised F (1) than when the contexts had a lowered F (1). This was established with contexts that consisted of only two syllables. These short contexts were necessary for Experiment 2, a discrimination task that encouraged listeners to focus on the perceptual properties of vowels at a precategorical level. Vowel normalization was again found: Ambiguous vowels were more easily discriminated from an endpoint [ε] than from an endpoint [ɪ] in a high-F (1) context, whereas the opposite was true in a low-F (1) context. Experiment 3 measured discriminability between pairs of steps along the [ɪ]-[ε] continuum. Contextual influences were again found, but without discrimination peaks, contrary to what was predicted from the same participants' categorization behavior. Extrinsic vowel normalization therefore appears to be a process that takes place at least in part at a precategorical processing level.

Abstract

We investigated how the strength of a foreign accent and varying types of experience with foreign-accented speech influence the recognition of accented words. In Experiment 1, native Dutch listeners with limited or extensive prior experience with German-accented Dutch completed a cross-modal priming experiment with strongly, medium, and weakly accented words. Participants with limited experience were primed by the medium and weakly accented words, but not by the strongly accented words. Participants with extensive experience were primed by all accent types. In Experiments 2 and 3, Dutch listeners with limited experience listened to a short story before doing the cross-modal priming task. In Experiment 2, the story was spoken by the priming task speaker and either contained strongly accented words or did not. Strongly accented exposure led to immediate priming by novel strongly accented words, while exposure to the speaker without strongly accented tokens led to priming only in the experiment’s second half. In Experiment 3, listeners listened to the story with strongly accented words spoken by a different German-accented speaker. Listeners were primed by the strongly accented words, but again only in the experiment’s second half. Together, these results show that adaptation to foreign-accented speech is rapid but depends on accent strength and on listener familiarity with those strongly accented words.

Abstract

This paper presents lexical statistics on the pattern of occurrence of words embedded in other words. We report the results of an analysis of 25000 words, varying in length from two to six syllables, extracted from a phonetically-coded English dictionary (The Longman Dictionary of Contemporary English). Each syllable, and each string of syllables within each word was checked against the dictionary. Two analyses are presented: the first used a complete list of polysyllables, with look-up on the entire dictionary; the second used a sublist of content words, counting only embedded words which were themselves content words. The results have important implications for models of human speech recognition. The efficiency of these models depends, in different ways, on the number and location of words within words.