Publications

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.

Abstract

We report two experiments in which vowels and steady-state consonants served as targets in a speeded detection task. In the first experiment, two vowels were compared with one voiced and once unvoiced fricative. Response times (RTs) to the vowels were longer than to the fricatives. The error rate was higher for the consonants. Consonants in word-final position produced the shortest RTs, For the vowels, RT correlated negatively with target duration. In the second experiment, the same two vowel targets were compared with two nasals. This time there was no significant difference in RTs, but the error rate was still significantly higher for the consonants. Error rate and length correlated negatively for the vowels only. We conclude that RT differences between phonemes are independent of vocalic or consonantal status. Instead, we argue that the process of phoneme detection reflects more finely grained differences in acoustic/articulatory structure within the phonemic repertoire.

Abstract

Recent FMRI studies indicate that language related brain regions are engaged in artificial grammar (AG) processing. In the present study we investigate the Reber grammar by means of formal analysis and network simulations. We outline a new method for describing the network dynamics and propose an approach to grammar extraction based on the state-space dynamics of the network. We conclude that statistical frequency-based and rule-based acquisition procedures can be viewed as complementary perspectives on grammar learning, and more generally, that classical cognitive models can be viewed as a special case of a dynamical systems perspective on information processing

Abstract

The research presented in this dissertation examined the influence of prosodically-conditioned detail on the recognition of spoken words. The main finding is that subphonemic information in the speech signal that is conditioned by constituent-level prosodic structure can affect lexical processing systematically. It was shown that such information, as indicated by and estimated from the lengthening of speech sounds in the vicinity of prosodic boundaries, can help listeners to distinguish onset-embedded words (e.g. 'ham') from longer words that have this word embedded at their onset (e.g. 'hamster'). Furthermore, it was shown that variation in the realization of a spoken word that is associated with its position in the prosodic structure of an utterance can effect lexical processing. The pattern of competitor activation associated with the recognition of a monosyllabic spoken word in utterance-final position, where the realization of the word is strongly affected by the utterance boundary, is different from that associated with the recognition of the same word in utterance-medial position, where the realization of the word is less strongly affected by the following prosodic-word boundary. Taken together, the findings attest to the extraordinary sensitivity of the spoken-word recogntion system by demonstrating the relevance for lexical processing of very fine-grained phonetic detail conditioned by prosodic structure.

Abstract

A series of experiment tested Ekman’s (1992) hypothesis that there are a set of positive basic emotions that are expressed using vocal para-linguistic sounds, e.g. laughter and cheers. The proposed categories investigated were amusement, contentment, pleasure, relief and triumph. Behavioural testing using a forced-choice task indicated that participants were able to reliably recognize vocal expressions of the proposed emotions. A cross-cultural study in the preliterate Himba culture in Namibia confirmed that these categories are also recognized across cultures. A recognition test of acoustically manipulated emotional vocalizations established that the recognition of different emotions utilizes different vocal cues, and that these in turn differ from the cues used when comprehending speech. In a study using fMRI we found that relative to a signal correlated noise baseline, the paralinguistic expressions of emotion activated bilateral superior temporal gyri and sulci, lateral and anterior to primary auditory cortex, which is consistent with the processing of non linguistic vocal cues in the auditory ‘what’ pathway. Notably amusement was associated with greater activation extending into both temporal poles and amygdale and insular cortex. Overall, these results support the claim that ‘happiness’ can be fractionated into amusement, pleasure, relief and triumph.

Abstract

This paper addresses the issue of large-vocabulary recognition in a specific word class. We propose a two-pass strategy in which only major cities are explicitly represented in the first stage lexicon. An unknown word model encoded as a phone loop is used to detect OOV city names (referred to as rare city names). After which SpeM, a tool that can extract words and word-initial cohorts from phone graphs on the basis of a large fallback lexicon, provides an N-best list of promising city names on the basis of the phone sequences generated in the first stage. This N-best list is then inserted into the second stage lexicon for a subsequent recognition pass. Experiments were conducted on a set of spontaneous telephone-quality utterances each containing one rare city name. We tested the size of the N-best list and three types of language models (LMs). The experiments showed that SpeM was able to include nearly 85% of the correct city names into an N-best list of 3000 city names when a unigram LM, which also boosted the unigram scores of a city name in a given state, was used.

Abstract

RU Radboud Universiteit Nijmegen, 16 september 2005

Abstract

In this paper, we illustrate the close parallels between the research fields of human speech recognition (HSR) and automatic speech recognition (ASR) using a computational model of human word recognition, SpeM, which was built using techniques from ASR. We show that ASR has proven to be useful for improving models of HSR by relieving them of some of their shortcomings. However, in order to build an integrated computational model of all aspects of HSR, a lot of issues remain to be resolved. In this process, ASR algorithms and techniques definitely can play an important role.

Abstract

Miraña, an endangered Witotoan language spoken in the Colombian Amazon region, has an inventory of over 60 noun class markers, most of which denote the shape of nominal referents. Class markers in this language are ubiquitous in their uses for derivational purposes in nouns and for agreement marking in virtually all other nominal expressions, such as pronouns, numerals, demonstratives, and relative clauses, as well as in verbs. This study provides a comprehensive analysis of this system by giving equal attention to its morphosyntactic, semantic, and discourse-pragmatic properties. The particular properties of this system raise issues in a number of ongoing theoretical discussions, in particular the typology of systems of nominal classification and the typology of reference tracking.

Abstract

This paper investigates the interaction between acoustic scores and symbolic mismatch penalties in multi-pass speech decoding techniques that are based on the creation of a segment graph followed by a lexical search. The interaction between acoustic and symbolic mismatches determines to a large extent the structure of the search space of these multipass approaches. The background of this study is a recently developed computational model of human word recognition, called SpeM. SpeM is able to simulate human word recognition data and is built as a multi-pass speech decoder. Here, we focus on unravelling the structure of the search space that is used in SpeM and similar decoding strategies. Finally, we elaborate on the close relation between distances in this search space, and distance measures in search spaces that are based on a combination of acoustic and phonetic features.

Abstract

This dissertation focuses on syntactic comprehension problems in patients with Broca's aphasia from an electrophysiological perspective. The central objective of this dissertation was to further explore what syntax-related event-related brain potential (ERP) effects can reveal about the nature of the deficit that underlies syntactic comprehension problems in patients with Broca's aphasia. Chapter two to four describe experiments in which event-related brain potentials were recorded while subjects (Broca patients, non-aphasic patients with a right-hemisphere lesion, and healthy elderly controls) were presented with sentences that contained either violations of syntactic constraints or were syntactically correct. Chapter two investigates ERP effects of subject-verb agreement violations in the different subject groups, and seeks to answer the following questions: Do agrammatic comprehenders show sensitivity to subject-verb agreement violations as indicated by a syntax-related ERP effect? In addition, does the severity of the syntactic comprehension impairment in the Broca patients affect the ERP responses? Chapter three describes an investigation of whether Broca patients show sensitivity to violations of word order as indicated by a syntax-related ERP effect, and whether the ERP responses in the Broca patients are affected by the severity of their syntactic comprehension impairment. Chapter four reports on ERP effects of violations of word-category. In addition, also a semantic violation condition was added to track possible dissociations in the sensitivity to semantic and syntactic information in the Broca patients. Chapter five describes the development of a paradigm in which the electrophysiological approach and the classical sentence-picture matching approach are combined. In this chapter, the ERP method is applied to study on-line thematic role assignment in Broca patients during sentence-picture matching. Also the relation between ERP effects and behavioral responses is pursued. Finally, Chapter 6 provides a summary of the main findings of the experiments and a general discussion.