Publications

Abstract

Introduction Speech research saw a dramatic change in paradigm in the 90-ies. While earlier the discussion was dominated by a phoneticians’ approach who knew about phenomena in the speech signal, the situation completely changed after stochastic machinery such as Hidden Markov Models [1] and Artificial Neural Networks [2] had been introduced. Speech processing was now dominated by a purely mathematic approach that basically ignored all existing knowledge about the speech production process and the perception mechanisms. The key was now to construct a large enough training set that would allow identifying the many free parameters of such stochastic engines. In case that the training set is representative and the annotations of the training sets are widely ‘correct’ we could assume to get a satisfyingly functioning recognizer. While the success of knowledge-based systems such as Hearsay II [3] was limited, the statistically based approach led to great improvements in recognition rates and to industrial applications.

Abstract

According to a widely-held view among various scholars, olfaction is inferior to other human senses. It is also believed by many that languages do not have words for describing smells. Data collected among the Maniq, a small population of nomadic foragers in southern Thailand, challenge the above claims and point to a great linguistic and cultural elaboration of odor. This article presents evidence of the importance of olfaction in indigenous rituals and beliefs, as well as in the lexicon. The results demonstrate the richness and complexity of the domain of smell in Maniq society and thereby challenge the universal paucity of olfactory terms and insignificance of olfaction for humans.

Abstract

We carried out the first study on the relationship between individual language aptitude and structural connectivity of language pathways in the adult brain. We measured four components of language aptitude (vocabulary learning, VocL; sound recognition, SndRec; sound-symbol correspondence, SndSym; and grammatical inferencing, GrInf) using the LLAMA language aptitude test (Meara, 2005). Spatial working memory (SWM), verbal working memory (VWM) and IQ were also measured as control factors. Diffusion Tensor Imaging (DTI) was employed to investigate the structural connectivity of language pathways in the perisylvian language network. Principal Component Analysis (PCA) on behavioural measures suggests that a general ability might be important to the first stages of L2 acquisition. It also suggested that VocL, SndSy and SWM are more closely related to general IQ than SndRec and VocL, and distinguished the tasks specifically designed to tap into L2 acquisition (VocL, SndRec,SndSym and GrInf) from more generic measures (IQ, SWM and VWM). Regression analysis suggested significant correlations between most of these behavioural measures and the structural connectivity of certain language pathways, i.e., VocL and BA47-Parietal pathway, SndSym and inter-hemispheric BA45 pathway, GrInf and BA45-Temporal pathway and BA6-Temporal pathway, IQ and BA44-Parietal pathway, BA47-Parietal pathway, BA47-Temporal pathway and inter-hemispheric BA45 pathway, SWM and inter-hemispheric BA6 pathway and BA47-Parietal pathway, and VWM and BA47-Temporal pathway. These results are discussed in relation to relevant findings in the literature.

Abstract

Set is widely used as a kind of basic data structure. However, when it is used for large scale data set the cost of storage, search and transport is overhead. The bloom filter uses a fixed size bit string to represent elements in a static set, which can reduce storage space and search cost that is a fixed constant. The time-space efficiency is achieved at the cost of a small probability of false positive in membership query. However, for many applications the space savings and locating time constantly outweigh this drawback. Dynamic bloom filter (DBF) can support concisely representation and approximate membership queries of dynamic set instead of static set. It has been proved that DBF not only possess the advantage of standard bloom filter, but also has better features when dealing with dynamic set. This paper proposes a time-dependent multiple bit-strings bloom filter (TMBF) which roots in the DBF and targets on dynamic incremental set. TMBF uses multiple bit-strings in time order to present a dynamic increasing set and uses backward searching to test whether an element is in a set. Based on the system logs from a real P2P file sharing system, the evaluation shows a 20% reduction in searching cost compared to DBF.

Abstract

Four experiments investigated the role of the syllable in Chinese spoken word production. Chen, Chen and Ferrand (2003) reported a syllable priming effect when primes and targets shared the first syllable using a masked priming paradigm in Chinese. Our Experiment 1 was a direct replication of Chen et al.'s (2003) Experiment 3 employing CV (e. g., /ba2.ying2/, strike camp) and CVG (e. g., /bai2.shou3/, white haired) syllable types. Experiment 2 tested the syllable priming effect using different syllable types: e. g., CV (/qi4.qiu2/, balloon) and CVN (/qing1.ting2/, dragonfly). Experiment 3 investigated this issue further using line drawings of common objects as targets that were preceded either by a CV (e. g., /qi3/, attempt), or a CVN (e. g., /qing2/, affection) prime. Experiment 4 further examined the priming effect by a comparison between CV or CVN priming and an unrelated priming condition using CV-NX (e. g., /mi2.ni3/, mini) and CVN-CX (e. g., /min2.ju1/, dwellings) as target words. These four experiments consistently found that CV targets were named faster when preceded by CV primes than when they were preceded by CVG, CVN or unrelated primes, whereas CVG or CVN targets showed the reverse pattern. These results indicate that the priming effect critically depends on the match between the structure of the prime and that of the first syllable of the target. The effect obtained in this study was consistent across different stimuli and different tasks (word and picture naming), and provides more conclusive and consistent data regarding the role of the syllable in Chinese speech production.

Abstract

Automatic Language Identification of written texts is a well-established area of research in Computational Linguistics. State-of-the-art algorithms often rely on n-gram character models to identify the correct language of texts, with good results seen for European languages. In this paper we propose the use of a character n-gram model and a word n-gram language model for the automatic classification of two written varieties of Portuguese: European and Brazilian. Results reached 0.998 for accuracy using character 4-grams.

Abstract

This study presents a new language identification model for pluricentric languages that uses n-gram language models at the character and word level. The model is evaluated in two steps. The first step consists of the identification of two varieties of Spanish (Argentina and Spain) and two varieties of French (Quebec and France) evaluated independently in binary classification schemes. The second step integrates these language models in a six-class classification with two Portuguese varieties.

Abstract

This article provides a first overview of some striking grammatical structures in Türk Idotscedilaret Dili (Turkish Sign Language, TID), the sign language used by the Deaf community in Turkey. The data are described with a typological perspective in mind, focusing on aspects of TID grammar that are typologically unusual across sign languages. After giving an overview of the historical, sociolinguistic and educational background of TID and the language community using this sign language, five domains of TID grammar are investigated in detail. These include a movement derivation signalling completive aspect, three types of nonmanual negation — headshake, backward head tilt, and puffed cheeks — and their distribution, cliticization of the negator NOT to a preceding predicate host sign, an honorific whole-entity classifier used to refer to humans, and a question particle, its history and current status in the language. A final evaluation points out the significance of these data for sign language research and looks at perspectives for a deeper understanding of the language and its history.

Abstract

Semantic unification, the process by which small blocks of semantic information are combined into a coherent utterance, has been studied with various types of tasks. However, whether the brain activations reported in these studies are attributed to semantic unification per se or to other task-induced concomitant processes still remains unclear. The neural basis for semantic unification in sentence comprehension was examined using event-related potentials (ERP) and functional Magnetic Resonance Imaging (fMRI). The semantic unification load was manipulated by varying the goodness of fit between a critical word and its preceding context (in high cloze, low cloze and violation sentences). The sentences were presented in a serial visual presentation mode. The participants were asked to perform one of three tasks: semantic congruency judgment (SEM), silent reading for comprehension (READ), or font size judgment (FONT), in separate sessions. The ERP results showed a similar N400 amplitude modulation by the semantic unification load across all of the three tasks. The brain activations associated with the semantic unification load were found in the anterior left inferior frontal gyrus (aLIFG) in the FONT task and in a widespread set of regions in the other two tasks. These results suggest that the aLIFG activation reflects a semantic unification, which is different from other brain activations that may reflect task-specific strategic processing.

Abstract

How does language comprehension interact with motor activity? We investigated the conditions under which comprehending an action sentence affects people's balance. We performed two experiments to assess whether sentences describing forward or backward movement modulate the lateral movements made by subjects who made sensibility judgments about the sentences. In one experiment subjects were standing on a balance board and in the other they were seated on a balance board that was mounted on a chair. This allowed us to investigate whether the action compatibility effect (ACE) is robust and persists in the face of salient incompatibilities between sentence content and subject movement. Growth-curve analysis of the movement trajectories produced by the subjects in response to the sentences suggests that the ACE is indeed robust. Sentence content influenced movement trajectory despite salient inconsistencies between implied and actual movement. These results are interpreted in the context of the current discussion of embodied, or grounded, language comprehension and meaning representation.

Abstract

This paper explores the expression of multiple entities in Turkish Sign Language (Türk İşaret Dili; TİD), a less well-studied sign language. It aims to provide a comprehensive description of the ways and frequencies in which entity plurality in this language is expressed, both within and outside the noun phrase. We used a corpus that includes both elicited and spontaneous data from native signers. The results reveal that most of the expressions of multiple entities in TİD are iconic, spatial strategies (i.e. localization and spatial plural predicate inflection) none of which, we argue, should be considered as genuine plural marking devices with the main aim of expressing plurality. Instead, the observed devices for localization and predicate inflection allow for a plural interpretation when multiple locations in space are used. Our data do not provide evidence that TİD employs (productive) morphological plural marking (i.e. reduplication) on nouns, in contrast to some other sign languages and many spoken languages. We relate our findings to expression of multiple entities in other signed languages and in spoken languages and discuss these findings in terms of modality effects on expression of multiple entities in human language.

Abstract

The Corpus NGT