Spectral Characteristics of Schwa in Czech Accented English

The English central mid lax vowel (i.e., schwa) often contributes considerably to the sound differences between native and non-native speech. Many foreign speakers of English fail to reduce certain underlying vowels to schwa, which, on the suprasegmental level of description, affects the perceived rhythm of their speech. However, the problem of capturing quantitatively the differences between native and non-native schwa poses difficulties that, to this day, have been tackled only partially. We offer a technique of measurement in the acoustic domain that has not been probed properly as yet: the distribution of acoustic energy in the vowel spectrum. Our results show that spectral slope features measured in weak vowels discriminate between Czech and British speakers of English quite reliably. Moreover, the measurements of formant bandwidths turned out to be useful for the same task, albeit less direc

An algorithm for cross-lingual sense-clustering tested in a MT evaluation setting

Unsupervised sense induction methods offer a solution to the problem of scarcity of semantic resources. These methods automatically extract semantic information from textual data and create resources adapted to specific applications and domains of interest. In this paper, we present a clustering algorithm for cross-lingual sense induction which generates bilingual semantic inventories from parallel corpora. We describe the clustering procedure and the obtained resources. We then proceed to a large-scale evaluation by integrating the resources into a Machine Translation (MT) metric (METEOR). We show that the use of the data-driven sense-cluster inventories leads to better correlation with human judgments of translation quality, compared to precision-based metrics, and to improvements similar to those obtained when a handcrafted semantic resource is used

Dependency relations as source context in phrase-based SMT

The Phrase-Based Statistical Machine Translation (PB-SMT) model has recently begun to include source context modeling, under the assumption that the proper lexical choice of an ambiguous word can be determined from the context in which it appears. Various types of lexical and syntactic features such as words, parts-of-speech, and supertags have been explored as effective source context in SMT. In this paper, we show that position-independent syntactic dependency relations of the head of a source phrase can be modeled as useful source context to improve target phrase selection and thereby improve overall performance of PB-SMT. On a Dutch—English translation task, by combining dependency relations and syntactic contextual features (part-of-speech), we achieved a 1.0 BLEU (Papineni et al., 2002) point improvement (3.1% relative) over the baseline

Size Matters! Body Height and Labor Market Discrimination: A Cross-European Analysis

Taller workers earn on average higher salaries. Recent research has proposed cognitive abilities and social skills as explanations for the height-wage premium. Another possible mechanism, employer discrimination, has found little support. In this paper, we provide some evidence in favor of the discrimination hypothesis. Using a cross section of 13 countries, we show that there is a consistent height-wage premium across Europe and that it is largely due to occupational sorting. We show that height has a significant effect for the occupational sorting of employed workers but not for the self-employed. We interpret this result as evidence of employer discrimination in favor of taller workers. Our results are consistent with the theoretical predictions of recent models on statistical discrimination and employer learning.height, wage premium, discrimination, cognitive functions, occupational sorting

A MT System from Turkmen to Turkish employing finite state and statistical methods

In this work, we present a MT system from Turkmen to Turkish. Our system exploits the similarity of the languages by using a modified version of direct translation method. However, the complex inflectional and derivational morphology of the Turkic languages necessitate special treatment for word-by-word translation model. We also employ morphology-aware multi-word processing and statistical disambiguation processes in our system. We believe that this approach is valid for most of the Turkic languages and the architecture implemented using FSTs can be easily extended to those languages

The effect of L1 regional variation on the perception and production of standard L1 and L2 vowels

This study reports on the perception and production of Standard Dutch and Standard British English vowels by speakers of two regional varieties of Belgian Dutch (East Flemish and Brabantine) which differ in their vowel realizations. Twenty-four native speakers of Dutch performed two picture-naming tasks and two vowel categorization tasks, in which they heard Standard Dutch or English vowels and were asked to map these onto orthographic representations of Dutch vowels. The results of the Dutch production and categorization tasks revealed that the participants’ L1 regional variety importantly influenced their production and especially perception of vowels in the standard variety of their L1. The two groups also differed in how they assimilated non-native English vowels to native vowel categories, but no major differences could be observed in their productions of non-native vowels. The study therefore only partly confirms earlier studies showing that L1 regional variation may have an influence on the acquisition of non-native language varieties