English Centering Diphthong Production By Polish Learners of English

The paper shows how British English centering diphthongs are adapted to the vowel space of Polish learners of English. The goal is to focus on complex vowels and the interaction of qualitative and quantitative features. Acoustic analysis revealed various processes used to overcome pronunciation difficulties: /j/ and /w/ breaking, /r/ insertion, substitutions of other vocalic qualities, changes in diphthong duration and diphthong phases duration, and changes in the rate of frequency change

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Alcohol Language Corpus

The Alcohol Language Corpus (ALC) is the first publicly available speech corpus comprising intoxicated and sober speech of 162 female and male German speakers. Recordings are done in the automotive environment to allow for the development of automatic alcohol detection and to ensure a consistent acoustic environment for the alcoholized and the sober recording. The recorded speech covers a variety of contents and speech styles. Breath and blood alcohol concentration measurements are provided for all speakers. A transcription according to SpeechDat/Verbmobil standards and disfluency tagging as well as an automatic phonetic segmentation are part of the corpus. An Emu version of ALC allows easy access to basic speech parameters as well as the us of R for statistical analysis of selected parts of ALC. ALC is available without restriction for scientific or commercial use at the Bavarian Archive for Speech Signals

Hungarian neutral vowels

In Hungarian, stems containing only front unrounded (neutral) vowels fall into two groups: one group taking front suffixes, the other taking back suffixes in vowel harmony. The distinction is traditionally thought of as purely lexical. Beňuš and Gafos (2007) have recently challenged this position, claiming that there are significant articulatory differences between the vowels in the two groups. Neutral vowels also occur in vacillating stems. These typically contain one back vowel and one or more neutral vowels, and accept both front and back suffixes, with extensive inter- and intra-speaker variation. Based on Beňuš and Gafos’s line of argument, the expectation is that vacillating stems will display a kind of phonetic realisation that is distinct from both harmonic and anti-harmonic stems. We present the results of an ongoing acoustic study on the acoustics of neutral vowels, partly re-creating Beňuš and Gafos’s conditions, but also including vacillating stems. To map the extent of individual and dialectal variation regarding vacillating stems, a grammaticality judgement test was also carried out on speakers of two dialects of Hungarian, crucially differing in the surface inventory of neutral vowels. We present our first findings about how this phonetic difference influences the phonological behaviour of vacillating stems

Towards predicting post-editing productivity

Machine translation (MT) quality is generally measured via automatic metrics, producing scores that have no meaning for translators who are required to post-edit MT output or for project managers who have to plan and budget for transla- tion projects. This paper investigates correlations between two such automatic metrics (general text matcher and translation edit rate) and post-editing productivity. For the purposes of this paper, productivity is measured via processing speed and cognitive measures of effort using eye tracking as a tool. Processing speed, average fixation time and count are found to correlate well with the scores for groups of segments. Segments with high GTM and TER scores require substantially less time and cognitive effort than medium or low-scoring segments. Future research involving score thresholds and confidence estimation is suggested

Eye-tracking as a measure of cognitive effort for post-editing of machine translation

The three measurements for post-editing effort as proposed by Krings (2001) have been adopted by many researchers in subsequent studies and publications. These measurements comprise temporal effort (the speed or productivity rate of post-editing, often measured in words per second or per minute at the segment level), technical effort (the number of actual edits performed by the post-editor, sometimes approximated using the Translation Edit Rate metric (Snover et al. 2006), again usually at the segment level), and cognitive effort. Cognitive effort has been measured using Think-Aloud Protocols, pause measurement, and, increasingly, eye-tracking. This chapter provides a review of studies of post-editing effort using eye-tracking, noting the influence of publications by Danks et al. (1997), and O’Brien (2006, 2008), before describing a single study in detail. The detailed study examines whether predicted effort indicators affect post-editing effort and results were previously published as Moorkens et al. (2015). Most of the eye-tracking data analysed were unused in the previou