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Linguistic query systems are special purpose IR applications. We present a novel state-of-the-art approach for the efficient exploitation of very large linguistic corpora, combining the advantages of relational database management systems (RDBMS) with the functional MapReduce programming model. Our implementation uses the German DEREKO reference corpus with multi-layer linguistic annotations and several types of text-specific metadata, but the proposed strategy is language-independent and adaptable to large-scale multilingual corpora.
The Manatee corpus management system on which the Sketch Engine is built is efficient, but unable to harness the power of today’s multiprocessor machines. We describe a new, compatible implementation of Manatee which we develop in the Go language and report on the performance gains that we obtained.
American English and German AI, AU observed in cognates such as Wein, wine, Haus, house are usually treated on a par, represented with the same initial vowel (cf. [ai], [au] for Am. Engl, and German [1]). Yet, acoustic measurements indicate differences as the relevant trajectories characteristically cross in Am. Engl, but not in German. These data may indicate consistency with the same initial target for these diphthongs in German, supporting the choice of the same Symbol /a/ in phonemic representation, as opposed to distinct targets (and distinct initial phonemes) in American English.
The English language has taken advantage of the Digital Revolution to establish itself as the global language; however, only 28.6 %of Internet users speak English as their native language. Machine Trans-lation (MT) is a powerful technology that can bridge this gap. In devel-opment since the mid-20th century, MT has become available to every Internet user in the last decade, due to free online MT services. This paper aims to discuss the implications that these tools may have for the privacy of their users and how they are addressed by EU data protec-tion law. It examines the data-flows in respect of the initial processing (both from the perspective of the user and the MT service provider) and potential further processing that may be undertaken by the MT service provider.
Our paper describes an experiment aimed to assessment of lexical coverage in web corpora in comparison with the traditional ones for two closely related Slavic languages from the lexicographers’ perspective. The preliminary results show that web corpora should not be considered ― inferior, but rather ― different.
Language attitudes may be differentiated into attitudes towards speakers and attitudes towards languages. However, to date, no systematic and differentiated instrument exists that measures attitudes towards language. Accordingly, we developed, validated, and applied the Attitudes Towards Languages (AToL) scale in four studies. In Study 1, we selected 15 items for the AToL scale, which represented the three dimensions of value, sound, and structure. The following studies replicated and validated the three-factor structure and differential mean profiles along the three dimensions for different languages (a) in a more diverse German sample (Study 2), (b) in different countries (Study 3), and (c) when participants based their evaluations on speech samples (Study 4). Moreover, we investigated the relation between the AToL dimensions and stereotypic speaker evaluations. Results confirm the reliability, validity, and generalizability of the AToL scale and its incremental value to mere speaker evaluations.