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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 A New Dataset and Efficient Baselines for Document-level Text Simplification in German ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ebling, Sarah; Kew, Tannon. - : Underline Science Inc., 2021 BASE Show details 2 Benchmarking Automated Review Response Generation for the Hospitality Domain ... Kew, Tannon; Amsler, Michael; Ebling, Sarah. - : Association for Computational Linguistics, 2020 BASE Show details 3 ASR for Non-standardised Languages with Dialectal Variation: the case of Swiss German ... The 28th International Conference on Computational Linguistics 2020; Kew, Tannon; Nigmatulina, Iuliia; Samardzic, Tanja. - : Underline Science Inc., 2020 Abstract: Strong regional variation, together with the lack of standard orthography, makes Swiss German automatic speech recognition (ASR) particularly difficult in a multi-dialectal setting. This paper focuses on one of the many challenges, namely, the choice of the output text to represent non-standardised Swiss German. We investigate two potential options: a) dialectal writing – approximate phonemic transcriptions that provide close correspondence between grapheme labels and the acoustic signal but are highly inconsistent and b) normalised writing – transcriptions resembling standard German that are relatively consistent but distant from the acoustic signal. To find out which writing facilitates Swiss German ASR, we build several systems using the Kaldi toolkit and a dataset covering 14 regional varieties. A formal comparison shows that the system trained on the normalised transcriptions achieves better results in word error rate (WER) (29.39\%) but underperforms at the character level, suggesting dialectal ... Keyword: Natural Language Processing; Neural Network URL: https://underline.io/lecture/6514-asr-for-non-standardised-languages-with-dialectal-variation-the-case-of-swiss-german https://dx.doi.org/10.48448/smmb-0641 BASE Hide details 4 Benchmarking Automated Review Response Generation for the Hospitality Domain ... The 28th International Conference on Computational Linguistics 2020; Kew, Tannon. - : Underline Science Inc., 2020 BASE Show details 5 Benchmarking Automated Review Response Generation for the Hospitality Domain Kew, Tannon; Amsler, Michael; Ebling, Sarah In: Kew, Tannon; Amsler, Michael; Ebling, Sarah (2020). Benchmarking Automated Review Response Generation for the Hospitality Domain. In: Workshop on Natural Language Processing in E-Commerce, Barcelona, Spain, 12 December 2020. Association for Computational Linguistics, 43-52. (2020) BASE Show details 6 Modelling large parallel corpora. The Zurich Parallel Corpus Collection ... Graën, Johannes; Kew, Tannon; Shaitarova, Anastassia. - : Leibniz-Institut für Deutsche Sprache, 2019 BASE Show details 7 Modelling Large Parallel Corpora: The Zurich Parallel Corpus Collection Graën, Johannes; Kew, Tannon; Shaitarova, Anastassia... In: Graën, Johannes; Kew, Tannon; Shaitarova, Anastassia; Volk, Martin (2019). Modelling Large Parallel Corpora: The Zurich Parallel Corpus Collection. In: Challenges in the Management of Large Corpora (CMLC-7), Cardiff, Wales, 22 July 2019 - 22 July 2019. (2019) BASE Show details

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