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Statistical Natural Language Processing Group (Heidelberg University - Department of Computational Linguistics)
The Statistical Natural Language Processing Group is part of the Department of Computational Linguistics.
Our research addresses various aspects of the problem of the confusion of languages, by means of statistical learning techniques.
Research topics include the following:
  • Statistical machine translation, statistical parsing, question answering, information retrieval, learning-to-rank.
  • Statistical machine learning methods, especially unsupervised, semi-supervised and discriminative learning techniques.
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1 to 10 of 19 Results
Jun 13, 2020
Beilharz, Benjamin; Sun, Xin, 2019, "LibriVoxDeEn - A Corpus for German-to-English Speech Translation and Speech Recognition", https://doi.org/10.11588/data/TMEDTX, heiDATA, V2
This dataset is a corpus of sentence-aligned triples of German audio, German text, and English translation, based on German audio books. The corpus consists of over 100 hours of audio material and over 50k parallel sentences. The speech data are low in disfluencies because of the...
Gzip Archive - 20.3 GB - MD5: 9fb23ee878584f4cab717e348cdeeaaf
Data
Gzip Archive - 17.2 GB - MD5: daf33d0f1242bad5a623b061fbaa426d
Data
Markdown Text - 4.3 KB - MD5: 971f62ef7dc31254dfc0e25f14347bc1
Documentation
Jun 18, 2014
Hieber, Felix; Schamoni, Shigehiko; Sokolov, Artem; Riezler, Stefan, 2014, "WikiCLIR: A Cross-Lingual Retrieval Dataset from Wikipedia", https://doi.org/10.11588/data/10003, heiDATA, V1
WikiCLIR is a large-scale (German-English) retrieval data set for Cross-Language Information Retrieval (CLIR). It contains a total of 245,294 German single-sentence queries with 3,200,393 automatically extracted relevance judgments for 1,226,741 English Wikipedia articles as docu...
Plain Text - 1.8 KB - MD5: f2d15639b962977ea19a20308bccbfc4
README
Gzip Archive - 846.8 MB - MD5: 8f51894ff1c6ba2987d07dde62b3143d
data
data set
Jun 16, 2014
Wäschle, Katharina; Riezler, Stefan, 2014, "PatTR: Patent Translation Resource", https://doi.org/10.11588/data/10002, heiDATA, V3
PatTR is a sentence-parallel corpus extracted from the MAREC patent collection. The current version contains more than 22 million German-English and 18 million French-English parallel sentences collected from all patent text sections as well as 5 million German-French sentence pa...
Jun 16, 2014
Sokolov, Artem; Jehl Laura; Hieber Felix; Ruppert, Eugen; Riezler, Stefan, 2014, "BoostCLIR: JP-EN Relevance Marked Patent Corpus", https://doi.org/10.11588/data/10001, heiDATA, V1
BoostCLIR is a bilingual (Japanese-English) corpus of patent abstracts, extracted from the MAREC patent data, and the data from the NTCIR PatentMT workshop collections, accompanied with relevance judgements for the task of patent prior-art search. Important: The English side of t...
Gzip Archive - 241.8 MB - MD5: 35fde8d24e6e80bf932490549c991a3f
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