Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Twitter during Pandemic"'
Questo contributo si propone di presentare il progetto TrAVaSI (Trattamento Automatico di Varietà Storiche di Italiano), il cui obiettivo è la creazione di risorse per il trattamento automatico di varietà storiche della lingua italiana, in partico
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::09c24adb4abd472949361c195c517ea5
http://books.openedition.org/aaccademia/8515
http://books.openedition.org/aaccademia/8515
We present the European Clinical Case Corpus (E3C) project, aimed at collecting and annotating a large corpus of clinical cases in five European languages (Italian, English, French, Spanish, and Basque). Project results include: (i) a freely availabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::299157f0690ebe730c345de969248fb8
http://books.openedition.org/aaccademia/8663
http://books.openedition.org/aaccademia/8663
Autor:
Papa, Sirio
Il contributo presenta una valutazione delle prestazioni di DeepL nella traduzione di testi specialistici dall’inglese all’italiano. La valutazione è stata condotta a livello di frase, su un campione di 108 frasi tratte da testi relativi ad ambi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::2a3cdfe1d9f1b41fa51ace0649f2cbda
http://books.openedition.org/aaccademia/8924
http://books.openedition.org/aaccademia/8924
Existing research on Authorship Attribution (AA) focuses on texts for which a lot of data is available (e.g novels), mainly in English. We approach AA via Authorship Verification on short Italian texts in two novel datasets, and analyze the interacti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::3495754f94dd3e4f58fc4b3c2c1e50a1
http://books.openedition.org/aaccademia/8880
http://books.openedition.org/aaccademia/8880
While text-only datasets are widely produced and used for research purposes, limitations set by image-based social media platforms like Instagram make it difficult for researchers to experiment with multimodal data. We therefore developed CREENDER, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::4a09953e5612e2ee7cf058fc7bb404e4
http://books.openedition.org/aaccademia/8825
http://books.openedition.org/aaccademia/8825
Modern personal assistants require to access unstructured information in order to successfully fulfill user requests. In this paper, we have studied the use of two machine learning components to design personal assistants: intent classification, to u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::683c52d06324d38e8fd9c3417bf7d5c9
http://books.openedition.org/aaccademia/8945
http://books.openedition.org/aaccademia/8945
Publikováno v:
Scopus-Elsevier
CLiC-it
CLiC-it
We present a new dataset of sentences extracted from the movie Forrest Gump, annotated with the emotions perceived by a group of subjects while watching the movie. We run experiments to predict these emotions using two classifiers, one based on a Sup
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55e83a9c2e8afc65519e7bcae53fa29a
http://books.openedition.org/aaccademia/8610
http://books.openedition.org/aaccademia/8610
We explore linguistic features that contribute to sarcasm detection. The linguistic features that we investigate are a combination of text and word complexity, stylistic and psychological features. We experiment with sarcastic tweets with and without
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::4b3fc6b69e5a93013ff1ab9db2a1f44e
http://books.openedition.org/aaccademia/8485
http://books.openedition.org/aaccademia/8485
Publikováno v:
A Case Study of Natural Gender Phenomena in Translation: A Comparison of Google Translate, Bing {M}icrosoft Translator and DeepL for English to Italian, French and Spanish
This paper presents the results of an evaluation of Google Translate, DeepL and Bing Microsoft Translator with reference to natural gender translation and provides statistics about the frequency of female, male and neutral forms in the translations o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddaab37785775229d2f290be9742c6ea
http://books.openedition.org/aaccademia/8844
http://books.openedition.org/aaccademia/8844
Publikováno v:
Sandro Pezzelle
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 ISBN: 9791280136336
CLiC-it
Scopus-Elsevier
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 ISBN: 9791280136336
CLiC-it
Scopus-Elsevier
We study how language use differs between dialogue partners in a visually grounded reference task when a referent is mutually identifiable by both interlocutors vs. when it is only available to one of them. In the latter case, the addressee needs to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f93226824c854e59cce261b6b595f33a
http://books.openedition.org/aaccademia/8600
http://books.openedition.org/aaccademia/8600