Today, speech technology is only available for a small fraction of the thousands of languages spoken around the world because traditional systems need to be trained on large amounts of annotated speech audio with transcriptions. Obtaining that kind of data for every human language and dialect is almost impossible.
Wav2vec works around this limitation by requiring little to no transcribed data. The model uses self-supervision to push the boundaries by learning from unlabeled training data. This enables speech recognition systems for many more languages and dialects, such as Kyrgyz and Swahili, which don’t have a lot of transcribed speech audio. Self-supervision is the key to leveraging unannotated data and building better systems.
Hello, I am currently searchin for a way to convert several Word documents into a single PDF file. The original Word documents are attachments to a One Order object in CRM 5.0, and I want to create an
Beautiful visualizations of how language differs among document types. - GitHub - JasonKessler/scattertext: Beautiful visualizations of how language differs among document types.
A. Balan. DEZVOLTAREA ECONOMICO-SOCIALĂ DURABILĂ A EUROREGIUNILOR ŞI A ZONELOR TRANSFRONTALIERE (SUSTAINABLE ECONOMIC AND SOCIAL DEVELOPMENT OF EUROREGIONS AND CROSS - BORDER AREAS), page 21-27. Iași, Performantica, (2021)(SILC).
F. Arnold, and R. Jäschke. Proceedings of the Workshop on Natural Language Processing for Digital Humanities at ICON 2021, page 55--63. NLP Association of India, (2021)
J. Verma, S. Agrawal, B. Patel, and A. Patel. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), 5 (1):
41 - 51(February 2016)
S. Jänicke, T. Efer, M. Büchler, and G. Scheuermann. Computer Vision, Imaging and Computer Graphics - Theory and Applications, page 153--171. Cham, Springer International Publishing, (2015)
R. Linden. Central and East European Politics: Changes and Challenges, Rowman & Littlefield Publishers, Lanham, Maryland, Vereinigte Staaten, 5. edition, (Eurobarometer).(2021)
L. Alipranti-Maratou. Families and Family Values in Society and Culture, Information Age Publishing, Charlotte, North Carolina, Vereinigte Staaten, (SILC).(2021)
C. Coppée, and W. Lahaye. Families and Family Values in Society and Culture, Information Age Publishing, Charlotte, North Carolina, Vereinigte Staaten, (SILC).(2021)
K. Cardiff. The Political Economy of Adjustment Throughout and Beyond the Eurozone Crisis: What Have We Learned?, Routledge, London, (Eurobarometer).(2020)
T. Graf. Sozialwissenschaftliche Studien des Zentrums für Militärgeschichte und Sozialwissenschaften der Bundeswehr Berliner Wissenschafts-Verlag, Berlin, (2020)(ISSP).
S. Bloehdorn, and A. Hotho. Proceedings of the MSW 2004 workshop at the 10th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, page 70-87. (August 2004)
C. Vögele, and U. Ohliger. SCM Studies in Communication and Media, 9 (4):
627-650(2020)https://doi.org/10.5771/2192-4007-2020-4-627. (Politbarometer) (GLES).
M. Hossen, M. Faiad, M. Chowdhury, and M. Islam. International Journal of Computer Science & Information Technology (IJCSIT), 10 (1):
95 - 105(February 2018)
S. Jänicke, T. Efer, M. Büchler, and G. Scheuermann. Computer Vision, Imaging and Computer Graphics - Theory and Applications, page 153--171. Cham, Springer International Publishing, (2015)
A. Asai, K. Hashimoto, H. Hajishirzi, R. Socher, and C. Xiong. (2019)cite arxiv:1911.10470Comment: Published as a conference paper at ICLR 2020. Code is available at https://github.com/AkariAsai/learning_to_retrieve_reasoning_paths.