Our main goal is to provide you with data because you know what you want to do with it. Still, we give some information regarding typical MIR tasks below. We hope to provide snippets of code and benchmarks results to help you getting started. If you want to provide additional information / link to your code / new results / new tasks, please send us an email! We also try to maintain an informal list of publications that use the dataset.
Kaggle is a platform for data prediction competitions. Companies, organizations and researchers post their data and have it scrutinized by the world's best statisticians.
Werdende Eltern haben die quälende Wahl: Franz wie der Großvater oder Ronaldo wie der Fußballstar? Die Namenssuche fällt den Paaren immer schwerer. Informatiker der Universität Würzburg unterstützen Paare auf der Suche nach dem perfekten Namen jetzt mit einer Internetplattform, die helfen soll, den richtigen Namen für den Nachwuchs zu finden.
This research paper explains how increasing and improving practitioners’ knowledge of the importance and value of speech, language and communication skills contributes to advancement of educational, social and emotional competences; focus was on development for children in the Early Years. Proposed is the necessity to embed speech, language and communication development in practice, and the provision of a language and communication rich environment is considered a key strategy to influencing progress. The paper describes a research project that was subsequently evaluated using a multiple-method approach to afford a comprehensive analysis of findings. Outcomes were to highlight necessity for improvement of knowledge of less experienced practitioners, and added reinforcement for those who were relatively proficient; further, it was suggested that effective mentoring was required to maintain wide-ranging and continual growth of practitioners’ expertise. Development of confidence in subject knowledge was also essential in providing a child-initiated approach to learning; this, it claims, would enhance the fostering of a learning community which would place greater importance on the requirement for enhancement of speech, language and communication skills.
mendation service which can be called via HTTP by BibSonomy's recommender when a user posts a bookmark or publication. All participating recommenders are called on each posting process, one of them is choosen to actually deliver the results to the user. We can then measure
This year's discovery challenge presents two tasks in the new area
of social bookmarking. One task covers spam detection and
the other covers tag recommendations. As we are hosting the social bookmark and
publication sharing system BibSonomy, we are able to provide a dataset
of BibSonomy for the challenge. A training dataset for both tasks is provided at the beginning of the competition.
The test dataset will be released 48 hours before the final deadline. Due to a very tight schedule we cannot grant any deadline
extension.
The presentation of the results will take place at the ECML/PKDD workshop where the top teams are
invited to present their approaches and results.
The Natural Language Decathlon (decaNLP) is a new benchmark for studying general NLP models that can perform a variety of complex, natural language tasks.
There are currently few datasets appropriate for training and evaluating models for non-goal-oriented dialogue systems (chatbots); and equally problematic, there is currently no standard procedure for evaluating such models beyond the classic Turing test.
The aim of our competition is therefore to establish a concrete scenario for testing chatbots that aim to engage humans, and become a standard evaluation tool in order to make such systems directly comparable.
R. Jäschke, A. Hotho, F. Mitzlaff, и G. Stumme. Recommender Systems for the Social Web, том 32 из Intelligent Systems Reference Library, Springer, Berlin/Heidelberg, (2012)
J. Yamagishi, T. Nose, H. Zen, T. Toda, и K. Tokuda. Proceedings of the 2008 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), стр. 3957-3960. Las Vegas, NV, USA, (марта 2008)