Search Results for author: Emilia Parada-Cabaleiro

Found 4 papers, 2 papers with code

A Temporal-oriented Broadcast ResNet for COVID-19 Detection

no code implementations31 Mar 2022 Xin Jing, Shuo Liu, Emilia Parada-Cabaleiro, Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang, Björn W. Schuller

Detecting COVID-19 from audio signals, such as breathing and coughing, can be used as a fast and efficient pre-testing method to reduce the virus transmission.

Computational Efficiency

Do Perceived Gender Biases in Retrieval Results Affect Relevance Judgements?

no code implementations3 Mar 2022 Klara Krieg, Emilia Parada-Cabaleiro, Markus Schedl, Navid Rekabsaz

This work investigates the effect of gender-stereotypical biases in the content of retrieved results on the relevance judgement of users/annotators.

Information Retrieval Retrieval

Grep-BiasIR: A Dataset for Investigating Gender Representation-Bias in Information Retrieval Results

1 code implementation19 Jan 2022 Klara Krieg, Emilia Parada-Cabaleiro, Gertraud Medicus, Oleg Lesota, Markus Schedl, Navid Rekabsaz

To facilitate the studies of gender bias in the retrieval results of IR systems, we introduce Gender Representation-Bias for Information Retrieval (Grep-BiasIR), a novel thoroughly-audited dataset consisting of 118 bias-sensitive neutral search queries.

Information Retrieval Retrieval

Predicting Music Relistening Behavior Using the ACT-R Framework

1 code implementation4 Aug 2021 Markus Reiter-Haas, Emilia Parada-Cabaleiro, Markus Schedl, Elham Motamedi, Marko Tkalcic, Elisabeth Lex

In this paper, we describe a psychology-informed approach to model and predict music relistening behavior that is inspired by studies in music psychology, which relate music preferences to human memory.

Recommendation Systems Retrieval

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