Search Results for author: Marius Miron

Found 7 papers, 4 papers with code

ISPA: Inter-Species Phonetic Alphabet for Transcribing Animal Sounds

1 code implementation5 Feb 2024 Masato Hagiwara, Marius Miron, Jen-Yu Liu

Traditionally, bioacoustics has relied on spectrograms and continuous, per-frame audio representations for the analysis of animal sounds, also serving as input to machine learning models.

Music Rearrangement Using Hierarchical Segmentation

1 code implementation12 May 2023 Christos Plachouras, Marius Miron

Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration.

Segmentation

Assessing Algorithmic Biases for Musical Version Identification

no code implementations30 Sep 2021 Furkan Yesiler, Marius Miron, Joan Serrà, Emilia Gómez

Version identification (VI) systems now offer accurate and scalable solutions for detecting different renditions of a musical composition, allowing the use of these systems in industrial applications and throughout the wider music ecosystem.

Attribute Information Retrieval +2

Soundata: A Python library for reproducible use of audio datasets

no code implementations26 Sep 2021 Magdalena Fuentes, Justin Salamon, Pablo Zinemanas, Martín Rocamora, Genís Paja, Irán R. Román, Marius Miron, Xavier Serra, Juan Pablo Bello

Soundata is a Python library for loading and working with audio datasets in a standardized way, removing the need for writing custom loaders in every project, and improving reproducibility by providing tools to validate data against a canonical version.

Addressing multiple metrics of group fairness in data-driven decision making

1 code implementation10 Mar 2020 Marius Miron, Songül Tolan, Emilia Gómez, Carlos Castillo

The Fairness, Accountability, and Transparency in Machine Learning (FAT-ML) literature proposes a varied set of group fairness metrics to measure discrimination against socio-demographic groups that are characterized by a protected feature, such as gender or race. Such a system can be deemed as either fair or unfair depending on the choice of the metric.

BIG-bench Machine Learning Decision Making +1

Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour

no code implementations7 Jun 2018 Emilia Gómez, Carlos Castillo, Vicky Charisi, Verónica Dahl, Gustavo Deco, Blagoj Delipetrev, Nicole Dewandre, Miguel Ángel González-Ballester, Fabien Gouyon, José Hernández-Orallo, Perfecto Herrera, Anders Jonsson, Ansgar Koene, Martha Larson, Ramón López de Mántaras, Bertin Martens, Marius Miron, Rubén Moreno-Bote, Nuria Oliver, Antonio Puertas Gallardo, Heike Schweitzer, Nuria Sebastian, Xavier Serra, Joan Serrà, Songül Tolan, Karina Vold

The workshop gathered an interdisciplinary group of experts to establish the state of the art research in the field and a list of future research challenges to be addressed on the topic of human and machine intelligence, algorithm's potential impact on human cognitive capabilities and decision making, and evaluation and regulation needs.

Decision Making

Overcoming catastrophic forgetting with hard attention to the task

2 code implementations ICML 2018 Joan Serrà, Dídac Surís, Marius Miron, Alexandros Karatzoglou

In this paper, we propose a task-based hard attention mechanism that preserves previous tasks' information without affecting the current task's learning.

Continual Learning Hard Attention

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