Concept

Foundation models

Related publications (119)

Language model domain adaptation for automatic speech recognition

This report provides an overview of the work carried out in improving Language Model (LM) development used during the decoding of an Automatic Speech Recognition (ASR) system. The goal of this work is to develop a robust language model that can be adapted ...

Idiap2020

Musical Source Separation

Musical source separation is a complex topic that has been extensively explored in the signal processing community and has benefited greatly from recent machine learning research. Many deep learning models with impressive source separation quality have bee ...

2020

Fast Transformers with Clustered Attention

François Fleuret, Angelos Katharopoulos, Apoorv Vyas

Transformers have been proven a successful model for a variety of tasks in sequence modeling. However, computing the attention matrix, which is their key component, has quadratic complexity with respect to the sequence length, thus making them prohibitivel ...

2020

Lyrics-Conditioned Neural Melody Generation

Simon Canales, Yi Yu

Generating melody from lyrics to compose a song has been a very interesting research topic in the area of artificial intelligence and music, which tries to predict generative music relationship between lyrics and melody. In this demonstration paper, by exp ...

SPRINGER INTERNATIONAL PUBLISHING AG2020

Privacy-preserving and Personalized Federated Machine Learning for Medical Data

Felix Hans Michel Grimberg

The federated learning setting is prone to suffering from non-identically distributed data across participating agents. This gives rise to the task of model personalization, where agents collaborate to train several different machine learning models instea ...

2020

The SONATA data format for efficient description of large-scale network models

Eilif Benjamin Muller, Werner Alfons Hilda Van Geit, Jean-Denis Georges Emile Courcol, Michael Emiel Gevaert, Adrien Michel Achille Devresse, Juan Bautista Hernando Vieites

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation ...

PLOS2020

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

Boi Faltings, Diego Matteo Antognini

Today, recommender systems are an inevitable part of everyone's daily digital routine and are present on most internet platforms. State-of-the-art deep learning-based models require a large number of data to achieve their best performance. Many datasets fu ...

EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA2020

The MIDI Degradation Toolkit: Symbolic Music Augmentation and Correction

Andrew Philip McLeod

In this paper, we introduce the MIDI Degradation Toolkit (MDTK), containing functions which take as input a musical excerpt (a set of notes with pitch, onset time, and duration), and return a ``degraded'' version of that excerpt with some error (or errors) ...

2020

An Optimizing Multi-platform Source-to-source Compiler Framework for the NEURON MODeling Language

Felix Schürmann, James Gonzalo King, Michael Lee Hines, Pramod Shivaji Kumbhar, Jorge Blanco Alonso, Omar Awile, Liam Roger George Keegan

Domain-specific languages (DSLs) play an increasingly important role in the generation of high performing software. They allow the user to exploit domain knowledge for the generation of more efficient code on target architectures. Here, we describe a new c ...

Springer2020

Memory Augmented Neural Model for Incremental Session-based Recommendation

Boi Faltings, Fei Mi

Increasing concerns with privacy have stimulated interests in Session-based Recommendation (SR) using no personal data other than what is observed in the current browser session. Existing methods are evaluated in static settings which rarely occur in real- ...

2020

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