Concept

Étiquetage morpho-syntaxique

Publications associées (63)

AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...

New York2023

Interpreting Language Models Through Knowledge Graph Extraction

Martin Jaggi, Vinitra Swamy, Angeliki Romanou

Transformer-based language models trained on large text corpora have enjoyed immense popularity in the natural language processing community and are commonly used as a starting point for downstream tasks. While these models are undeniably useful, it is a c ...

2021

Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-specific Scaling

Milos Cernak, Paolo Prandoni, Natalia Nessler

In communication systems, it is crucial to estimate the perceived quality of audio and speech. The industrial standards for many years have been PESQ, 3QUEST, and POLQA, which are intrusive methods. This restricts the possibilities of using these metrics i ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Partially-supervised Mention Detection

James Henderson

Learning to detect entity mentions without using syntactic information can be useful for integration and joint optimization with other tasks. However, it is common to have partially annotated data for this problem. Here, we investigate two approaches to de ...

ACL2020

RSVQA: Visual Question Answering for Remote Sensing Data

Devis Tuia, Sylvain Lobry

This article introduces the task of visual question answering for remote sensing data (RSVQA). Remote sensing images contain a wealth of information, which can be useful for a wide range of tasks, including land cover classification, object counting, or de ...

2020

Graph-to-Graph Transformer for Transition-based Dependency Parsing

James Henderson, Alireza Mohammadshahi

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...

Association for Computational Linguistics2020

Dysarthric Speech Recognition with Lattice-Free MMI

Enno Hermann

Recognising dysarthric speech is a challenging problem as it differs in many aspects from typical speech, such as speaking rate and pronunciation. In the literature the focus so far has largely been on handling these variabilities in the framework of HMM/G ...

2020

Unsupervised Scalable Representation Learning for Multivariate Time Series

Martin Jaggi, Aymeric Daphnis Kévin Dieuleveut

Time series constitute a challenging data type for machine learning algorithms, due to their highly variable lengths and sparse labeling in practice. In this paper, we tackle this challenge by proposing an unsupervised method to learn universal embeddings ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2019

Decentralized clustering for node-variant graph filtering with graph diffusion LMS

Ali H. Sayed, Roula Nassif

In this work, we consider the problem of estimating the coefficients of linear shift-invariant FIR graph filters. We assume hybrid node-varying graph filters where the network is decomposed into clusters of nodes and, within each cluster, all nodes have th ...

IEEE2018

Simple Unsupervised Keyphrase Extraction using Sentence Embeddings

Martin Jaggi, Claudiu-Cristian Musat, Kamil Bennani-Smires

Keyphrase extraction is the task of automatically selecting a small set of phrases that best describe a given free text document. Keyphrases can be used for indexing, searching, aggregating and summarizing text documents, serving many automatic as well as ...

2018

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