Concept

Word2vec

Publications associées (95)

From Research to Reality: Evaluation of a Single-Computer Real-Time LVCSR System for Speech-Based Retrieval

Philip Neil Garner, Andrei Popescu-Belis, Nan Li, Maryam Habibi

This paper presents a series of tests that were performed on a state-of-the-art real-time automatic speech recognition system for English, in a single-computer implementation. As the intention is to use the system for speech-based query-free document retri ...

Idiap2017

Associate Latent Encodings in Learning from Demonstrations

Aude Billard, Hang Yin, Ana Paiva

We contribute a learning from demonstration approach for robots to acquire skills from multi-modal high-dimensional data. Both latent representations and associations of different modalities are proposed to be jointly learned through an adapted variational ...

2017

Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features

Martin Jaggi, Matteo Pagliardini, Prakhar Gupta

The recent tremendous success of unsupervised word embeddings in a multitude of applications raises the obvious question if similar methods could be derived to improve embeddings (i.e. semantic representations) of word sequences as well. We present a simpl ...

2017

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017

Semi-supervised Learning with Semantic Knowledge Extraction for Improved Speech Recognition in Air Traffic Control

Petr Motlicek

Automatic Speech Recognition (ASR) can introduce higher levels of automation into Air Traffic Control (ATC), where spoken language is still the predominant form of communication. While ATC uses standard phraseology and a limited vocabulary, we need to adap ...

2017

Semi-supervised Learning with Semantic Knowledge Extraction for Improved Speech Recognition in Air Traffic Control

Petr Motlicek

Idiap2017

Characterizing and Improving Stability in Neural Style Transfer

Alexandre Massoud Alahi, Agrim Gupta

Recent progress in style transfer on images has focused on improving the quality of stylized images and speed of methods. However, real-time methods are highly unstable resulting in visible flickering when applied to videos. In this work we characterize th ...

2017

Building Word Embeddings for Solving Natural Language Processing

Rémi Philippe Lebret

Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

École Polytechnique Fédérale de Lausanne2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

EPFL2016

Explicit Suggestion of Query Terms for News Search using Topic Models and Word Embeddings

Andrei Popescu-Belis, Parvaz Mahdabi

This report presents a study on assisting users in building queries to perform real-time searches in a news and social media monitoring system. The system accepts complex queries, and we assist the user by suggesting related keywords or entities. We do thi ...

Idiap2016

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