Publications associées à Mot

Novel Methods for Incorporating Prior Knowledge for Automatic Speech Assessment

Speech signal conveys several kinds of information such as a message, speaker identity, emotional state of the speaker and social state of the speaker. Automatic speech assessment is a broad area that refers to using automatic methods to predict human judg ...

EPFL2021

Explainable Phonology-based Approach for Sign Language Recognition and Assessment

Sandrine Tornay

Sign language technology, unlike spoken language technology, is an emerging area of research. Sign language technologies can help in bridging the gap between the Deaf community and the hearing community. One such computer-aided technology is sign language ...

EPFL2021

Broccoli: Sprinkling Lightweight Vocabulary Learning into Everyday Information Diets

Robert West

The learning of a new language remains to this date a cognitive task that requires considerable diligence and willpower, recent advances and tools notwithstanding. In this paper, we propose Broccoli, a new paradigm aimed at reducing the required effort by ...

ASSOC COMPUTING MACHINERY2020

Social babbling: The emergence of symbolic gestures and words

Aude Billard, Laura Bénédicte Marine Cohen

Language acquisition theories classically distinguish passive language understanding from active language production. However, recent findings show that brain areas such as Broca's region are shared in language understanding and production. Furthermore, th ...

PERGAMON-ELSEVIER SCIENCE LTD2018

Word Sense Consistency in Statistical and Neural Machine Translation

Xiao Pu

Different senses of source words must often be rendered by different words in the target language when performing machine translation (MT). Selecting the correct translation of polysemous words can be done based on the contexts of use. However, state-of-th ...

EPFL2018

Interplay between Narrative and Bodily Self in Access to Consciousness: No Difference between Self- and Non-self Attributes

Olaf Blanke, Andrea Serino, Roy Salomon, Jean-Paul Noel

The construct of the self is conceived as being fundamental in promoting survival. As such, extensive studies have documented preferential processing of self-relevant stimuli. For example, attributes that relate to the self are better encoded and retrieved ...

Frontiers Media2017

Word pair classification during imagined speech using direct brain recordings

José del Rocio Millán Ruiz, Inaki Asier Iturrate Gil, Stéphanie Martin

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used ...

Nature Research2016

Path to AWAKE: Evolution of the concept

Yiming Li, Hua Zhang, Gennady Plyushchev, Shuai Liu, Frank Zimmermann

This paper describes the conceptual steps in reaching the design of the AWAKE experiment currently under construction at CERN. We start with an introduction to plasma wakefield acceleration and the motivation for using proton drivers. We then describe the ...

Elsevier Science Bv2016

Sparse Modeling of Neural Network Posterior Probabilities for Exemplar-based Speech Recognition

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

In this paper, a compressive sensing (CS) perspective to exemplar-based speech processing is proposed. Relying on an analytical relationship between CS formulation and statistical speech recognition (Hidden Markov Models HMM), the automatic speech recognit ...

2016

Word Embeddings for 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 ...

EPFL2016

Rehabilitation of Count-based Models for Word Vector Representations

Rémi Philippe Lebret, Ronan Collobert

Recent works on word representations mostly rely on predictive models. Distributed word representations (aka word embeddings) are trained to optimally predict the contexts in which the corresponding words tend to appear. Such models have succeeded in captu ...

Springer International Publishing2015

Incremental Syllable-Context Phonetic Vocoding

Petr Motlicek, Philip Neil Garner, Milos Cernak

Current very low bit rate speech coders are, due to complexity limitations, designed to work off-line. This paper investigates incremental speech coding that operates real-time and incrementally (i.e., encoded speech depends only on already-uttered speech ...

2015

A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets

Boi Faltings, Pearl Pu Faltings, Claudiu-Cristian Musat, Marina Boia

Emoticons are widely used to express positive or negative sentiment on Twitter. We report on a study with live users to determine whether emoticons are used to merely emphasize the sentiment of tweets, or whether they are the main elements carrying the sen ...

IEEE2013

Expressiveness And Closure Properties For Quantitative Languages

Laurent Doyen

Weighted automata are nondeterministic automata with numerical weights on transitions. They can define quantitative languages L that assign to each word w a real number L(w). In the case of infinite words, the value of a run is naturally computed as the ma ...

2010

Enhancing posterior based speech recognition systems

Hamed Ketabdar

The use of local phoneme posterior probabilities has been increasingly explored for improving speech recognition systems. Hybrid hidden Markov model / artificial neural network (HMM/ANN) and Tandem are the most successful examples of such systems. In this ...

EPFL2008