Investigating the Usefulness of Generalized Word Representations in SMT

LIG System for WMT13 QE Task: Investigating the Usefulness of Features in Word Confidence Estimation for MT

Entity-Centric Contextual Affective Analysis

While contextualized word representations have improved state-of-the-art benchmarks in many NLP tasks, their potential usefulness for social-oriented tasks remains largely unexplored. We show how contextualized word embe…

Do speech foundation models really learn words?

Self-supervised speech foundation models are now used in a wide array of downstream applications, including traditional speech recognition and as the basis for tokens in speech-aware language models. Attempts to understa…

Ruminating Word Representations with Random Noise Masking

We introduce a training method for better word representation and performance, which we call \textbf{GraVeR} (\textbf{Gra}dual \textbf{Ve}ctor \textbf{R}umination). The method is to gradually and iteratively add random n…

WSRNet: Joint Spotting and Recognition of Handwritten Words

In this work, we present a unified model that can handle both Keyword Spotting and Word Recognition with the same network architecture. The proposed network is comprised of a non-recurrent CTC branch and a Seq2Seq branch…