16 citations · 32 across the 8 of their papers we have counts for
8 papers
Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022): Workshop and Shared Task Report
Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella +3
We provide a summary of the fifth edition of the CASE workshop that is held in the scope of EMNLP 2022. The workshop consists of regular papers, two keynotes, working papers of sha…
Why So Down? The Role of Negative (and Positive) Pointwise Mutual Information in Distributional Semantics
Alexandre Salle, Aline Villavicencio
In distributional semantics, the pointwise mutual information () weighting of the cooccurrence matrix performs far better than raw counts. There is, however, an issue…
Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
Marcely Zanon Boito, Aline Villavicencio, Laurent Besacier
Since Bahdanau et al. [1] first introduced attention for neural machine translation, most sequence-to-sequence models made use of attention mechanisms [2, 3, 4]. While they produce…
Unsupervised Word Segmentation from Speech with Attention
Pierre Godard, Marcely Zanon-Boito, Lucas Ondel +4
We present a first attempt to perform attentional word segmentation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource,…
Incorporating Subword Information into Matrix Factorization Word Embeddings
Alexandre Salle, Aline Villavicencio
The positive effect of adding subword information to word embeddings has been demonstrated for predictive models. In this paper we investigate whether similar benefits can also be…
Unwritten Languages Demand Attention Too! Word Discovery with Encoder-Decoder Models
Marcely Zanon Boito, Alexandre Berard, Aline Villavicencio +1
Word discovery is the task of extracting words from unsegmented text. In this paper we examine to what extent neural networks can be applied to this task in a realistic unwritten l…
Restricted Recurrent Neural Tensor Networks: Exploiting Word Frequency and Compositionality
Alexandre Salle, Aline Villavicencio
Increasing the capacity of recurrent neural networks (RNN) usually involves augmenting the size of the hidden layer, with significant increase of computational cost. Recurrent neur…
Enhancing the LexVec Distributed Word Representation Model Using Positional Contexts and External Memory
Alexandre Salle, Marco Idiart, Aline Villavicencio
In this paper we take a state-of-the-art model for distributed word representation that explicitly factorizes the positive pointwise mutual information (PPMI) matrix using window s…