20 citations · 61 across the 9 of their papers we have counts for
9 papers
Variable-rate hierarchical CPC leads to acoustic unit discovery in speech
Santiago Cuervo, Adrian Łańcucki, Ricard Marxer +2
The success of deep learning comes from its ability to capture the hierarchical structure of data by learning high-level representations defined in terms of low-level ones. In this…
Contrastive prediction strategies for unsupervised segmentation and categorization of phonemes and words
Santiago Cuervo, Maciej Grabias, Jan Chorowski +4
We investigate the performance on phoneme categorization and phoneme and word segmentation of several self-supervised learning (SSL) methods based on Contrastive Predictive Coding…
Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw
Jan Chorowski, Grzegorz Ciesielski, Jarosław Dzikowski +6
We present a number of low-resource approaches to the tasks of the Zero Resource Speech Challenge 2021. We build on the unsupervised representations of speech proposed by the organ…
Named Entity Recognition and Linking Augmented with Large-Scale Structured Data
Paweł Rychlikowski, Bartłomiej Najdecki, Adrian Łańcucki +1
In this paper we describe our submissions to the 2nd and 3rd SlavNER Shared Tasks held at BSNLP 2019 and BSNLP 2021, respectively. The tasks focused on the analysis of Named Entiti…
Aligned Contrastive Predictive Coding
Jan Chorowski, Grzegorz Ciesielski, Jarosław Dzikowski +6
We investigate the possibility of forcing a self-supervised model trained using a contrastive predictive loss to extract slowly varying latent representations. Rather than producin…
A Talker Ensemble: the University of Wrocław's Entry to the NIPS 2017 Conversational Intelligence Challenge
Jan Chorowski, Adrian Łańcucki, Szymon Malik +3
We present Poetwannabe, a chatbot submitted by the University of Wrocław to the NIPS 2017 Conversational Intelligence Challenge, in which it ranked first ex-aequo. It is able to co…
On Multilingual Training of Neural Dependency Parsers
Michał Zapotoczny, Paweł Rychlikowski, Jan Chorowski
We show that a recently proposed neural dependency parser can be improved by joint training on multiple languages from the same family. The parser is implemented as a deep neural n…
Text-based Adventures of the Golovin AI Agent
Bartosz Kostka, Jaroslaw Kwiecien, Jakub Kowalski +1
The domain of text-based adventure games has been recently established as a new challenge of creating the agent that is both able to understand natural language, and acts intellige…
Read, Tag, and Parse All at Once, or Fully-neural Dependency Parsing
Jan Chorowski, Michał Zapotoczny, Paweł Rychlikowski
We present a dependency parser implemented as a single deep neural network that reads orthographic representations of words and directly generates dependencies and their labels. Un…