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11/17/2022
Efficient Transformers with Dynamic Token Pooling
Transformers achieve unrivalled performance in modelling language, but r...
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06/05/2022
Variable-rate hierarchical CPC leads to acoustic unit discovery in speech
The success of deep learning comes from its ability to capture the hiera...
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10/29/2021
Contrastive prediction strategies for unsupervised segmentation and categorization of phonemes and words
We investigate the performance on phoneme categorization and phoneme and...
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06/22/2021
Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw
We present a number of low-resource approaches to the tasks of the Zero ...
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04/24/2021
Aligned Contrastive Predictive Coding
We investigate the possibility of forcing a self-supervised model traine...
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06/03/2020
A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning
Probabilistic Latent Variable Models (LVMs) provide an alternative to se...
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05/18/2020
Robust Training of Vector Quantized Bottleneck Models
In this paper we demonstrate methods for reliable and efficient training...
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10/16/2019
Conditional Invertible Flow for Point Cloud Generation
This paper focuses on a novel generative approach for 3D point clouds th...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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01/25/2019
Unsupervised speech representation learning using WaveNet autoencoders
We consider the task of unsupervised extraction of meaningful latent rep...
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01/14/2019
Towards Using Context-Dependent Symbols in CTC Without State-Tying Decision Trees
Deep neural acoustic models benefit from context dependent modeling of o...
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08/03/2018
Efficient Purely Convolutional Text Encoding
In this work, we focus on a lightweight convolutional architecture that ...
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05/21/2018
A Talker Ensemble: the University of Wrocław's Entry to the NIPS 2017 Conversational Intelligence Challenge
We present Poetwannabe, a chatbot submitted by the University of Wrocław...
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12/22/2017
On Using Backpropagation for Speech Texture Generation and Voice Conversion
Inspired by recent work on neural network image generation which rely on...
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12/05/2017
State-of-the-art Speech Recognition With Sequence-to-Sequence Models
Attention-based encoder-decoder architectures such as Listen, Attend, an...
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05/29/2017
On Multilingual Training of Neural Dependency Parsers
We show that a recently proposed neural dependency parser can be improve...
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03/24/2017
Sequence-to-Sequence Models Can Directly Translate Foreign Speech
We present a recurrent encoder-decoder deep neural network architecture ...
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01/23/2017
Regularizing Neural Networks by Penalizing Confident Output Distributions
We systematically explore regularizing neural networks by penalizing low...
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12/08/2016
Towards better decoding and language model integration in sequence to sequence models
The recently proposed Sequence-to-Sequence (seq2seq) framework advocates...
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11/28/2016
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
There exist many problem domains where the interpretability of neural ne...
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09/12/2016
Read, Tag, and Parse All at Once, or Fully-neural Dependency Parsing
We present a dependency parser implemented as a single deep neural netwo...
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05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
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08/18/2015
End-to-End Attention-based Large Vocabulary Speech Recognition
Many of the current state-of-the-art Large Vocabulary Continuous Speech ...
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06/24/2015
Attention-Based Models for Speech Recognition
Recurrent sequence generators conditioned on input data through an atten...
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06/01/2015
Blocks and Fuel: Frameworks for deep learning
We introduce two Python frameworks to train neural networks on large dat...
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12/04/2014
