Search Results for author: Filip Jurčíček

Found 6 papers, 4 papers with code

Neural Generation for Czech: Data and Baselines

2 code implementations11 Oct 2019 Ondřej Dušek, Filip Jurčíček

We present the first dataset targeted at end-to-end NLG in Czech in the restaurant domain, along with several strong baseline models using the sequence-to-sequence approach.

Language Modelling

Denotation Extraction for Interactive Learning in Dialogue Systems

1 code implementation9 Jan 2018 Miroslav Vodolán, Filip Jurčíček

This paper presents a novel task using real user data obtained in human-machine conversation.

Question Answering

A Context-aware Natural Language Generator for Dialogue Systems

1 code implementation25 Aug 2016 Ondřej Dušek, Filip Jurčíček

We present a novel natural language generation system for spoken dialogue systems capable of entraining (adapting) to users' way of speaking, providing contextually appropriate responses.

Spoken Dialogue Systems Text Generation

Recurrent Neural Networks for Dialogue State Tracking

no code implementations28 Jun 2016 Ondřej Plátek, Petr Bělohlávek, Vojtěch Hudeček, Filip Jurčíček

This paper discusses models for dialogue state tracking using recurrent neural networks (RNN).

Dialogue State Tracking

Sequence-to-Sequence Generation for Spoken Dialogue via Deep Syntax Trees and Strings

1 code implementation17 Jun 2016 Ondřej Dušek, Filip Jurčíček

We present a natural language generator based on the sequence-to-sequence approach that can be trained to produce natural language strings as well as deep syntax dependency trees from input dialogue acts, and we use it to directly compare two-step generation with separate sentence planning and surface realization stages to a joint, one-step approach.

Data Collection for Interactive Learning through the Dialog

no code implementations31 Mar 2016 Miroslav Vodolán, Filip Jurčíček

This paper presents a dataset collected from natural dialogs which enables to test the ability of dialog systems to learn new facts from user utterances throughout the dialog.

Open-Domain Dialog

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