activity
20162020
most citedMethod for Aspect-Based Sentiment Annotation Using Rhetorical Analysis

2 citations · 3 across the 2 of their papers we have counts for

collaborators

8 papers

cs.CL20201 cited

Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections

Łukasz Augustyniak, Krzysztof Rajda, Tomasz Kajdanowicz +1

Political campaigns are full of political ads posted by candidates on social media. Political advertisements constitute a basic form of campaigning, subjected to various social req…

cs.CL2020

Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?

Łukasz Augustyniak, Piotr Szymanski, Mikołaj Morzy +5

Automatic Speech Recognition (ASR) systems introduce word errors, which often confuse punctuation prediction models, turning punctuation restoration into a challenging task. These…

cs.CL2019

Extracting Aspects Hierarchies using Rhetorical Structure Theory

Łukasz Augustyniak, Tomasz Kajdanowicz, Przemysław Kazienko

We propose a novel approach to generate aspect hierarchies that proved to be consistently correct compared with human-generated hierarchies. We present an unsupervised technique us…

cs.CL2019

Aspect Detection using Word and Char Embeddings with (Bi)LSTM and CRF

Łukasz Augustyniak, Tomasz Kajdanowicz, Przemysław Kazienko

We proposed a~new accurate aspect extraction method that makes use of both word and character-based embeddings. We have conducted experiments of various models of aspect extraction…

eess.AS2019

Avaya Conversational Intelligence: A Real-Time System for Spoken Language Understanding in Human-Human Call Center Conversations

Jan Mizgajski, Adrian Szymczak, Robert Głowski +14

Avaya Conversational Intelligence(ACI) is an end-to-end, cloud-based solution for real-time Spoken Language Understanding for call centers. It combines large vocabulary, real-time…

cs.CL2019

Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition

Piotr Żelasko, Jan Mizgajski, Mikołaj Morzy +4

In this paper, we present a method for correcting automatic speech recognition (ASR) errors using a finite state transducer (FST) intent recognition framework. Intent recognition i…