119 citations · 235 across the 9 of their papers we have counts for
11 papers
highway2vec -- representing OpenStreetMap microregions with respect to their road network characteristics
Kacper Leśniara, Piotr Szymański
Recent years brought advancements in using neural networks for representation learning of various language or visual phenomena. New methods freed data scientists from hand-crafting…
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…
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…
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…
LNEMLC: Label Network Embeddings for Multi-Label Classification
Piotr Szymański, Tomasz Kajdanowicz, Nitesh Chawla
Multi-label classification aims to classify instances with discrete non-exclusive labels. Most approaches on multi-label classification focus on effective adaptation or transformat…
Punctuation Prediction Model for Conversational Speech
Piotr Żelasko, Piotr Szymański, Jan Mizgajski +3
An ASR system usually does not predict any punctuation or capitalization. Lack of punctuation causes problems in result presentation and confuses both the human reader andoff-the-s…
Spatio-temporal profiling of public transport delays based on large scale vehicle positioning data from GPS in Wrocław
Piotr Szymański, Michał Żołnieruk, Piotr Oleszczyk +2
In recent years many studies of urban mobility based on large data sets have been published: most of them based on crowdsourced GPS data or smart-card data. We present, what is to…
A Network Perspective on Stratification of Multi-Label Data
Piotr Szymański, Tomasz Kajdanowicz
In the recent years, we have witnessed the development of multi-label classification methods which utilize the structure of the label space in a divide and conquer approach to impr…
Is a Data-Driven Approach still Better than Random Choice with Naive Bayes classifiers?
Piotr Szymański, Tomasz Kajdanowicz
We study the performance of data-driven, a priori and random approaches to label space partitioning for multi-label classification with a Gaussian Naive Bayes classifier. Experimen…
A scikit-based Python environment for performing multi-label classification
Piotr Szymański, Tomasz Kajdanowicz
scikit-multilearn is a Python library for performing multi-label classification. The library is compatible with the scikit/scipy ecosystem and uses sparse matrices for all internal…
How is a data-driven approach better than random choice in label space division for multi-label classification?
Piotr Szymański, Tomasz Kajdanowicz, Kristian Kersting
We propose using five data-driven community detection approaches from social networks to partition the label space for the task of multi-label classification as an alternative to r…