Papers by Piotr Pęzik

4 papers
DiaBiz – an Annotated Corpus of Polish Call Center Dialogs (2022.lrec-1)

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Challenge: DiaBiz is a large corpus of phone conversations from different business domains . it contains nearly 410 hours of recordings and over 3 million words of transcribed speech.
Approach: They introduce DiaBiz, a large, annotated, multimodal corpus of Polish telephone conversations . it is a multimodal, multi-modal corpor of 4036 phone conversations from nine different domains .
Outcome: The corpus of 4036 phone conversations in Poland is 410 hours long and contains over 3 million words of transcribed speech.
Introducing the CURLICAT Corpora: Seven-language Domain Specific Annotated Corpora from Curated Sources (2022.lrec-1)

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Challenge: The CURLICAT CEF Telecom project aims to collect and deeply annotate a set of large corpora from selected domains.
Approach: They present the results of the CURLICAT CEF Telecom project . they propose to collect and deeply annotate a set of large corpora from selected domains .
Outcome: The CURLICAT CEF Telecom project provides a set of large corpora from selected domains . the corporatized corporates are tokenized, lemmatized and morphologically analysed .
Increasing the Accessibility of Time-Aligned Speech Corpora with Spokes Mix (L18-1)

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Challenge: Spokes Mix is an online service providing access to spoken corpora of Polish . high-quality corporata of conversational language are expensive to acquire .
Approach: a new online service provides access to spoken corpora of Polish . the service provides a centralized, easy-to-use corpus query engine with a responsive web interface .
Outcome: the proposed service provides access to spoken corpora of Polish, including three newly released time-aligned collections of manually transcribed spoken-conversational data.
The MARCELL Legislative Corpus (2020.lrec-1)

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Challenge: MARCELL corpus provides a rich and valuable source for further studies and developments in machine learning, cross-lingual terminological data extraction and classification.
Approach: They present the results of the project MARCELL CEF Telecom . they aim to collect and deeply annotate a large comparable corpus of legal documents .
Outcome: The MARCELL corpus includes 7 monolingual sub-corpora containing the body of respective national legislative documents.

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