Search Results for author: Piotr Pęzik

Found 5 papers, 0 papers with code

DiaBiz – an Annotated Corpus of Polish Call Center Dialogs

no code implementations LREC 2022 Piotr Pęzik, Gosia Krawentek, Sylwia Karasińska, Paweł Wilk, Paulina Rybińska, Anna Cichosz, Angelika Peljak-Łapińska, Mikołaj Deckert, Michał Adamczyk

This paper introduces DiaBiz, a large, annotated, multimodal corpus of Polish telephone conversations conducted in varied business settings, comprising 4036 call centre interactions from nine different domains, i. e. banking, energy services, telecommunications, insurance, medical care, debt collection, tourism, retail and car rental.

speech-recognition Speech Recognition

SpokesBiz -- an Open Corpus of Conversational Polish

no code implementations19 Dec 2023 Piotr Pęzik, Sylwia Karasińska, Anna Cichosz, Łukasz Jałowiecki, Konrad Kaczyński, Małgorzata Krawentek, Karolina Walkusz, Paweł Wilk, Mariusz Kleć, Krzysztof Szklanny, Szymon Marszałkowski

This paper announces the early release of SpokesBiz, a freely available corpus of conversational Polish developed within the CLARIN-BIZ project and comprising over 650 hours of recordings.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Keyword Extraction from Short Texts with a Text-To-Text Transfer Transformer

no code implementations28 Sep 2022 Piotr Pęzik, Agnieszka Mikołajczyk-Bareła, Adam Wawrzyński, Bartłomiej Nitoń, Maciej Ogrodniczuk

The paper explores the relevance of the Text-To-Text Transfer Transformer language model (T5) for Polish (plT5) to the task of intrinsic and extrinsic keyword extraction from short text passages.

Keyword Extraction Language Modelling

Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios

no code implementations13 Sep 2021 Raghavendra Pappagari, Piotr Żelasko, Agnieszka Mikołajczyk, Piotr Pęzik, Najim Dehak

Further, we show that by training the model in the written text domain and then transfer learning to conversations, we can achieve reasonable performance with less data.

Transfer Learning

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