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Table of Contents
DiaBiz
DiaBiz corpus is a dialog corpus comprising recordings and annotated transcriptions of phone-based customer-agent interactions in several key business domains.
The corpus comprises:
- 4,036 conversations amounting to nearly 410 hours and over 3 million words
- dialogues between 5 professional call-center agents and 191 participants as customers
- data from 9 business domains with high commercial demand for conversational analytics and automation solutions
- dialogues based on 251 real-life interaction scenarios
The domains covered:
Domain | Dialogs | Words | Duration (HH:MM:SS) |
---|---|---|---|
Banking | 907 | 773,858 | 92:56:54 |
Car rental | 246 | 189,741 | 24:07:07 |
Debt collection | 300 | 245,031 | 29:23:56 |
Energy services | 390 | 248,295 | 30:05:42 |
Insurance | 401 | 307,760 | 40:00:54 |
Medical care | 371 | 236,057 | 30:13:57 |
Telecommunications | 700 | 416,333 | 52:21:52 |
Tourism | 451 | 674,066 | 86:23:10 |
Retail | 270 | 133,702 | 24:24:00 |
Total | 3,766 | 3,091,141 | 385:33:32 |
The data was manually transcribed, time-aligned and annotated.
Applications
Customer support interactions recorded by operators of call centers are highly unlikely to be widely released in any useful form as they contain sensitive information which is subject to strict privacy regulations. NLP start-ups and academic research groups have to develop their own datasets or rely on limited resources which cannot be directly adapted to commercially viable domains. The DiaBiz corpus can serve as a source of training and evaluation data for a wide range of intrinsic and downstream tasks, such as:
- speech recognition and transcript formatting
- speaker diarization
- conversational intent and named entity recognition
- spoken dialog segmentation, labelling and classification
- conversational analytics as well as more sophisticated modelling of dialog systems.
The DiaBiz corpus is therefore a major new resource for spoken Polish, offering research potential and making it possible to bootstrap the development of language processing tools for automating linguistic interactions with high volumes of customers, such as voice bots and other dialog systems.
Availability
Click HERE to download sample recordings.
The current version of the recording catalog is available HERE.
For more information, please contact piotr.pezik@uni.lodz.pl .
Project Team
- Piotr Pęzik
- Michał Adamczyk
- Małgorzata Krawentek
- Paweł Wilk
- Sylwia Karasińska
- Karolina Adamczyk
- Monika Garnys
- Karolina Walkusz
- Angelika Peljak-Łapińska
- Anna Cichosz
- Anna Kwiatkowska
- Mikołaj Deckert
- Paulina Rybińska
- Izabela Grabarczyk
- Maciej Grabski
- Karol Ługowski
- Gracjan Stepaniec-Krawentek
- Krzysztof Hejduk
- Michał Koźmiński
- Zuzanna Deckert
- Piotr Górniak
Acknowledgments
DiaBiz was developed in the project titled “CLARIN - Common Language Resources and Technology Infrastructure”, which is financed under the 2014-2020 Smart Growth Operational Programme, POIR.04.02.00-00C002/19. We would also like to acknowledge the support of three companies: VoiceLab, Genesys and Damovo in the data collection and transcription efforts.