Opendata, web and dolomites


BIg Speech data analytics for cONtact centres

Total Cost €


EC-Contrib. €






Project "BISON" data sheet

The following table provides information about the project.


Organization address
address: CHALOUPKOVA 3002/1A
city: BRNO
postcode: 612 00
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Czech Republic [CZ]
 Project website
 Total cost 4˙097˙952 €
 EC max contribution 3˙090˙824 € (75%)
 Programme 1. H2020-EU. (Content technologies and information management: ICT for digital content, cultural and creative industries)
 Code Call H2020-ICT-2014-1
 Funding Scheme IA
 Starting year 2015
 Duration (year-month-day) from 2015-01-01   to  2017-12-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    PHONEXIA SRO CZ (BRNO) coordinator 385˙000.00
2    MyForce BE (Blanden) participant 711˙812.00
3    VYSOKE UCENI TECHNICKE V BRNE CZ (BRNO STRED) participant 457˙500.00
4    EBOS LUXEMBOURG SA LU (DIFFERDANGE) participant 441˙497.00
7    TELEFONICA MOVILES ESPANA SA ES (MADRID) participant 240˙030.00
8    COMCZECH AS CZ (PRAHA) participant 235˙865.00


 Project objective

Contact centers (CC) are an important business for Europe: 35,000 contact centers generate 3.2 Million jobs (~1% of Europe’s active population). A typical CC produces a wealth of multilingual spoken data that is nowadays mined by humans (CC agents and supervisors) or by rudimentary technical means.

BISON consortium plans to bring significant innovations in three areas: (1) basic speech data mining technologies (systems quickly adaptable to new languages, domains and CC campaigns), (2) business outcome mining from speech (translated into improvement of CCs’ Key Performance Indicators) and (3) CC support systems integrating both speech and business outcome mining in user-friendly way.

The project will produce two prototypes: smallBison (end of the 1st year) will be a functioning system for real, though limited, deployment and user feedback collection. bigBison (end of the project) will include full range of capabilities and be fully integrated with CC hardware and software infrastructure. Generation of business outputs will be demonstrated on real data.

Business indicators and values for the market were instrumental for the definition of the project and will be crucial for project execution.

BISON consortium is composed of eight players with complementary skills. Two end users running large CC operations (EBOS, Atento) are generating user requirements and are ready to deploy the prototypes immediately in real scenarios. Phonexia (the coordinator), Brno University of Technology and Telefónica ID are experts in speech data mining - from R&D, data processing to developing products placed on the market. Telefónica Móviles is an expert in business outcome mining and MyForce is a skilled Contact Center hardware and software integrator. CC data involve a number of legal issues, therefore, the University of Bologna (with significant experience in regulatory and legal aspects) complements the consortium.


List of deliverables.
Public web-page Websites, patent fillings, videos etc. 2019-03-11 10:43:56
smallBison Demonstrators, pilots, prototypes 2019-03-11 10:44:01
bigBison Demonstrators, pilots, prototypes 2019-03-11 10:44:06
Final set of speech technologies adapted for Contact Centers Other 2019-03-11 10:43:42
Initial speech mining technologies Other 2019-03-11 10:43:47
Legal, ethical and societal issues of BISON - The BISON ethical and societal code Documents, reports 2019-01-08 15:40:07
Optimizing speech data mining for CC operation Documents, reports 2019-01-08 15:40:10
Indexing and database access to big speech data Other 2019-01-08 15:40:08

Take a look to the deliverables list in detail:  detailed list of BISON deliverables.


year authors and title journal last update
List of publications.
2017 Martin Karafiát, Murali Karthick Baskar, Pavel Matějka, Karel Veselý, František Grézl, Lukáš Burget, Jan Černocký
2016 BUT Babel System: Multilingual BLSTM Acoustic Model with i-Vector Based Adaptation
published pages: 719-723, ISSN: , DOI: 10.21437/Interspeech.2017-1775
Interspeech 2017 2019-05-30
2017 Karel Beneš, Murali Karthick Baskar, Lukáš Burget
Residual Memory Networks in Language Modeling: Improving the Reputation of Feed-Forward Networks
published pages: 284-288, ISSN: , DOI: 10.21437/Interspeech.2017-1442
Interspeech 2017 2019-05-30
2017 Anna Silnova, Lukáš Burget, Jan Černocký
Alternative Approaches to Neural Network Based Speaker Verification
published pages: 1572-1575, ISSN: , DOI: 10.21437/Interspeech.2017-1062
Interspeech 2017 2019-05-30
2016 Ekaterina Egorova, Jordi Luque Serrano
Semi-Supervised Training of Language Model on Spanish Conversational Telephone Speech Data
published pages: 114-120, ISSN: 1877-0509, DOI: 10.1016/j.procs.2016.04.038
Procedia Computer Science 81 2019-05-30
2016 František Grézl, Martin Karafiát
Bottle-Neck Feature Extraction Structures for Multilingual Training and Porting
published pages: 144-151, ISSN: 1877-0509, DOI: 10.1016/j.procs.2016.04.042
Procedia Computer Science 81 2019-05-30
2016 Jan Pešán, Lukáš Burget, Jan Černocký
Sequence Summarizing Neural Networks for Spoken Language Recognition
published pages: 3285-3288, ISSN: , DOI: 10.21437/Interspeech.2016-764
Interspeech 2016 2019-05-30
2016 Lucas Ondel, Lukaš Burget, Jan Černocký
Variational Inference for Acoustic Unit Discovery
published pages: 80-86, ISSN: 1877-0509, DOI: 10.1016/j.procs.2016.04.033
Procedia Computer Science 81 2019-05-30
2016 Abraham Woubie, Jordi Luque, Javier Hernando
Improving i-Vector and PLDA Based Speaker Clustering with Long-Term Features
published pages: 372-376, ISSN: , DOI: 10.21437/Interspeech.2016-339
Interspeech 2016 2019-05-30
2017 Hossein Zeinali, Hossein Sameti, Lukáš Burget, Jan “Honza” Černocký
Text-dependent speaker verification based on i-vectors, Neural Networks and Hidden Markov Models
published pages: 53-71, ISSN: 0885-2308, DOI: 10.1016/j.csl.2017.04.005
Computer Speech & Language 46 2019-05-30
2017 Hossein Zeinali, Hossein Sameti, Lukas Burget
HMM-Based Phrase-Independent i-Vector Extractor for Text-Dependent Speaker Verification
published pages: 1421-1435, ISSN: 2329-9290, DOI: 10.1109/TASLP.2017.2694708
IEEE/ACM Transactions on Audio, Speech, and Language Processing 25/7 2019-05-30
2016 BRUMMER Niko, SWART Albert du Preez, PRIETO Jesús J., GARCIA Perera Leibny Paola, MATĚJKA Pavel, PLCHOT Oldřich, DIEZ Sánchez Mireia, SILNOVA Anna, JIANG Xiaowei, NOVOTNÝ Ondřej, ROHDIN Johan A., GLEMBEK Ondřej, GRÉZL František, BURGET Lukáš, ONDEL Lucas, PEŠÁN Jan, ČERNOCKÝ Jan, KENNY Patrick, ALAM Jahangir, BHATTACHARYA Gautam and ZEINALI Hossein et al.
published pages: , ISSN: , DOI:
Proceedings of the NIST SRE Workshop 2019-05-30
2017 Pavel Matějka, Ondřej Novotný, Oldřich Plchot, Lukáš Burget, Mireia Diez Sánchez, Jan Černocký
Analysis of Score Normalization in Multilingual Speaker Recognition
published pages: 1567-1571, ISSN: , DOI: 10.21437/Interspeech.2017-803
Interspeech 2017 2019-05-30
2016 František Grézl, Ekaterina Egorova, Martin Karafiát
Study of Large Data Resources for Multilingual Training and System Porting
published pages: 15-22, ISSN: 1877-0509, DOI: 10.1016/j.procs.2016.04.024
Procedia Computer Science 81 2019-05-30
2017 Karel Veselý, Lukáš Burget, Jan Černocký
Semi-Supervised DNN Training with Word Selection for ASR
published pages: 3687-3691, ISSN: , DOI: 10.21437/Interspeech.2017-1385
Interspeech 2017 2019-05-30
2017 Oldřich Plchot, Pavel Matějka, Anna Silnova, Ondřej Novotný, Mireia Diez Sánchez, Johan Rohdin, Ondřej Glembek, Niko Brümmer, Albert Swart, Jesús Jorrín-Prieto, Paola García, Luis Buera, Patrick Kenny, Jahangir Alam, Gautam Bhattacharya
Analysis and Description of ABC Submission to NIST SRE 2016
published pages: 1348-1352, ISSN: , DOI: 10.21437/Interspeech.2017-1498
Interspeech 2017 2019-05-30
2016 Abraham Woubie Zewoudie, Jordi Luque, Javier Hernando
Short- and Long-Term Speech Features for Hybrid HMM-i-Vector based Speaker Diarization System
published pages: 400-406, ISSN: , DOI: 10.21437/Odyssey.2016-58
Odyssey 2016 2019-05-30

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