Project Details
Big speech data analytics for contact centers
Project Period: 1. 1. 2015 – 31. 12. 2017
Project Type: grant
Agency: Evropská unie
Program: Horizon 2020
contact centres, speech data mining, big data, speech recognition, keyword spotting
Contact centers (CC) are an important business for Europe: 35,000 contact centers generate 3.2 Million jobs (~1% of Europes 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 I+D 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.
Beneš Karel, Ing. (DCGM)
Burget Lukáš, doc. Ing., Ph.D. (DCGM)
Cao Yujia, M.Sc., Ph.D.
Grézl František, Ing., Ph.D. (DCGM)
Hannemann Mirko, Ph.D.
Matějka Pavel, Ing., Ph.D. (DCGM)
Mošner Ladislav, Ing. (DCGM)
Nathans Riva, Bc.
Žmolíková Kateřina, Ing., Ph.D. (FIT)
2018
- EGOROVA, E.; BURGET, L. Out-of-Vocabulary Word Recovery Using FST-Based Subword Unit Clustering in a Hybrid ASR System. In Proceedings of ICASSP 2018. Calgary: IEEE Signal Processing Society, 2018.
p. 5919-5923. ISBN: 978-1-5386-4658-8. Detail - VESELÝ, K.; PERALES, C.; SZŐKE, I.; LUQUE, J.; ČERNOCKÝ, J. Lightly supervised vs. semi-supervised training of acoustic model on Luxembourgish for low-resource automatic speech recognition. In Proceedings of Interspeech 2018. Proceedings of Interspeech. Hyderabad: International Speech Communication Association, 2018.
p. 2883-2887. ISSN: 1990-9772. Detail
2017
- BASKAR, M.; KARAFIÁT, M.; BURGET, L.; VESELÝ, K.; GRÉZL, F.; ČERNOCKÝ, J. Residual Memory Networks: Feed-forward approach to learn long-term temporal dependencies. In Proceedings of ICASSP 2017. New Orleans: IEEE Signal Processing Society, 2017.
p. 4810-4814. ISBN: 978-1-5090-4117-6. Detail - BENEŠ, K.; BASKAR, M.; BURGET, L. Residual Memory Networks in Language Modeling: Improving the Reputation of Feed-Forward Networks. In Proceedings of Interspeeech 2017. Proceedings of Interspeech. Stockholm: International Speech Communication Association, 2017.
p. 284-288. ISSN: 1990-9772. Detail - KARAFIÁT, M.; BASKAR, M.; MATĚJKA, P.; VESELÝ, K.; GRÉZL, F.; BURGET, L.; ČERNOCKÝ, J. 2016 BUT Babel system: Multilingual BLSTM acoustic model with i-vector based adaptation. In Proceedings of Interspeech 2017. Proceedings of Interspeech. Stockholm: International Speech Communication Association, 2017.
p. 719-723. ISSN: 1990-9772. Detail - MATĚJKA, P.; NOVOTNÝ, O.; PLCHOT, O.; BURGET, L.; DIEZ SÁNCHEZ, M.; ČERNOCKÝ, J. Analysis of Score Normalization in Multilingual Speaker Recognition. In Proceedings of Interspeech 2017. Proceedings of Interspeech. Stockholm: International Speech Communication Association, 2017.
p. 1567-1571. ISSN: 1990-9772. Detail - ONDEL YANG, L.; BURGET, L.; ČERNOCKÝ, J.; KESIRAJU, S. Bayesian phonotactic language model for acoustic unit discovery. In Proceedings of ICASSP 2017. New Orleans: IEEE Signal Processing Society, 2017.
p. 5750-5754. ISBN: 978-1-5090-4117-6. Detail - PLCHOT, O.; MATĚJKA, P.; SILNOVA, A.; NOVOTNÝ, O.; DIEZ SÁNCHEZ, M.; ROHDIN, J.; GLEMBEK, O.; BRÜMMER, N.; SWART, A.; PRIETO, J.; GARCIA PERERA, L.; BUERA, L.; KENNY, P.; ALAM, J.; BHATTACHARYA, G. Analysis and Description of ABC Submission to NIST SRE 2016. In Proceedings of Interspeech 2017. Proceedings of Interspeech. Stockholm: International Speech Communication Association, 2017.
p. 1348-1352. ISSN: 1990-9772. Detail - SILNOVA, A.; BURGET, L.; ČERNOCKÝ, J. Alternative Approaches to Neural Network based Speaker Verification. In Proceedings of Interspeech 2017. Proceedings of Interspeech. Stockholm: International Speech Communication Association, 2017.
p. 1572-1575. ISSN: 1990-9772. Detail - VESELÝ, K.; BASKAR, M.; DIEZ SÁNCHEZ, M.; BENEŠ, K. MGB-3 BUT System: Low-resource ASR on Egyptian YOUTUBE data. In Proceedings of ASRU 2017. Okinawa: IEEE Signal Processing Society, 2017.
p. 368-373. ISBN: 978-1-5090-4788-8. Detail - VESELÝ, K.; BURGET, L.; ČERNOCKÝ, J. Semi-supervised DNN training with word selection for ASR. In Proceedings of Interspeech 2017. Proceedings of Interspeech. Stockholm: International Speech Communication Association, 2017.
p. 3687-3691. ISSN: 1990-9772. Detail - ZEINALI, H.; SAMETI, H.; BURGET, L. HMM-Based Phrase-Independent i-Vector Extractor for Text-Dependent Speaker Verification. IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH AND LANGUAGE PROCESSING, 2017, vol. 25, no. 7,
p. 1421-1435. ISSN: 2329-9290. Detail - ZEINALI, H.; SAMETI, H.; BURGET, L.; ČERNOCKÝ, J. Text-dependent speaker verification based on i-vectors, Neural Networks and Hidden Markov Models. COMPUTER SPEECH AND LANGUAGE, 2017, vol. 2017, no. 46,
p. 53-71. ISSN: 0885-2308. Detail
2016
- BRUMMER, J.; SWART, A.; PRIETO, J.; GARCIA PERERA, L.; MATĚJKA, P.; PLCHOT, O.; DIEZ SÁNCHEZ, M.; SILNOVA, A.; JIANG, X.; NOVOTNÝ, O.; ROHDIN, J.; GLEMBEK, O.; GRÉZL, F.; BURGET, L.; ONDEL YANG, L.; PEŠÁN, J.; ČERNOCKÝ, J.; KENNY, P.; ALAM, J.; BHATTACHARYA, G.; ZEINALI, H. ABC NIST SRE 2016 SYSTEM DESCRIPTION. San Diego: National Institute of Standards and Technology, 2016.
p. 1-8. Detail - EGOROVA, E.; SERRANO, J. Semi-Supervised Training of Language Model on Spanish Conversational Telephone Speech Data. In Procedia Computer Science. Procedia Computer Science. Yogyakarta: Elsevier Science, 2016.
p. 114-120. ISSN: 1877-0509. Detail - GRÉZL, F.; EGOROVA, E.; KARAFIÁT, M. Study of Large Data Resources for Multilingual Training and System Porting. In Procedia Computer Science. Procedia Computer Science. Yogyakarta: Elsevier Science, 2016.
p. 15-22. ISSN: 1877-0509. Detail - GRÉZL, F.; KARAFIÁT, M. Bottle-Neck Feature Extraction Structures for Multilingual Training and Porting. In Procedia Computer Science. Procedia Computer Science. Yogyakarta: Elsevier Science, 2016.
p. 144-151. ISSN: 1877-0509. Detail - MATĚJKA, P.; GLEMBEK, O.; NOVOTNÝ, O.; PLCHOT, O.; GRÉZL, F.; BURGET, L.; ČERNOCKÝ, J. Analysis Of DNN Approaches To Speaker Identification. In Proceedings of the 41th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), 2016. Shanghai: IEEE Signal Processing Society, 2016.
p. 5100-5104. ISBN: 978-1-4799-9988-0. Detail - NOVOTNÝ, O.; MATĚJKA, P.; GLEMBEK, O.; PLCHOT, O.; GRÉZL, F.; BURGET, L.; ČERNOCKÝ, J. Analysis of the DNN-Based SRE Systems in Multi-language Conditions. In Proceedings of SLT 2016. San Diego: IEEE Signal Processing Society, 2016.
p. 199-204. ISBN: 978-1-5090-4903-5. Detail - ONDEL YANG, L.; BURGET, L.; ČERNOCKÝ, J. Variational Inference for Acoustic Unit Discovery. In Procedia Computer Science. Procedia Computer Science. Yogyakarta: Elsevier Science, 2016.
p. 80-86. ISSN: 1877-0509. Detail - PEŠÁN, J.; BURGET, L.; ČERNOCKÝ, J. Sequence Summarizing Neural Networks for Spoken Language Recognition. In Proceedings of Interspeech 2016. San Francisco: International Speech Communication Association, 2016.
p. 3285-3289. ISBN: 978-1-5108-3313-5. Detail - PLCHOT, O.; BURGET, L.; ARONOWITZ, H.; MATĚJKA, P. Audio Enhancing With DNN Autoencoder For Speaker Recognition. In Proceedings of the 41th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), 2016. Shanghai: IEEE Signal Processing Society, 2016.
p. 5090-5094. ISBN: 978-1-4799-9988-0. Detail - SKÁCEL, M.; KARAFIÁT, M.; ONDEL YANG, L.; UCHYTIL, A.; SZŐKE, I. BUT Zero-Cost Speech Recognition 2016 System Description. In CEUR Workshop Proceedings. CEUR Workshop Proceedings. Hilversum: CEUR-WS.org, 2016.
p. 1-3. ISSN: 1613-0073. Detail - SZŐKE, I.; ANGUERA, X. Zero-Cost Speech Recognition Task at Mediaeval 2016. In CEUR Workshop Proceedings. CEUR Workshop Proceedings. Hilversum: CEUR-WS.org, 2016.
p. 1-3. ISSN: 1613-0073. Detail
2015
- GLEMBEK, O.; MATĚJKA, P.; BURGET, L.; SCHWARZ, P.; PEŠÁN, J.; PLCHOT, O. Voice-print transformation for migration between automatic speaker identification systems. Abstract book of the 7th European Academy of Forensic Science Conference. Praha: Criminal Police Department Prague, 2015.
p. 345-345. ISBN: 978-80-260-8659-8. Detail - KARAFIÁT, M.; GRÉZL, F.; BURGET, L.; SZŐKE, I.; ČERNOCKÝ, J. Three ways to adapt a CTS recognizer to unseen reverberated speech in BUT system for the ASpIRE challenge. In Proceedings of Interspeech 2015. Proceedings of Interspeech. Dresden: International Speech Communication Association, 2015.
p. 2454-2458. ISBN: 978-1-5108-1790-6. ISSN: 1990-9772. Detail - SZŐKE, I.; METZE, F.; RODRIGUEZ-FUENTES, L.; PROENCA, J.; BUZO, A.; LOJKA, M.; ANGUERA, X.; XIONG, X. Query by Example Search on Speech at Mediaeval 2015. In CEUR Workshop Proceedings. CEUR Workshop Proceedings. Wurzen: CEUR-WS.org, 2015.
p. 1-3. ISSN: 1613-0073. Detail