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Journals | Conferences | Theses | Other | Talks | Posters

Journal Papers

  • A. S. Bali, N. Basu, P. Weber, C. Rosas-Aguilar, G. Edmond, K. A. Martire, G. S. Morrison (2024). Speaker identification in courtroom contexts - Part III: Groups of collaborating listeners compared to forensic voice comparison based on automatic-speaker-recognition technology. Forensic Science International, In press:112048. ( DOI ).
  • N. Basu, P. Weber, A. S. Bali, C. Rosas-Aguilar, G. Edmond, K. A. Martire, G. S. Morrison (2023). Speaker identification in courtroom contexts - Part II: Investigation of bias in individual listeners’ responses. Forensic Science International, 349:111768. ( DOI ).
  • N. Basu, A. S. Bali, P. Weber, C. Rosas-Aguilar, G. Edmond, K. A. Martire, G. S. Morrison (2022). Speaker identification in courtroom contexts - Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology. Forensic Science International, 341:111499. ( DOI ).
  • G. S. Morrison, N. Basu, E. Enzinger, P. Weber (2022). The opacity myth: A response to Swofford & Champod (2022). Letter to the Editor, Forensic Science International: Synergy, 5:100275, 2 pages. ( DOI ).
  • G. S. Morrison, D. Ramos, R. J. F. Ypma, N. Basu, K. de Bie, E. Enzinger, Z. Geradts, D. Meuwly, D. van der Vloed, P. Vergeer, P. Weber (2022). A strawman with machine learning for a brain: A response to Biedermann (2022) The strange persistence of (source) “identification” claims in forensic literature. Letter to the Editor, Forensic Science International: Synergy, 4:100230, 2 pages. ( DOI ).
  • G. S. Morrison, P. Weber, E. Enzinger, B. Labrador, A. Lozano-Díez, D. Ramos, J. González-Rodríguez (2022). Forensic voice comparison - human-supervised automatic approach. In M. Houck, L. Wilson, S. Lews, H. Eldridge, P., Reedy, K. Lothridge (Eds.), Encyclopedia of Forensic Sciences (3rd Ed.), Elsevier, 2022. ( Preprint PDF,  Link ).
  • I. Litchfield, A. M. Turner, J. B. Ferreira Filho, M. Lee, P. Weber (2022). Automated conflict resolution for patients with multiple morbidity being treated using more than one set of single condition clinical guidance: A case study. Computers in Biology and Medicine, 144:105381, 7 pages. ( DOI ).
  • P. Weber, E. Enzinger, B. Labrador, A. Lozano-Díez, D. Ramos, J. González-Rodríguez, G. S. Morrison (2022). Validation of the alpha version of the E3 Forensic Speech Science System (E3FS3) core software tools. Forensic Science International: Synergy, 4:100223, 13 pages, 2022. ( DOI ).
  • G. S. Morrison, P. Weber, N. Basu, R. Puch-Solis, P. S. Randolph-Quinney (2021). Calculation of likelihood ratios for inference of biological sex from human skeletal remains. Forensic Science International: Synergy, 3:100102, 51 pages. ( DOI ).
  • I. A. Trajano, J. B. Ferreira Filho, F. R. C. Sousa, I. Litchfield, P. Weber (2020). MedPath : A process-based modeling language for designing carepathways. International Journal of Medical Informatics, 146:104328, 9 pages. ( DOI ).
  • R. P. De Figueiredo, J. B. Ferreira Filho, F. R. C. Sousa, P. Weber, I. Litchfield (2020). Automated Verification of Care Pathways Using Constraint Programming. IEEE Journal of Biomedical and Health Informatics, 24(9):2718-2725. ( DOI ).
  • I. Litchfield, A. Turner, R. Backman, J. B. F. Filho, P. Weber (2018). Automated conflict resolution between multiple clinical pathways: A technology report. Journal of Innovation in Health Informatics, 5(3):142-148. ( DOI ).
  • I. Litchfield, C. Hoye, D. Shukla, R. Backman, A. Turner, M. Lee, P. Weber (2018). Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol. BMJ Open, 8:e019947, 9 pages. ( DOI ).
  • P. Weber, J. B. F. Filho, B. Bordbar, M. Lee, I. Litchfield, R. Backman (2017). Automated Conflict Detection Between Medical Care Pathways. Journal of Software: Evolution and Process (Special Issue on Software Engineering for Connected Health), 30(7):e1898, 18 pages. ( Preprint PDF,  DOI ).
  • R. Backman, P. Weber, A. M. Turner, M. G. Lee, I. Litchfield (2018). Assessing the extent of drug interactions amongst patients with multimorbidity in primary and secondary care in the West Midlands (UK): A study protocol for the Mixed Methods Multimorbidity Study (MiMMS). BMJ Open, 7(9):e016713, 8 pages. ( HTTP,  DOI ).
  • B. Bordbar, P. Weber (2013). Automated Prevention of Failure in Complex and Large Systems: Fighting Fire with Fire. International Journal of informatics Society (IJIS), 5(2):97-106. ( PDF ).
  • P. Weber, B. Bordbar, P. Tiňo (2013). A Framework for the Analysis of Process Mining Algorithms. IEEE Transactions on Systems, Man and Cybernetics: Systems, 43(2):303-317. ( DOI ).

Refereed Conference Papers

  • Mohamed M., Weber P. (2020). Trends of digitalization and adoption of big data & analytics among UK SMEs: Analysis and lessons drawn from a case study of 53 SMEs. 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Cardiff, UK, 6 pages. ( DOI ).
  • L. Bai, P. Weber, P. Jančovič, M. Russell (2018). Exploring how Phone Classification Neural Networks Learn Phonetic Information by Visualising and Interpreting Bottleneck Features. Interspeech 2018, pp1472-1476, Hyderabad, India. ( DOI,  PDF ).
  • P. Weber, R. Backman, I. Litchfield, M. Lee (2018). A Process Mining and Text Analysis Approach to Analyse the Extent of Polypharmacy in Medical Prescribing. In Proc. the 6th IEEE International Conference on Healthcare Informatics (ICHI 2018), pp1-11, New York, NY, USA. ( PDF, slides, poster PDF ).
  • P. Weber, J. B. F. Filho, B. Bordbar, M. Lee, I. Litchfield, R. Backman (2017). Automated Conflict Detection Between Medical Care Pathways. In N. Carroll, C. Kuziemsky and I. Richardson (Eds.), Software Engineering for Connected Health (Journal First Session), Proc. International Conference on Software and System Process (ICSSP), Paris, France. ( DOI, slides ).
  • L. Bai, P. Jančovič, M. Russell, P. Weber, S. Houghton (2017). Phone Classification using a Non-Linear Manifold with Broad Phone Class Dependent DNNs. Interspeech 2017, pp319-323, Stockholm, Sweden. ( DOI,  PDF ).
  • P. Weber, L. Bai, M. J. Russell, P. Jančovič, S. M. Houghton (2016). Interpretation of Low Dimensional Neural Network Bottleneck Features in Terms of Human Perception and Production. Interspeech 2016, pp3384-3388, San Francisco, CA, USA. ( DOI,  PDF, poster PDF ).
  • M. Najafian, S. Safavi, P. Weber, M. J. Russell (2016). Identification of British English regional accents using fusion of i-vector and multi-accent phonotactic systems. Odyssey 2016, pp132-139, Bilbao, Spain. ( DOI,  PDF ).
  • P. Weber, L. Bai, S. M. Houghton, P. Jančovič, M. J. Russell (2016). Progress on Phoneme Recognition with a Continuous-State HMM. ICASSP 2016, pp5850-5854, Shanghai, China. ( DOI, poster PDF ).
  • P. Weber, C. Champion, S. Houghton, P. Jančovič, M. Russell (2015). Consonant Recognition with Continuous-State Hidden Markov Models and Perceptually-Motivated Features. Interspeech 2015, pp1893-1897, Dresden, Germany. ( DOI,  PDF ).
  • Linxue Bai, P. Jančovič, M. Russell, P. Weber (2016). Analysis of a Low-Dimensional Bottleneck Neural Network Representation of Speech for Modelling Speech Dynamics. Interspeech 2015, pp583-587, Dresden, Germany. ( DOI,  PDF ).
  • S. Houghton, C. Champion, P. Weber (2015). Recognition of Voiced Sounds with a Continuous State HMM. Interspeech 2015, pp523-527, Dresden, Germany. ( DOI,  PDF ).
  • P. Weber, S. Houghton, C. Champion, M. J. Russell, P. Jančovič (2014). Trajectory Analysis of Speech using Continuous State Hidden Markov Models. ICASSP 2014, pp3042-3046, Florence, Italy. ( DOI, slides ).
  • P. Weber, B. Bordbar, P. Tiňo (2013). A Principled Approach to Mining From Noisy Logs Using Heuristics Miner. In Proc. Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on, pp119-126, Singapore. ( DOI ).
  • P. Weber, P. Taylor, B. Majeed, B. Bordbar (2012). Comparing Complex Business Process Models. In Proc. The IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2012, Hong Kong, 5 pages. ( PDF Copyright IEEE ).
  • P. Weber, P. Tiňo, B. Bordbar (2012). Process Mining in Non-Stationary Environments. In The 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN 2012, pp37-42, Bruges, Belgium. ( PDF, poster PDF ).
  • P. Weber, B. Bordbar, P. Tiňo (2011). A Principled Approach to the Analysis of Process Mining Algorithms. In The 12th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2011, pp. 474-481, Lecture Notes in Computer Science, LNCS 6936, Springer. ( DOI,  slides ).
  • P. Weber, B. Bordbar, P. Tiňo, B. Majeed (2011). A Framework for Comparing Process Mining Algorithms. In The 6th IEEE GCC Conference, pp. 625-628, IEEE Computer Society. ( DOI ).

PhD Thesis

  • P. Weber (2014). A Framework for the Analysis and Comparison of Process Mining Algorithms. PhD thesis, University of Birmingham, UK. ( eTheses ).

Workshop and Other Papers

  • P. Weber, E. Enzinger, B. Labrador-Serrano, A. Lozano-Díez, D. Ramos, J. González-Rodríguez, G. S. Morrison (2022). The E3 Forensic Speech Science System (E3FS3): Design principles and validation of core software tools. Presented at the 9th European Academy of forensic Sciences (EAFS) conference, Stockholm, Sweden. ( PDF,  slides ).
  • I. Litchfield, M. Lee, P. Weber (2018). The Automated Identification and Mitigation of Conflict Between Clinical Pathways. Presented at the 46th North American Primary Care Research Group (NAPCRG) Annual Meeting, Chicago, USA.
  • I. Litchfield, M. Lee, P. Weber (2018). Using Process Mining to Automatically Describe and Compare Pathways of Patients with Long-Term Conditions in Primary Care. Presented at the 1st Annual Implementation Science Research Conference, London.
  • I. Litchfield, A. Turner, R. Backman, P. Weber, M. Lee (2017). Automated Conflict Resolution between multiple Clinical Pathways: An Aid for Family Practitioners. Presented at the 45th North American Primary Care Research Group (NAPCRG) Annual Meeting, Montreal, Quebec. ( poster PDF ).
  • I. Litchfield, J. Bowles, B. Bordbar, A. Turner, R. Backman, P. Weber, M. Caminati, M. Lee (2016). Automated Conflict Resolution between multiple Clinical Pathways: An Aid for Family Practitioners. Presented at the 44th North American Primary Care Research Group (NAPCRG) Annual Meeting, Colorado Springs, USA, 2016, and the 3rd West Midlands Health Informatics Network (WIN) Annual Conference, Warwick, UK, 2017. ( poster PDF ).
  • P. Weber, B. Bordbar, P. Tiňo (2011). Real-Time Detection of Process Change using Process Mining. In Andrew V. Jones, editor, ICCSW, volume DTR11-9 of Department of Computing Technical Report, pp. 108-114. Imperial College London. ( PDF,  slides ).

Other Talks

  • P. Weber (2024). Justifying AI in court: Human or machine analysis of evidence?, at BrumAI, Aston University, Birmingham. ( YouTube ).
  • P. Weber (2021). Forensic Voice Comparison (Automatic Speaker Recognition): at BrumAI, Online. ( slides ).
  • P. Weber (2020). Automatic Speech Recognition: where AI meets Human Intelligence: at BrumAI, Birmingham. ( slides ).
  • P. Weber (2016). Can Deep Neural Networks Inform Speech Science? Automatically-Derived Meaningful Representations of Speech: at PERCAT LES & EPS Research Conference, University of Birmingham. ( slides ).
  • P. Weber (2015). Consonant Recognition with Continuous-State Hidden Markov Models and Perceptually-Motivated Features: at UK Speech, University of East Anglia. ( slides ).

Posters

  • P. Weber (2023). An initial empirical analysis of the effect of sampling variability in a forensic voice comparison system. Presented at the UK Speech Conference, The University of Sheffield. ( PDF ).
  • N. Basu, A. S. Bali, P. Weber, C. Rosas-Aguilar, G. Edmond, K. A. Martire, G. S. Morrison (2022). Speaker identification in courtroom contexts: Individual listeners vs automatic forensic voice comparison. Presented at the UK Speech Conference, The University of Edinburgh. ( PDF ).
  • L. Bai, P. Weber, P. Jančovič, M. Russell (2019). Exploring How Phone Classification Neural Networks Learn Phonetic Information by Visualising and Interpreting Bottleneck Features. Presented at the UK Speech Conference, University of Birmingham. ( PDF ).
  • P. Weber, R. Backman, I. Litchfield, M. Lee (2018). A Process Mining and Text Analysis Approach to Analyse the Extent of Polypharmacy in Medical Prescribing. Presented at the Clinical Science and Engineering for Digital Health Workshop, Aston University. ( PDF ).
  • R. Backman, A. Turner, P. Weber, M. Lee, I. Litchfield (2016). A Mixed Methods Approach to Assessing Multimorbidity in Primary and Secondary Care (MiMMS). Presented at the PERCAT Research Gala, University of Birmingham. ( PDF ).
  • Linxue Bai, P. Jančovič, M. Russell, P. Weber (2015). Analysis of a Low-Dimensional Bottleneck Neural Network Representation of Speech for Modelling Speech Dynamics. Presented at the UK Speech Conference, University of East Anglia, Norwich. ( PDF ).
  • P. Weber, S. Houghton, C. Champion, M. J. Russell, P. Jančovič (2014). Trajectory Analysis of Speech using Continuous State Hidden Markov Models. Presented at the UK Speech Conference, University of Edinburgh, Google’s 1st Doctoral Workshop on Speech Technology, London, and the College of Engineering and Physical Sciences Research Conference, University of Birmingham. ( PDF ).
  • P. Weber, B. Bordbar, P. Tiňo (2012). A Framework for the Analysis of Process Mining Algorithms. Presented at the CS & EECE PhD Student trip to the Raymond Priestly Centre, Coniston. ( PDF ).
  • P. Weber, B. Bordbar, P. Tiňo (2010). Real-time Process Mining? Presented at the British Science Festival doctoral research showcase, University of Birmingham, and Industrial Advisory Board, School of Computer Science, University of Birmingham. ( PDF ).