I am a Ph. D. student at the Computer Vision Center working in Document Analysis and Optical Music Recognition. I also have interests in other Computer Science-related technologies such as Compiler Construction or Language Processing.

Publications

Conferences

  • P. Torras, A. Baró, L. Kang, and A. Fornés, “On the Integration of Language Models into Sequence to Sequence Architectures for Handwritten Music Recognition” in Proceedings of the 22nd International Society for Music Information Retrieval Conference, Online, Nov. 07, 2021, pp. 690–696. doi: 10.5281/zenodo.5624451.

Workshops

  • P. Torras, M. A. Souibgui, J. Chen, and A. Fornés, “A Transcription Is All You Need: Learning to Align Through Attention” in Document Analysis and Recognition – ICDAR 2021 Workshops, 2021, pp. 141–146. doi: 10.1007/978-3-030-86198-8_11.
  • P. Torras, M. A. Souibgui, J. Chen, and A. Fornés, “An Evaluation of Handwritten Text Recognition Methods for Historical Ciphered Manuscripts” in Proceedings of the 7th International Workshop on Historical Document Imaging and Processing, 2023, pp. 7-12. doi:10.1145/3604951.3605509.
  • P. Torras, M. A. Souibgui, J. Chen, S. Biswas, and A. Fornés, “Segmentation-Free Alignment of Arbitrary Symbol Transcripts to Images” in Document Analysis and Recognition – ICDAR 2023 Workshops, 2023, pp. 83-93. doi: 10.1007/978-3-031-41498-5_6

Other Publications

  • A. Baró, C. Badal, P. Torras, A. Fornés, “Handwritten Historical Music Recognition through Sequence-to-Sequence with Attention Mechanism” in Proceedings of the 3rd International Workshop on Reading Music Systems, 2021, pp. 55-59.
  • P. Torras, A. Baró, L. Kang, A. Fornés, “Improving Handwritten Music Recognition through Language Model Integration” in Proceedings of the 4th International Workshop on Reading Music Systems, 2022.

Projects

  • Bachelor’s Thesis: Integration of Language Models in Sequence to Sequence Optical Music Recognition Systems. May be found here (awarded a 9.6/10)
  • Master’s Thesis: Music Tree Notation for End-to-End Optical Music Recognition. May be found here (awarded a 10/10)

Awards

  • Extraordinary Academic Achievement Award, B. Sc. in Computer Science (2021)
  • Best Master’s Thesis Award, M. Sc. in Computer Vision (2022)

Studies

Academic

  • B. Sc. in Computer Science by Universitat Autònoma de Barcelona (2021).
  • M. Sc. in Computer Vision by Universitat Autònoma de Barcelona, Universitat Politècnica de Catalunya, Universitat Pompeu Fabra and Universitat Oberta de Catalunya (2022).

Other

  • Federative Chess Instructor Course – Registered in the Catalan Sport Professionals Registry (ROPEC) with number 039549 (2019)

Experience

  • Chess Instructor at Club Escacs Montmeló (2018 - ongoing)
  • Intern at Computer Vision Center (Universitat Autònoma de Barcelona) working in the Decrypt project (September 2020 - April 2021).
  • Intern at the Computer Vision Center (Universitat Autònoma de Barcelona) working in Optical Music Recognition (June 2021 - October 2021)

Skills

  • Tools: Python, Pytorch, OpenCV, C/C++, Keras, Numpy, Matlab
  • Fields: Computer Vision, Optical Music Recognition, Document Analysis
  • Hobbies: Self-taught music theory and piano, 1898 peak FIDE chess rating

Languages

  • Catalan: Native Level
  • Spanish: Native Level
  • English: Certified C1 Level
  • French: Basic Level

Traits

Hard-working, quick learner, responsible, creative, organised, enthusiastic.