Dr.-Ing. Pablo Delgado

Current offerings

  • Currently offering master thesis, research internship and student job opportunities.
  • PhD and Postdoc positions also available.

Research Interests

  • Audio quality assessment

    • Perceptual audio quality metrics (PEAQ, PESQ, POLQA, and other ITU-R/ITU-T methods)
    • Perceptual models of human hearing (peripheral and cognitive)
    • Psychoacoustics
    • Machine learning for audio quality assessment
    • Subjective assessment of audio quality (spatial and timbre)
  • Machine learning and deep learning in audio

    • Neural audio coding
    • Perceptual loss functions for deep learning in audio
    • Machine learning based incorporation of subjective data into perceptual models
  • Perceptual audio coding

    • Low and high bitrate music and speech coding
    • Multichannel and object-oriented reproduction formats
    • Binaural audio reproduction and coding
  • Audio signal processing

    • Musical applications
    • Virtual reality
    • Spatial audio reproduction
    • Human machine interaction
    • Embedded/low-power systems

Teaching

  • Current

    • 2018-2023: Audio Processing Laboratory, Statistical Methods for Audio Experiments (Prof. Jürgen Herre, FAU)
  • Previous

    • 2012: Introductory Mathematics (National University of Avellaneda)
    • 2009-2012: Algebra II. Linear algebra. (University of Buenos Aires)
    • 2007-2008: Mathematical Analysis III. Complex variable calculus, integral transforms and deterministic signal processing. (University of Buenos Aires)

Research Supervision

  • Master Thesis: "Investigations on Neural Audio Coding", Alexander Heinmüller, 2024

  • Master Thesis: “Models of Cognitive Effects for Auditory Salience in Objective Quality Measurement”, Aalok Gupta, 2022.

  • Master Thesis: “Improved Cognitive Model for a Perceptual Evaluation of Audio Quality Method”, Stefan Emmert, 2021.

  • Research Internship: “Influence of Combined Inter-Aural Cue distortions on Overall Audio Quality in Spatial Audio Telecommunications”, Slavica Subič, 2019.

  • Master Thesis: “Overview of State-of-the-Art Binaural Feature Extraction for Objective Quality Estimation of Parametric Spatial Audio”, Meng Chen, 2018.

Workshops/Keynote Talks

  • Keynote: “To PEAQ or Not to PEAQ? - BS.1387 Revisited” w/Prof. Thomas Sporer, 147th Audio Engineering Society (AES) Convention, 2019.

Memberships

  • Member; IEEE, Institute of Electrical and Electronics Engineers
    • Reviewer: Signal Processing Society (IEEE SPS) Signal Processing Letters (SPL).
    • Reviewer: Transactions on Speech, Audio and Language Processing (IEEE-TASL).
    • Reviewer: IEEE ARGENCON.
  • Member: AES, Audio Engineering Society
    • Reviewer: Journal of the Audio Engineering Society (JAES).
    • Member: AES Technical Committee on Perception and Subjective Evaluation of Audio Signals.
    • Member: AES Technical Committee on Coding of Audio Signals.
    • Member: AES Technical Committee on Machine Learning and Artificial Intelligence in Audio.

CV

Industry Projects (selected)

Education

  • Doctor of Engineering (Dr.-Ing) – Friedrich-Alexander-Universität Erlangen-Nürnberg. Perceptual coding of audio signals. Models of human auditory perception. Psychoacoustics. Machine Learning.

  • Electrical/Electronics Engineer (M.S.E.E.) – University of Buenos Aires.

  • EE, and App. Physics, Signal Processing, Embedded Systems, Telecom and Automation Engineering – École Nationale Supérieure d’Ingénieurs de Caen (ENSICAEN), France.

Further Specialization

  • Statistical methods for data analysis (Dr. Felix Bauer, Prof. Dr. Sebastian Sauer)
  • Filter banks for audio analysis and coding (Prof. Dr.-Ing Bernd Edler)
  • Auditory models (Prof. Dr.-Ing Bernd Edler)
  • Perceptual audio coding techniques and technology (Prof. Dr.-Ing. Jürgen Herre)
  • C/C++ language development techniques for advanced users (Jörg Fasching- bauer)
  • Python for advanced users (Bernd Klein)
  • Scientific writing (Elisabeth Grenzebach)

Multimedia

  • A Data-Driven Cognitive Salience Model for Objective Perceptual Audio Quality Assessment

  • Objective Quality Assessment of Perceptually Coded Audio Signals

Website