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Philipp Aichinger
DI Dr.techn. Philipp Aichinger

Department of Otorhinolaryngology (Division of Speech and Language Therapy)
Position: Research Associate (Postdoc)

T +43 1 40400 11670


Hearing; Pattern Recognition, Automated; Psychoacoustics; Signal Processing, Computer-Assisted; Speech; Speech Acoustics; Speech Disorders; Voice; Voice Disorders; Voice Quality

Research interests

Philipp Aichinger is interested in objective voice quality description, speech acoustics, audio and video signal processing, machine learning, pattern classification, and diagnostic studies. His PhD disseration entitled "Diplophonic Voice - Definitions, models, and detection" reports research on disordered voice sounds in which two simultaneous pitches may be heard. Basic concepts of the described phenomena are clarified through original theoretical analysis, simulation studies, and investigation of clinical data. The adressed problems involve auditory perception and projection effects that occur in imaging of the vocal folds, and are adressed by means of analysis-by-synthesis of audio and glottal area waveforms, as well as graphical segmentation.

Techniques, methods & infrastructure

Voice production and the audio waveform are observed by means of laryngeal high-speed videos with simultaneous high-quality microphone recordings. The obtained data are analyzed in MATLAB.

Selected publications

  1. Aichinger, P. et al., 2015. Diplophonic Voice - Definitions, models, and detection. PhD dissertation, Graz University of Technology, Austria. 154 pages. Available at:
  2. Aichinger, P. et al., 2016. Fundamental frequency tracking in diplophonic voices. Biomedical Signal Processing and Control. Available at:
  3. Aichinger, P. et al., 2016. Diplophonia Disturbs Jitter and Shimmer Measurement. Folia Phoniatrica et Logopaedica, 68(1), pp.22-28. Available at:
  4. Aichinger, P. et al., 2016. Towards Objective Voice Assessment: The Diplophonia Diagram. Journal of Voice. Available at:
  5. Aichinger, P. et al., 2014. Comparison of an audio-based and a video-based approach for detecting diplophonia. Biomedical Signal Processing and Control. Available at: