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个人简介
Josef is a Lecturer in the Division for Human Communication, Development and Hearing, and at the Manchester Centre for Audiology and Deafness (ManCAD). The focus of his research lies on auditory perception and machine learning for healthare and audio. Current projects of his team are
Bayesian active learning for remote hearing assessment
Machine-to-human communication for the hearing impaired
Irrelevant Speech Effect: Features of speech
Loudness modelling
Perception in background noise
Using EEG to characterise a hearing loss
Josef graduated from TU Munich with a M.Sc. in Electrical Engineering and Information Technology. During this time he enjoyed working part-time as a software developer for helicopter simulators at ESG. His curiosity about decoding the human brain took him to obtaining a Ph.D. in Psychology at TU Darmstadt. He has done several research visits to Seikei University (Tokyo).
While being a postdoc at the University of Cambridge he sped up hearing tests by using Bayesian active-learning techniques and information theory. This allows clinicians to do more tests in a given time, leading to a more precise knowledge about an individual’s hearing. He did further research in basic auditory science.
He won several awards for his work on perceptual models, including a Best Paper and Presentation Award at ICA 2019 and the DIN Award “Young Science” (DIN is the German Organization for Standardization).
Bayesian active learning for remote hearing assessment
Machine-to-human communication for the hearing impaired
Irrelevant Speech Effect: Features of speech
Loudness modelling
Perception in background noise
Using EEG to characterise a hearing loss
Josef graduated from TU Munich with a M.Sc. in Electrical Engineering and Information Technology. During this time he enjoyed working part-time as a software developer for helicopter simulators at ESG. His curiosity about decoding the human brain took him to obtaining a Ph.D. in Psychology at TU Darmstadt. He has done several research visits to Seikei University (Tokyo).
While being a postdoc at the University of Cambridge he sped up hearing tests by using Bayesian active-learning techniques and information theory. This allows clinicians to do more tests in a given time, leading to a more precise knowledge about an individual’s hearing. He did further research in basic auditory science.
He won several awards for his work on perceptual models, including a Best Paper and Presentation Award at ICA 2019 and the DIN Award “Young Science” (DIN is the German Organization for Standardization).
研究兴趣
论文共 44 篇作者统计合作学者相似作者
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TRENDS IN HEARING (2024): 23312165231225545-23312165231225545
Josef Schlittenlacher, Megan Brogan
Acoustical Science and Technology (2024)
Trends in hearing (2023): 23312165231184982-23312165231184982
Josef Schlittenlacher, Karine Wales
INTER-NOISE and NOISE-CON Congress and Conference Proceedingsno. 6 (2023): 1200-1205
semanticscholar(2021)
INTER-NOISE and NOISE-CON Congress and Conference Proceedingsno. 2 (2021): 4767-4772
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