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So-called Sound Quality Metrics are applied in automated evaluation and classification of sound patterns. Machine Learning approaches such as linear regression modelling are followed in order to establish these metrics as combinations of different (psycho-)acoustic descriptors.
This two-day seminar conveys safe access to the topic of Sound Quality Metric Development and insights into topics of Machine Learning in Acoustics.
9:00 h - 16:00 h
The seminar addresses noise and vibration engineers who want to get started with automated evaluation and classification of sound patterns with the help of Sound Quality Metrics.
Basic knowledge in the fields of (psycho-)acoustic analysis and statistics.
Experience with ArtemiS suite software is advantageous.
Machine Learning, Regression and Classification
Conduction of Jury Tests to generate training datasets
Definition of predictors using (Psycho-)Acoustics
Extended approaches and cross-validation
Conduction of Jury Tests in ArtemiS suite
(Psycho-)Acoustic analysis in ArtemiS suite
Definition of Sound Quality Metrics in ArtemiS suite
Training material is provided in print and as pdf on a USB stick.
Notebooks and frontends are available for all participants. The number of participants is limited to 10.
HEAD acoustics GmbH