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Quantifying Spatial Audio Quality Impairment
by Karn Watcharasupat Spatial audio quality is a highly multifaceted concept (see this for a very long list of things to consider). “Geometrical” components of spatial audio quality are perhaps the least subjective aspect of spatial audio quality to quantify, yet there have been very little attempt at dealing withit since BSS Eval came out … Continue reading Quantifying Spatial Audio Quality Impairment
The post Quantifying Spatial Audio Quality Impairment first appeared on Music Informatics Group. -
Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models
by Karn N. Watcharasupat and Junyoung Lee Controllable deep generative models have promising applications in various fields such as computer vision, natural language processing, or music. However, implementations of evaluation metrics for these generative models remain non-standardized. Evaluating disentanglement learning, in particular, might require implementing your own metrics, possibly entangling you more than when you … Continue reading Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models
The post Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models first appeared on Music Informatics Group.