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Jason Cramer

2 accepted papers

2020

Chirping up the Right Tree: Incorporating Biological Taxonomies into Deep Bioacoustic Classifiers

ICASSP 2020accepted

Class imbalance in the training data hinders the generalization ability of machine listening systems. In the context of bioacoustics, this issue may be circumvented by aggregating species labels into super-groups of higher taxonomic rank: genus, family, order, and so forth. However, different applic…

Cited by 0SourceScholar
2019

Look, Listen, and Learn More: Design Choices for Deep Audio Embeddings

ICASSP 2019accepted

A considerable challenge in applying deep learning to audio classification is the scarcity of labeled data. An increasingly popular solution is to learn deep audio embeddings from large audio collections and use them to train shallow classifiers using small labeled datasets. Look, Listen, and Learn…

Cited by 0SourceScholar