McDonnell Boehnen Hulbert & Berghoff LLP
Unsupervised learning of semantic audio representations
Methods are provided for generating training triplets that can be used to train multidimensional embeddings to represent the semantic content of non-speech sounds present in a corpus of audio recordings. These training triplets can be used with a triplet loss function to train the multidimensional embeddings such that the embeddings can be used to cluster the contents of a corpus of audio recordings, to facilitate a query-by-example lookup from the corpus, to allow a small number of manually-labeled audio recordings to be generalized, or to facilitate some other audio classification task. The triplet sampling methods may be used individually or collectively, and each represent a respective heuristic about the semantic structure of audio recordings.
Google LLC
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Manoj Jiayang Daniel Ryan Ratheet Shawn Aren Richard Channing
Plakal Liu Ellis Rifkin Pandya Hershey Jansen Moore