Invention Grant
- Patent Title: Unsupervised learning of semantic audio representations
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Application No.: US16758564Application Date: 2018-10-26
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Publication No.: US11335328B2Publication Date: 2022-05-17
- Inventor: Aren Jansen , Manoj Plakal , Richard Channing Moore , Shawn Hershey , Ratheet Pandya , Ryan Rifkin , Jiayang Liu , Daniel Ellis
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: McDonnell Boehnen Hulbert & Berghoff LLP
- International Application: PCT/US2018/057734 WO 20181026
- International Announcement: WO2019/084419 WO 20190502
- Main IPC: G10L15/06
- IPC: G10L15/06 ; G10L15/16 ; G10L15/02 ; G10L25/30 ; G06N3/04 ; G06N3/08 ; G10L25/18 ; G10L25/51

Abstract:
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.
Public/Granted literature
- US20200349921A1 Unsupervised Learning of Semantic Audio Representations Public/Granted day:2020-11-05
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