DEEP SOURCE SEPARATION ARCHITECTURE

A speech separation server comprises a deep-learning encoder with nonlinear activation. The encoder is programmed to take a mixture audio waveform in the time domain, learn generalized patterns from the mixture audio waveform, and generate an encoded representation that effectively characterizes the...

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Bibliographic Details
Main Authors LIU, Xiaoyu, KADIOGLU, Berkan, PUIG, Jordi Pons, HORGAN, Michael Getty
Format Patent
LanguageEnglish
French
German
Published 18.09.2024
Subjects
ACOUSTICS
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
MUSICAL INSTRUMENTS
PHYSICS
SPEECH ANALYSIS OR SYNTHESIS
SPEECH OR AUDIO CODING OR DECODING
SPEECH OR VOICE PROCESSING
SPEECH RECOGNITION
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Summary:A speech separation server comprises a deep-learning encoder with nonlinear activation. The encoder is programmed to take a mixture audio waveform in the time domain, learn generalized patterns from the mixture audio waveform, and generate an encoded representation that effectively characterizes the mixture audio waveform for speech separation.
Bibliography:Application Number: EP20200804119