Short-cycle frequency detector
AssigneeNuvoton Technology Corporation
InventorsItamar Tamir, Ittai Barkai
Life of this patent
Estimating the term…
Abstract
A system includes a memory and processor. The memory is configured to store a machine learning (ML) model that is trained to estimate values of frequencies added (FA) in sparse input signals that have been derived from respective input audio signals, the sparse input signals being indicative of one or more FA in the corresponding input audio signals. The processor is configured to (i) receive an input audio signal, (ii) derive from the input audio signal a sparse input signal indicative of the FA in the input audio signal, and (iii) estimate the values of the FA in the input audio signal by applying the trained ML model to the sparse input signal.
Claims23
A system, comprising:
- a memory, configured to store a machine learning (ML) model that is trained to estimate values of frequencies added (FA) in sparse input signals that have been derived from respective input audio signals, the sparse input signals being indicative of one or more FA in the corresponding input audio signals;
- and
- a processor, which is configured to:
- receive an input audio signal;
- derive from the input audio signal a sparse input signal indicative of the FA in the input audio signal;
- and
- estimate the values of the FA in the input audio signal by applying the trained ML model to the sparse input signal.
A system, comprising:
- a memory configured to store a machine learning (ML) model;
- and
- a processor, which is configured to:
- obtain a plurality of audio signals that are labeled according to respective values of frequencies added (FA) in the signals;
- derive from the plurality of audio signals a respective plurality of sparse training signals, each sparse training signal being indicative of one or more FA in a corresponding audio signal;
- and
- using the sparse training signals, train the ML model to estimate values of the FA.
A method, comprising:
- storing in a memory a machine learning (ML) model that is trained to estimate values of frequencies added (FA) in sparse input signals that have been derived from respective input audio signals, the sparse input signals being indicative of one or more FA in the corresponding input audio signals;
- receiving an input audio signal;
- deriving from the input audio signal a sparse input signal indicative of the FA in the input audio signal;
- and
- estimating the values of the FA in the input audio signal by applying the trained ML model to the sparse input signal.
A method, comprising:
- storing in a memory a machine learning (ML) model;
- obtaining a plurality of audio signals that are labeled according to respective values of frequencies added (FA) in the signals;
- deriving from the plurality of audio signals a respective plurality of sparse training signals, each sparse training signal being indicative of one or more FA in a corresponding audio signal;
- and
- using the sparse training signals, training the ML model to estimate the values of the FA.
Dependencies are inferred from the claim text.