System and method for robust estimation and tracking the fundamental frequency of pseudo periodic signals in the presence of noise
AssigneeVocalzoom Systems Ltd.
InventorsYekutiel Avargel, Tal Bakish
Life of this patent
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Abstract
Method and system for tracking fundamental frequencies of pseudo-periodic signals in the presence of noise that include receiving a time-frequency representation of signals measured in a predefined environment; estimating and tracking a fundamental frequency of a respective pseudo-periodic signal at each time frame of the time-frequency representation by tracking detections of harmonious frequencies in the time-frequency representation over time; and outputting each respective estimated fundamental frequency associated with the pseudo-periodic signal of each respective time frame.
Claims19
A computer implemented method of tracking fundamental frequencies of pseudo-periodic signals in the presence of noise, said method comprising:
- receiving a time-frequency representation of signals measured in a predefined environment;
- estimating and tracking a fundamental frequency of a respective pseudo-periodic signal at each time frame of said time-frequency representation by tracking detections of harmonious frequencies in said time-frequency representation over time;
- and
- outputting said respective estimated fundamental frequency associated with said pseudo-periodic signal of each said respective time frame;
- wherein a respective said fundamental frequency is tracked, recorded in a memory unit, and identified in each time frame of said time-frequency representation;
- wherein said estimation and tracking of the fundamental frequency of each respective time frame comprises:
- identifying harmonious frequencies in each time frame of said time-frequency representation;
- checking correlations between each identified harmonious frequency and harmonious frequencies identified in preceding time frames;
- allocating a new tracker to each respective identified uncorrelated harmonious frequency;
- updating information relating to each tracker including number of identified correlations associated with each said tracker;
- and
- determining said fundamental frequency of the respective time frame by selecting one of said trackers, according to predefined rules associated with accumulated information of said trackers, including the number of correlations associated with each said tracker.
A system for tracking fundamental frequencies of pseudo-periodic signals in the presence of noise, said system comprising:
- a signal measurement system for measuring pseudo-periodic signals in a predefined environment;
- at least one processing unit, which
- receives measured pseudo-periodic signals in real time or near real time from said signal measurement system,
- processes said signal for obtaining a time-frequency representation thereof in real time or near real time and recursively estimates,
- tracks a respective fundamental frequency of each respective pseudo-periodic signal at each time frame of said time-frequency representation by tracking detections of harmonious frequencies in said time-frequency representation over time, and
- outputs said respective estimated fundamental frequency associated with said pseudo-periodic signal of said respective time frame;
- and
- wherein said estimation and tracking of the fundamental frequency of each respective time frame is carried out by:
- identifying harmonious frequencies in each time frame of said time-frequency representation;
- checking correlations between each identified harmonious frequency and harmonious frequencies identified in preceding time frames;
- allocating a new tracker to each respective identified uncorrelated harmonious frequency;
- updating information relating to each tracker including number of identified correlations associated with each said tracker;
- and
- determining said fundamental frequency of the respective time frame by selecting a tracker according to accumulated information including the number of correlations associated therewith.
Dependencies are inferred from the claim text.