Acoustic signal classification system
First Claim
Patent Images
1. A method for classifying an input signal, comprising:
- establishing a first signal model;
obtaining an input signal;
determining a time-frequency representation of the input signal;
determining, by a processor, whether a harmonic is present in the time-frequency representation;
initiating spectrogram template matching, using the first signal model, in response to determining that the harmonic is present; and
forgoing spectrogram template matching when the harmonic is not present;
where determining whether the harmonic is present comprises;
determining a frequency range to scan;
scanning the time-frequency representation over the frequency range;
identifying local peaks in the frequency range that exceed neighboring spectrum values by more than a peak threshold;
counting votes for the local peaks;
determining a normalized vote ratio using an expected number of harmonics in the frequency range; and
comparing the normalized vote ratio to a harmonic threshold.
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Abstract
A system classifies the source of an input signal. The system determines whether a sound source belongs to classes that may include human speech, musical instruments, machine noise, or other classes of sound sources. The system is robust, performing classification despite variation in sound level and noise masking. Additionally, the system consumes relatively few computational resources and adapts over time to provide consistently accurate classification.
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Citations
21 Claims
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1. A method for classifying an input signal, comprising:
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establishing a first signal model; obtaining an input signal; determining a time-frequency representation of the input signal; determining, by a processor, whether a harmonic is present in the time-frequency representation; initiating spectrogram template matching, using the first signal model, in response to determining that the harmonic is present; and forgoing spectrogram template matching when the harmonic is not present; where determining whether the harmonic is present comprises; determining a frequency range to scan; scanning the time-frequency representation over the frequency range; identifying local peaks in the frequency range that exceed neighboring spectrum values by more than a peak threshold; counting votes for the local peaks; determining a normalized vote ratio using an expected number of harmonics in the frequency range; and comparing the normalized vote ratio to a harmonic threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. An acoustic signal classification system comprising:
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a processor; memory coupled to the processor, the memory comprising a first signal model and instructions operable to cause the processor to; obtain an input signal; determine a time-frequency representation of the input signal; determine whether a harmonic is present in the time-frequency representation; initiate spectrogram template matching, using the first signal model, in response to determining the harmonic is present; and forgo spectrogram template matching when the harmonic is not present; where the instructions that cause the processor to determine whether the harmonic is present are further operable to cause the processor to; establish a frequency range to scan; scan the time-frequency representation over the frequency range; identify local peaks in the frequency range that exceed neighboring spectrum values by more than a peak threshold; count votes for the local peaks; determine a normalized vote ratio using an expected number of harmonics in the frequency range; and compare the normalized vote ratio to a harmonic threshold. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A method for classifying an input signal, comprising:
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establishing a first signal model; obtaining an input signal; determining a time-frequency representation of the input signal; determining, by a processor, whether a harmonic is present in the time-frequency representation; initiating spectrogram template matching, using the first signal model, in response to determining that the harmonic is present; and forgoing spectrogram template matching when the harmonic is not present; where spectrogram template matching comprises; comparing the time-frequency representation with a plurality of time-frequency spectrogram templates; calculating a first root mean square distance difference between the time-frequency representation and a first template of the plurality of time-frequency spectrogram templates; calculating a second root mean square distance difference between the time-frequency representation and a second template of the plurality of time-frequency spectrogram templates; identifying the first template as a matching spectrogram template in response to determining that the first root mean square distance difference is lower than the second root mean square distance difference; and identifying the second template as the matching spectrogram template, by the processor, in response to a determination that the second root mean square distance difference is lower than the first root mean square distance difference.
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17. A method for classifying an input signal, comprising:
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obtaining an input signal; determining a time-frequency representation of the input signal; detecting a harmonic present in the time-frequency representation; and initiating spectrogram template matching by a processor in response to detecting the harmonic; where detecting the harmonic comprises; determining a frequency range to scan; scanning the time-frequency representation over the frequency range; identifying local peaks in the frequency range that exceed neighboring spectrum values by more than a peak threshold; counting votes for the local peaks; determining a normalized vote ratio using an expected number of harmonics in the frequency range; and comparing the normalized vote ratio to a harmonic threshold.
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18. A product comprising:
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a machine readable medium; and instructions stored on the machine readable medium that cause a processor in a signal processing system to; establish a first signal model; obtain an input signal; determine a time-frequency representation of the input signal; determine whether a harmonic is present in the time-frequency representation; initiate spectrogram template matching, using the first signal model, in response to determining that the harmonic is present; and forgo spectrogram template matching when the harmonic is not present; where the instructions that cause the system to determine whether the harmonic is present are further operable to cause the processor to; establish a frequency range to scan; scan the time-frequency representation over the frequency range; identify local peaks in the frequency range that exceed neighboring spectrum values by more than a peak threshold; count votes for the local peaks; determine a normalized vote ratio using an expected number of harmonics in the frequency range; and compare the normalized vote ratio to a harmonic threshold. - View Dependent Claims (19, 20, 21)
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Specification