Adaptive system for broadcast program identification and reporting
First Claim
1. A computer-implemented method for identifying and reporting an audible performance of a musical work recorded in a medium of fixed expression, said method comprising the steps of:
- (a) training a neural network to generate an output signal corresponding to recognition of a selected retinal sample of said audible performance;
(b) receiving an audio signal from a performance broadcast;
(c) processing said audio signal to create a series of overlapping retinal samples of said audible performance, wherein each said retinal sample includes a plurality of digital signals representing a spectral and temporal distribution of power of said audio signal;
(d) generating said neural network output signal responsive to said series of overlapping retinal samples;
(e) comparing each said neural network output signal with a corresponding predetermined threshold signal; and
(f) logging a record of the broadcast of said musical work performance responsive to said neural network output signal exceeding said corresponding predetermined threshold signal.
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Accused Products
Abstract
A computer-implemented method and system for monitoring, identifying, classifying and logging musical work performance broadcasts over the public airwaves. The system uses a neural network to classify specially-processed "retinal" signatures of the musical work performance. The neural network is trained for each musical work using a single noise-biased retinal sample of the spectral distribution of preselected dynamic features of the corresponding audio signal. A detection decision is made at the neural network output using fuzzy logic circuitry to compare results of predetermined thresholding. The system of this invention fully automates the real-time identification of broadcast musical work performances.
251 Citations
13 Claims
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1. A computer-implemented method for identifying and reporting an audible performance of a musical work recorded in a medium of fixed expression, said method comprising the steps of:
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(a) training a neural network to generate an output signal corresponding to recognition of a selected retinal sample of said audible performance; (b) receiving an audio signal from a performance broadcast; (c) processing said audio signal to create a series of overlapping retinal samples of said audible performance, wherein each said retinal sample includes a plurality of digital signals representing a spectral and temporal distribution of power of said audio signal; (d) generating said neural network output signal responsive to said series of overlapping retinal samples; (e) comparing each said neural network output signal with a corresponding predetermined threshold signal; and (f) logging a record of the broadcast of said musical work performance responsive to said neural network output signal exceeding said corresponding predetermined threshold signal. - View Dependent Claims (2, 3)
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4. A computer-implemented method for identifying an Ith one of a plurality S of musical works from a first audio signal A1s representing a first audible performance of a musical work, wherein for each of said plurality S of musical works a set of R weights (Wr)s is predetermined responsive to a portion P2s spanning a retinal time interval tR of a second audio signal A2s representing a second audible performance of said each musical work, wherein 1≦
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S and 1≦
r≦
R are non-zero positive integers, said method comprising the steps of;(a) creating a plurality R of retinal signals (Sr) representing a spectral and temporal distribution of power in a portion P1s of said first audio signal A1s spanning a retinal time interval tR ; (b) combining said retinal signals (Sr) with each of a plurality S of weight sets (Wr)s to create a plurality S of neural output signals (Ns) each representing a weighted combination of said retinal signals (Sr) ; (c) creating a plurality S of ratio signals (Ns /Ts) each corresponding to the ratio of each of said neural output signals (Ns) to a corresponding predetermined alarm threshold signal Ts ; (d) if at least one of said ratio signals (Ns /Ts) exceeds unity, selecting an Ith neural output signal NI =Ns corresponding to a greatest said ratio signal NI /TI of said plurality S of ratio signals (Ns /Ts), whereby said neural output signal NI represents an identity of said Ith musical work, otherwise selecting nothing; (e) making an alarm log record responsive to said selection of said neural output signal NI, said alarm log record including an alarm date, an alarm time, and the identity of said Ith musical work; and (f) repeating said steps (a)-(f) responsive to a passage of an updating time interval tU <
tR. - View Dependent Claims (5, 6, 7, 8, 9, 10)
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11. A system for identifying and logging a broadcast of an audible performance of a musical work recorded in a medium of fixed expression, said system comprising:
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input means for receiving an audio signal from a performance broadcast; processing means coupled to said input means for creating a series of overlapping retinal samples of audio signal, wherein each said retinal sample includes a plurality of digital signals representing a spectral and temporal distribution of power of said audio signal power; neural network means coupled to said processing means for creating a neural output signal representing a recognition of said each retinal sample; training means coupled to said neural network means for training said neural network means to generate said neural output signal corresponding to recognition of a selected retinal sample of said audible performance; and logging means for storing a record of a recognition of said broadcast of said musical work performance responsive to each said neural output signal in excess of a predetermined threshold signal. - View Dependent Claims (12, 13)
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Specification