Feature-based audio content identification

A method for forming an identifying feature of a portion of a recording of audio signals, said method comprising the steps of:

• performing a Fourier transformation of the audio signals of the portion into a time series of audio power dissipated over a first plurality of frequencies;
• grouping the frequencies into a smaller second plurality of bands that each include a range of neighboring frequencies;
• detecting power dissipation events in each of the bands;
• and
• grouping together the power dissipation events from mutually adjacent bands at a selected moment so as to form the identifying feature,
• wherein each of the power dissipation events is a crossing of the value of a first running average and the value of a second running average,
• the first running average is an average over a first averaging period of the audio power dissipated, and
• the second running average is an average over a second averaging period, which is different than the first averaging period, of the audio power dissipated.

A computer-readable medium encoded with a program for identifying audio content, said program containing instructions for performing the steps of:

• obtaining an audio signal;
• analyzing the power spectrum of the audio signal so as to obtain a plurality of time dependent frequency components;
• and
• detecting a plurality of events, each of the events being a crossing of the value of a first running average and the value of a second running average,
• wherein the first running average is an average over a first averaging period of a first subset of the time dependent frequency components, and
• the second running average is an average over a second averaging period, which is different than the first averaging period, of the first subset of the time dependent frequency components.

A computer-readable medium encoded with a program for forming an identifying feature of a portion of a recording of audio signals, said program containing instructions for performing the steps of:

• performing a Fourier transformation of the audio signals of the portion into a time series of audio power dissipated over a first plurality of frequencies;
• grouping the frequencies into a smaller second plurality of bands that each include a range of neighboring frequencies;
• detecting power dissipation events in each of the bands;
• and
• grouping together the power dissipation events from mutually adjacent bands at a selected moment so as to form the identifying feature,
• wherein each of the power dissipation events is a crossing of the value of a first running average and the value of a second running average,
• the first running average is an average over a first averaging period of the audio power dissipated, and
• the second running average is an average over a second averaging period, which is different than the first averaging period, of the audio power dissipated.

A system for identifying a recording of an audio signal, said system comprising:

• an interface for receiving an audio signal to be identified;
• a spectrum analyzer for analyzing the power spectrum of the audio signal so as to produce a plurality of time dependent frequency components from the audio signal;
• an event detector for detecting a plurality of events in each of the time dependent frequency components;
• and
• a key generator for grouping the plurality of events by frequency and time, and assembling a plurality of keys based on the plurality of events,
• wherein each of the events detected by the event detector is a crossing of the value of a first running average and the value of a second running average,
• the first running average is an average over a first averaging period of a first subset of the time dependent frequency components, and
• the second running average is an average over a second averaging period, which is different than the first averaging period, of the first subset of the time dependent frequency components.

A system for forming an identifying feature of a portion of a recording of audio signals, said system comprising:

• means for performing a Fourier transformation of the audio signals of the portion into a time series of audio power dissipated over a first plurality of frequencies;
• means for grouping the frequencies into a smaller second plurality of bands that each include a range of neighboring frequencies;
• means for detecting power dissipation events in each of the bands;
• and
• means for grouping together the power dissipation events from mutually adjacent bands at a selected moment so as to form the identifying feature,
• wherein each of the power dissipation events detected by the means for detecting is a crossing of the value of a first running average and the value of a second running average,
• the first running average is an average over a first averaging period of the audio power dissipated, and
• the second running average is an average over a second averaging period, which is different than the first averaging period, of the audio power dissipated.