Abstract: An example method includes receiving, by one or more processors of a computing device, audio data recorded by one or more microphones of the computing device; and generating, based on the audio data and by the one or more processors, one or more structured sound records, a first structured sound record of the one or more structured sound records including: a description of a first sound, the description including a descriptive label of the first sound, the descriptive label different than a text transcription of the first sound, and a time stamp indicating a time at which the first sound occurred; and outputting a graphical user interface including timeline representation of the one or more structured sound records.

Abstract: Methods, systems, and media for identifying similar songs using jumpcodes are provided. In some embodiments, methods for a cover song from a query song are provided, the methods comprising: identifying a query song jumpcode for the query song, wherein the query song jumpcode is indicative of changes in prominent pitch over a portion of the query song; identifying a plurality of reference song jumpcodes for a reference song, wherein each of the reference song jumpcodes is indicative of changes in prominent pitch over a portion of the reference song; determining if the query song jumpcode matches any of the plurality of reference song jumpcodes; and upon determining that the query song jumpcode matches at least one of the plurality of reference song jumpcodes, generating an indication that the reference song is a cover song of the query song.

Abstract: Apparatus and methods for processing compression encoded signals are provided. In some embodiments, a signal processing method is provided that includes receiving a subband of a compression encoded signal at a subband processor, generating envelope information regarding the subband of the compression encoded signal to provide changes in the dynamic range of the compression encoded signal for fixed-point digital signal processing, processing the compression encoded signal with a fixed-point companding digital signal processor using the envelope information, and producing a processed compression encoded signal at the output of the subband processor.

Abstract: System, methods, and media that: receive a first piece of audio content; identify a first plurality of atoms that describe at least a portion of the first piece of audio content using a Matching Pursuit algorithm; form a first group of atoms from at least a portion of the first plurality of atoms, the first group of atoms having first group parameters; form at least one first hash value for the first group of atoms based on the first group parameters; compare the at least one first hash value with at least one second hash value, wherein the at least one second hash value is based on second group parameters of a second group of atoms associated with a second piece of audio content; and identify a match between the first piece of audio content and the second piece of audio content based on the comparing.

Abstract: Methods and systems for analyzing gross resource consumption data to determine resource consumption of individual devices are disclosed. In some embodiments, the methods and methods include the following: obtaining a first data that includes a time series of a gross resource consumption for a location; using blind signal separation techniques, identifying power-on and power-off events within the first data, the events being caused by turning particular devices at the location on and off during the time series and each of the events reflecting a power consumption signature for each of the particular devices; associating each of the events with a known device, the known device being substantially similar to one of the particular devices at the location; and determining a portion of the gross resource consumption consumed by each of the particular devices.

Abstract: Methods, systems, and media for mobile audio event recognition are provided. In some embodiments, a method for recognizing audio events is provided, the method comprising: receiving an application that includes a plurality of classification models from a server, wherein each of the plurality of classification models is trained to identify one of a plurality of classes of non-speech audio events; receiving an audio signal; storing at least a portion of the audio signal; extracting, a plurality of audio features from the portion of the audio signal based on one or more criterion; comparing each of the plurality of extracted audio features with the plurality of classification models; identifying at least one class of non-speech audio events present in the portion of the audio signal based on the comparison; and providing an alert corresponding to the at least one class of identified non-speech audio events.

Abstract: Apparatus and methods for processing compression encoded signals are provided. In some embodiments, a signal processing method is provided that includes receiving a subband of a compression encoded signal at a subband processor, generating envelope information regarding the subband of the compression encoded signal to provide changes in the dynamic range of the compression encoded signal for fixed-point digital signal processing, processing the compression encoded signal with a fixed-point companding digital signal processor using the envelope information, and producing a processed compression encoded signal at the output of the subband processor.

Abstract: System, methods, and media that: receive a first piece of audio content; identify a first plurality of atoms that describe at least a portion of the first piece of audio content using a Matching Pursuit algorithm; form a first group of atoms from at least a portion of the first plurality of atoms, the first group of atoms having first group parameters; form at least one first hash value for the first group of atoms based on the first group parameters; compare the at least one first hash value with at least one second hash value, wherein the at least one second hash value is based on second group parameters of a second group of atoms associated with a second piece of audio content; and identify a match between the first piece of audio content and the second piece of audio content based on the comparing.

Abstract: Methods and systems for identifying similar songs are provided. In accordance with some embodiments, methods for identifying similar songs are provided, the methods comprising: identifying beats in at least a portion of a song; generating beat-level descriptors of the at least a portion of the song corresponding to the beats; comparing the beat-level descriptors to other beat-level descriptors corresponding to a plurality of songs. In accordance with some embodiments, systems for identifying similar songs are provided, the systems comprising: a digital processing device that: identifies beats in at least a portion of a song; generates beat-level descriptors of the at least a portion of the song corresponding to the beats; and compares the beat-level descriptors to other beat-level descriptors corresponding to a plurality of songs.

Abstract: Methods, systems, and media are provided for classifying digital music. In some embodiments, methods of classifying a song are provided that include: receiving a selection of at least one seed song; receiving a label selection for at least one unlabeled song; training a support vector machine based on the at least one seed song and the label selection; and classifying a song using the support vector machine. In some embodiments, systems for classifying a song are provided that include: memory for storing at least one seed song, at least one unlabeled song, and a song; and a processor that: receives a selection of the at least one seed song; receives a label selection for the at least one unlabeled song; trains a support vector machine based on the at least one seed song and the label selection; and classifies the song using the support vector machine.

Abstract: In accordance with the present invention, computer implemented methods and systems are provided for representing and modeling the temporal structure of audio signals. In response to receiving a signal, a time-to-frequency domain transformation on at least a portion of the received signal to generate a frequency domain representation is performed. The time-to-frequency domain transformation converts the signal from a time domain representation to the frequency domain representation. A frequency domain linear prediction (FDLP) is performed on the frequency domain representation to estimate a temporal envelope of the frequency domain representation. Based on the temporal envelope, one or more speech features are generated.

Abstract: In accordance with the present invention, computer implemented methods and systems are provided for representing and modeling the temporal structure of audio signals. In response to receiving a signal, a time-to-frequency domain transformation on at least a portion of the received signal to generate a frequency domain representation is performed. The time-to-frequency domain transformation converts the signal from a time domain representation to the frequency domain representation. A frequency domain linear prediction (FDLP) is performed on the frequency domain representation to estimate a temporal envelope of the frequency domain representation. Based on the temporal envelope, one or more speech features are generated.

Abstract: In accordance with the present invention, computer implemented methods and systems are provided for representing and modeling the temporal structure of audio signals. In response to receiving a signal, a time-to-frequency domain transformation on at least a portion of the received signal to generate a frequency domain representation is performed. The time-to-frequency domain transformation converts the signal from a time domain representation to the frequency domain representation. A frequency domain linear prediction (FDLP) is performed on the frequency domain representation to estimate a temporal envelope of the frequency domain representation. Based on the temporal envelope, one or more speech features are generated.

Abstract: Methods, systems, and media are provided for classifying digital music. In some embodiments, methods of classifying a song are provided that include: receiving a selection of at least one seed song; receiving a label selection for at least one unlabeled song; training a support vector machine based on the at least one seed song and the label selection; and classifying a song using the support vector machine. In some embodiments, systems for classifying a song are provided that include: memory for storing at least one seed song, at least one unlabeled song, and a song; and a processor that: receives a selection of the at least one seed song; receives a label selection for the at least one unlabeled song; trains a support vector machine based on the at least one seed song and the label selection; and classifies the song using the support vector machine.