Audio decoding with supplemental semantic audio recognition and report generation
View Patent ↗System, apparatus and method for determining semantic information from audio, where incoming audio is sampled and processed to extract audio features, including temporal, spectral, harmonic and rhythmic features. The extracted audio features are compared to stored audio templates that include ranges and/or values for certain features and are tagged for specific ranges and/or values. The semantic information may be associated with audio codes to determine changing characteristics of identified media during a time period.
1. A processor-based method for producing supplemental information for media containing embedded audio codes, wherein the codes are read from an audio portion of the media, the method comprising the steps of:
receiving the audio codes at an input from a data network, said audio codes being received from a device during a first time period, said audio codes representing a first characteristic of the audio portion;
receiving semantic audio signature data at the input from the data network, said semantic audio signature data being received from the device for the first time period, wherein the semantic audio signature comprises at least one of temporal, spectral, harmonic and rhythmic features relating to a second characteristic of the media content; and
successively associating the semantic audio signature data to the audio codes in a processor for the first time period.
2. The method of claim 1 , wherein the semantic audio signature data temporal features comprise at least one of amplitude, power and zero crossing of at least some of the media content audio.
3. The method of claim 1 , wherein the semantic audio signature data spectral features comprise at least one of spectral centroid, spectral rolloff, spectral flux, spectral flatness measure, spectral crest factor, Mel-frequency cepstral coefficients, Daubechies wavelet coefficients, sopectral dissonance, spectral irregularity and spectral inharmonicity of at least some of the media content audio.
4. The method of claim 1 , wherein the semantic audio signature data harmonic features comprise at least one of pitch, tonality, pitch class profile, harmonic changes, main pitch class, octave range of dominant pitch, main tonal interval relation and overall pitch strength of at least some of the media content audio.
5. The method of claim 1 , wherein the semantic audio signature data rhythmic features comprise at least one of rhythmic structure, beat period, rhythmic fluctuation and average tempo for at least some of the media content audio.
6. The method of claim 1 , wherein the audio codes are formed by transforming at least some of the audio signals from a time domain to a frequency domain.
7. The method of claim 1 , wherein the semantic audio signature data is formed by transforming at least some of the audio signals from a time domain to a frequency domain.
8. A system for producing supplemental information for media containing embedded audio codes, wherein the codes are read from an audio portion of the media, comprising:
an input configured to receive the audio codes from a data network, said audio codes being received from a device during a first time period, wherein the audio codes representing a first characteristic of the audio portion;
said input being further configured to receive semantic audio signature data from the data network, said semantic audio signature data being received from the device for the first time period, wherein the semantic audio signature comprises at least one of temporal, spectral, harmonic and rhythmic features relating to a second characteristic of the media content; and
a processor, operatively coupled to the input, said processor being configured to successively associate the semantic audio signature data to the audio codes in a processor for the first time period.
9. The system of claim 8 , wherein the semantic audio signature data temporal features comprise at least one of amplitude, power and zero crossing of at least some of the media content audio.
10. The system of claim 8 , wherein the semantic audio signature data spectral features comprise at least one of spectral centroid, spectral rolloff, spectral flux, spectral flatness measure, spectral crest factor, Mel-frequency cepstral coefficients, Daubechies wavelet coefficients, sopectral dissonance, spectral irregularity and spectral inharmonicity of at least some of the media content audio.
11. The system of claim 8 , wherein the semantic audio signature data harmonic features comprise at least one of pitch, tonality, pitch class profile, harmonic changes, main pitch class, octave range of dominant pitch, main tonal interval relation and overall pitch strength of at least some of the media content audio.
12. The system of claim 8 , wherein the semantic audio signature data rhythmic features comprise at least one of rhythmic structure, beat period, rhythmic fluctuation and average tempo for at least some of the media content audio.
13. The system of claim 8 , wherein the audio codes are formed by transforming at least some of the audio signals from a time domain to a frequency domain.
14. The system of claim 8 , wherein the semantic audio signature data is formed by transforming at least some of the audio signals from a time domain to a frequency domain.
15. A processor-based method for producing supplemental information for media containing embedded audio codes, wherein the codes are read from an audio portion of the media, the method comprising the steps of:
receiving the audio codes at an input from a data network, said audio codes being received from a device during a first time period, wherein the audio codes represent a first characteristic of audio portion;
receiving semantic audio signature data at the input from the data network, said semantic audio signature data being received from the device for the first time period, wherein the semantic audio signature comprises at least one of temporal, spectral, harmonic and rhythmic features relating to a second characteristic of the media content;
successively associating the semantic audio signature data to the audio codes in a processor for the first time period; and
processing the associated semantic audio signature data and audio codes data to determine changing second characteristics in relation to the first characteristic.
16. The method of claim 15 , wherein the second characteristic comprises at least one of:
the temporal features comprising at least one of amplitude, power and zero crossing of at least some of the media content,
the spectral features comprising at least one of spectral centroid, spectral rolloff, spectral flux, spectral flatness measure, spectral crest factor, Mel-frequency cepstral coefficients, Daubechies wavelet coefficients, sopectral dissonance, spectral irregularity and spectral inharmonicity of at least some of the media content,
the harmonic features comprising at least one of pitch, tonality, pitch class profile, harmonic changes, main pitch class, octave range of dominant pitch, main tonal interval relation and overall pitch strength of at least some of the media content,
the rhythmic features comprising at least one of rhythmic structure, beat period, rhythmic fluctuation and average tempo for at least some of the audio signals.
17. The method of claim 15 , wherein the first characteristic data comprises one of media content identification, media content distributor identification, and media content broadcaster identification.
18. The method of claim 15 , wherein the second characteristic data comprises one of genre, instrumentation, style, acoustical dynamics and emotive descriptors.
19. The method of claim 15 , wherein the audio codes are formed by transforming at least some of the media content from a time domain to a frequency domain.
20. The method of claim 15 , wherein the semantic audio signature data is formed by transforming at least some of the media content from a time domain to a frequency domain.