Methods and apparatus to identify a mood of media

1. A method to identify an emotion evoked by media, the method comprising:

accessing a pre-verbal utterance known to evoke a first emotion;

creating, using a musical instrument digital interface notator, a musical instrument digital interface representation of the pre-verbal utterance;

synthesizing, using a digital musical instrument, a first synthesized sample based on the musical instrument digital interface representation of the pre-verbal utterance;

calculating, with a processor, a first value of a first feature of the first synthesized sample;

creating, with the processor, a mood model based on the first feature, the mood model to establish a relationship between the first value of the first feature and the first emotion;

identifying a second value of the first feature of first media evoking an unknown emotion; and

identifying the unknown emotion as the first emotion when the mood model indicates that the second value corresponds to the first value.

2. The method as described in claim 1 , wherein the first feature includes at least one of a number of zero crossings, a rolloff power, a brightness, a roughness, a presence of a minor third interval, a presence of a major third interval, an irregularity, a chroma, a main pitch, or a key.

3. The method as described in claim 1 , further including:

identifying a request for media evoking the first emotion; and

recommending second media as evoking the first emotion.

4. The method as described in claim 3 , wherein the second media is an advertisement.

5. The method as described in claim 1 , further including:

selecting a first reference value of the first feature of the first emotion;

calculating a first difference between the first reference value and the second value of the first feature of the first media; and

applying a first weighting value to the first difference to form a first feature score.

6. The method as described in claim 5 , further including identifying the unknown emotion as the first emotion when the first feature score exceeds a threshold.

7. The method as described in claim 5 , further including:

identifying a second reference value of a second feature of the first emotion, the second feature different from the first feature;

calculating a third value of the second feature of the first media;

calculating a second difference between the second reference value and the third value; and

applying a second weighting value to the second difference to form a second feature score.

8. The method as described in claim 1 , further including:

selecting an advertisement that evokes the first emotion evoked by the first media; and

presenting the advertisement in connection with the first media.

9. The method as described in claim 8 , wherein the advertisement includes audio and visual components, the method further including altering the audio component of the advertisement to more strongly evoke the first emotion.

10. The method as described in claim 1 , further including:

identifying a brand associated with the first emotion; and

generating an integrated advertisement identifying the brand; and

presenting the integrated advertisement at a same time as the first media.

11. A tangible machine readable storage medium comprising instructions which, when executed, cause a machine to at least:

access a pre-verbal utterance known to evoke a first emotion;

create a musical instrument digital interface representation of the pre-verbal utterance;

synthesize a first synthesized sample based on the musical instrument digital interface representation of the pre-verbal utterance using a digital musical instrument;

calculate a first value of a first feature of the first synthesized sample;

create a mood model based on the first value of the first feature, the mood model to correlate the first value of the first feature with the first emotion;

identify a second value of the first feature of first media evoking an unknown emotion; and

identify the unknown emotion as the first emotion when the mood model indicates that the second value corresponds to the first value.

12. The tangible computer readable storage medium as described in claim 11 , wherein the instructions, when executed, cause the machine to at least:

select a first reference value associated with a first feature-emotion pair, the first feature-emotion pair associated with the first feature and the first emotion;

select a first weighting value associated with the feature-emotion pair;

calculate a third value of the first feature of a first block of the first media;

calculate a first difference between the first reference value and the third value;

calculate a fourth value of the first feature of a second block of the first media, the second block different from the first block;

calculate a second difference between a second reference value and the fourth value;

apply a first weighting value to the first difference to form a first feature score;

apply the first weighting value to the second difference to form a second feature score; and

combine the first feature score and the second feature score to create a first combined feature score for the first feature-emotion pair.

13. The tangible computer readable storage medium as described in claim 12 , wherein the instructions, when executed, cause the machine to at least:

calculate a second combined feature score for a second feature-emotion pair associated with a second feature and the first emotion; and

determine a first emotion score for the first emotion based on the first combined feature score and the second combined feature score.

14. The tangible computer readable storage medium as described in claim 13 , wherein the instructions, when executed, cause the machine to at least:

determine a second emotion score for a second emotion, the second emotion different from the first emotion; and

select at least one of the first emotion or the second emotion as evoked by the first media based on the first emotion score and the second emotion score.

15. An apparatus to identify an emotion evoked by media, the apparatus comprising:

a musical instrument digital interface notator to create a musical instrument digital interface representation of a pre-verbal utterance associated with a first emotion;

a synthesizer to generate, using a digital musical instrument, a first synthesized sample based on the musical instrumented digital interface representation of the pre-verbal utterance;

a feature extractor to identify a first value of a first feature of the first synthesized sample, the feature extractor to identify a second value of the first feature of first media evoking an unknown emotion; and

a classification engine to create a mood model based on the first feature, the mood model to establish a relationship between the first value of the first feature and the first emotion, the classification engine to identify the first media as evoking the first emotion when the mood model indicates that the second value corresponds to the first value.

16. The apparatus as described in claim 15 , wherein the feature extractor is to identify a third value of the first feature of second media evoking the first emotion, and further including a mood model validator to validate the mood model by confirming that the mood model indicates that the first value of the first feature is within a threshold percentage of the third value of the first feature.

17. The apparatus as described in claim 16 , wherein the validator includes a semantic mapper to map a second emotion identified as being evoked by the first media to the first emotion.

18. The apparatus as described in claim 15 , further including a recommendation engine to recommend the first media in response to a request for media evoking the first emotion.