Methods and apparatus to determine audio source impact on an audience of media
Methods, apparatus, systems and articles of manufacture to determine audio source impact on an audience of media are disclosed. A disclosed example method includes dividing monitored audio into successive audio segments including a first audio segment and a second audio segment. The example method also includes generating a first confidence value from the first audio segment and a second confidence value from the second audio segment, the first confidence value associated with a presence of a first audio source in the first audio segment, the second confidence value associated with a presence of the first audio source in the second audio segment. The example method includes determining an impact of the presence of the first audio source on audience ratings associated with the monitored audio based on the first confidence value, the first quantity of audience members, the second confidence value and the second quantity of audience members to determine.
1. An apparatus comprising:
an audio segmenter implemented by hardware or at least one processor, the audio segmenter to divide monitored audio into successive audio segments including a first audio segment and a second audio segment, the first audio segment associated with a first quantity of audience members exposed to the monitored audio during the first audio segment, the second audio segment associated with a second quantity of audience members exposed to the monitored audio during the second audio segment;
a speaker evaluator to generate a first confidence value from the first audio segment of the successive segments and a second confidence value from the second audio segment, the first confidence value associated with a presence of a first audio source in the first audio segment, the second confidence value associated with a presence of the first audio source in the second audio segment; and
an audience rating correlator to determine an impact of the presence of the first audio source on audience ratings associated with the monitored audio based on the first confidence value, the first quantity of audience members, the second confidence value and the second quantity of audience members.
2. The apparatus of claim 1 , wherein the speaker evaluator includes:
a speech pattern generator to generate a pattern from the first audio segment; and
a pattern comparator to compare the generated pattern to a set of reference patterns to generate the first confidence value, the set of reference patterns associated with the first audio source.
3. The apparatus of claim 2 , wherein the pattern comparator is to compare the generated pattern to the set of reference patterns based on linear regression.
4. The apparatus of claim 1 , wherein the speaker evaluator is further to generate a third confidence value for the first audio segment, the third confidence value associated with a presence of a second audio source in the first audio segment, and further including a dominant speaker identifier to compare the first confidence value and the third confidence value to determine a dominant audio source in the first segment.
5. The apparatus of claim 1 , wherein the first audio source corresponds to a voice of a first person, and further including:
a sentiment analyzer to:
identify a first dialogue associated with the first person and the first segment;
identify a second dialogue associated with the first person and the second segment;
determine a first sentiment associated with the first dialogue and a second sentiment associated with the second dialogue; and
the audience rating correlator is to correlate a first difference between the first quantity of audience members and the second quantity of audience members and a second difference between the first sentiment and the second sentiment.
6. A non-transitory computer readable medium comprising instructions that, when executed, cause a processor to at least:
divide monitored audio into successive audio segments including a first audio segment and a second audio segment, the first audio segment associated with a first quantity of audience members exposed to the monitored audio during the first audio segment, the second audio segment associated with a second quantity of audience members exposed to the monitored audio during the second audio segment;
generate a first confidence value from the first audio segment and a second confidence value from the second audio segment, the first confidence value associated with a presence of a first audio source in the first audio segment, the second confidence value associated with a presence of the first audio source in the second audio segment; and
determine an impact of the presence of the first audio source on audience ratings associated with the monitored audio based on the first confidence value, the first quantity of audience members, the second confidence value and the second quantity of audience members.
7. The non-transitory computer readable medium of claim 6 , wherein the instructions, when executed, cause the processer to:
generate a pattern from the first audio segment; and
compare the generated pattern to a set of reference patterns to generate the first confidence value, the set of reference patterns associated with the first audio source.
8. The non-transitory computer readable medium of claim 7 , wherein the comparison of the generated pattern to the set of reference patterns is based on linear regression.
9. The non-transitory computer readable medium of claim 6 , wherein the instructions, when executed, further cause the processer to:
generate a third confidence value for the first audio segment, the third confidence value associated with a presence of a second audio source in the first audio segment; and
compare the first confidence value and the third confidence value to determine a dominant audio source in the first segment.
10. The non-transitory computer readable medium of claim 6 , wherein the first audio source corresponds to a voice of a first person, and the instructions, when executed, cause the processer to:
identify a first dialogue associated with the first person and the first segment;
identify a second dialogue associated with the first person and the second segment;
determine a first sentiment associated with the first dialogue and a second sentiment associated with the second dialogue; and
correlate a first difference between the first quantity of audience members and the second quantity of audience members and a second difference between the first sentiment and the second sentiment.
11. An apparatus comprising:
a memory including instructions; and
a processor to execute the instructions to:
divide monitored audio into successive audio segments including a first audio segment and a second audio segment, the first audio segment associated with a first quantity of audience members exposed to the monitored audio during the first audio segment, the second audio segment associated with a second quantity of audience members exposed to the monitored audio during the second audio segment;
generate a first confidence value from the first audio segment and a second confidence value from the second audio segment, the first confidence value associated with a presence of a first audio source in the first audio segment, the second confidence value associated with a presence of the first audio source in the second audio segment; and
determine an impact of the presence of the first audio source on audience ratings associated with the monitored audio based on the first confidence value, the first quantity of audience members, the second confidence value and the second quantity of audience members.
12. The apparatus of claim 11 , wherein the processor further executes the instructions to:
generate a pattern from the first audio segment; and
compare the generated pattern to a set of reference patterns to generate the first confidence value, the set of reference patterns associated with the first audio source.
13. The apparatus of claim 12 , wherein the comparison of the generated pattern to the set of reference patterns is based on linear regression.
14. The apparatus of claim 11 , wherein the processor further executes the instructions to:
generate a third confidence value for the first audio segment, the third confidence value associated with a presence of a second audio source in the first audio segment; and
compare the first confidence value and the third confidence value to determine a dominant audio source in the first segment.
15. The apparatus of claim 11 , wherein the first audio source corresponds to a voice of a first person and the processor further executes the instructions to:
identify a first dialogue associated with the first person and the first segment;
identify a second dialogue associated with the first person and the second segment;
determine a first sentiment associated with the first dialogue and a second sentiment associated with the second dialogue; and
correlate a first difference between the first quantity of audience members and the second quantity of audience members and a second difference between the first sentiment and the second sentiment.
16. A method comprising:
dividing, by executing an instruction with a processor, monitored audio into successive audio segments including a first audio segment and a second audio segment, the first audio segment associated with a first quantity of audience members exposed to the monitored audio during the first audio segment, the second audio segment associated with a second quantity of audience members exposed to the monitored audio during the second audio segment;
generating, by executing an instruction with the processor, a first confidence value from the first audio segment and a second confidence value from the second audio segment, the first confidence value associated with a presence of a first audio source in the first audio segment, the second confidence value associated with a presence of the first audio source in the second audio segment; and
determining, by executing an instruction with the processor, an impact of the presence of the first audio source on audience ratings associated with the monitored audio based on the first confidence value, the first quantity of audience members, the second confidence value and the second quantity of audience members to determine.
17. The method of claim 16 , wherein the generating of the first confidence value includes:
generating a pattern from the first audio segment; and
comparing the generated pattern to a set of reference patterns to generate the first confidence value, the set of reference patterns associated with the first audio source.
18. The method of claim 17 , wherein the comparing of the generated pattern to the set of reference patterns is based on linear regression.
19. The method of claim 16 , further including:
generating a third confidence value for the first audio segment, the third confidence value associated with a presence of a second audio source in the first audio segment; and
comparing the first confidence value and the third confidence value to determine a dominant audio source in the first segment.
20. The method of claim 16 , wherein the first audio source corresponds to a voice of a first person and further including:
identifying a first dialogue associated with the first person and the first segment;
identifying a second dialogue associated with the first person and the second segment;
determining a first sentiment associated with the first dialogue and a second sentiment associated with the second dialogue; and
correlating a first difference between the first quantity of audience members and the second quantity of audience members and a second difference between the first sentiment and the second sentiment.