Synthesizing an aggregate voice

1. A computer implemented method for synthesizing multi-person speech into an aggregate voice, the method comprising:

crowd-sourcing a data message configured to include a textual passage;

collecting, from a plurality of speakers, a set of vocal data for the textual passage, wherein the set of vocal data includes a first set of enunciation data corresponding to a first portion of the textual passage, a second set of enunciation data corresponding to a second portion of the textual passage, and a third set of enunciation data corresponding to both the first and second portions of the textual passage;

mapping a source voice profile to a subset of the set of vocal data to synthesize the aggregate voice;

calculating, using a natural language processing technique configured to analyze the set of vocal data, a spoken word count for the first set of enunciation data;

computing, based on the spoken word count and a predetermined word quantity, reward credits:

transmitting, to a first speaker of the first set of enunciation data, the reward credits; and

transmitting, in response to synthesizing the aggregate voice, the aggregate voice to a remote device.

2. The method of claim 1 , wherein mapping the source voice profile to a subset of the set of vocal data to synthesize the aggregate voice includes:

extracting phonological data from the set of vocal data, wherein the phonological data includes pronunciation tags, intonation tags, and syllable rates;

converting, based on the phonological data including pronunciation tags, intonation tags and syllable rates, the set of vocal data into a set of phoneme strings; and

applying, to the set of phoneme strings, the source voice profile.

3. The method of claim 1 , wherein the source voice profile includes a predetermined set of phonological and prosodic characteristics corresponding to a voice of a first individual.

4. The method of claim 3 , wherein the phonological and prosodic characteristics include rhythm, stress, tone, and intonation.

5. The method of claim 1 , further comprising:

assigning, based on evaluating the phonological data from the set of vocal data, a first quality score to the first set of enunciation data; and

transmitting, in response to determining that the first quality score is greater than a first quality threshold, bonus credits to the first speaker.

6. The method of claim 1 , further comprising:

detecting, by an incentive system, a transition phase of an entertainment content sequence;

presenting, during the transition phase of the entertainment content sequence, a speech sample collection module configured to record enunciation data for the textual passage; and

advancing, in response to recording enunciation data for the textual passage, the entertainment content sequence.

7. A system for synthesizing multi-person speech into an aggregate voice, the system comprising:

a crowd-sourcing module configured to crowd-source a data message including a textual passage;

a collecting module configured to collect, from a plurality of speakers, a set of vocal data for the textual passage, wherein the set of vocal data includes a first set of enunciation data corresponding to a first portion of the textual passage, a second set of enunciation data corresponding to a second portion of the textual passage, and a third set of enunciation data corresponding to both the first and second portions of the textual passage;

a mapping module configured to map a source voice profile to a subset of the set of vocal data to synthesize the aggregate voice, the mapping module further comprising:

an extracting module configured to extract phonological data from the set of vocal data, wherein the phonological data includes pronunciation tags, intonation tags, and syllable rates;

a converting module configured to convert, based on the phonological data including pronunciation tags, intonation tags and syllable rates, the set of vocal data into a set of phoneme strings; and

an applying module configured to apply, to the set of phoneme strings, the source voice profile;

a calculating module configured to calculate, using a natural language processing technique to analyze the set of vocal data, a spoken word count for the first set of enunciation data.

a computing module configured to compute, based on the spoken word count and a predetermined word quantity, reward credits; and

a transmitting module configured to transmit, to a first speaker of the first set of enunciation data, the reward credits, wherein the transmitting module is further configured to transmit the aggregate voice to a remote device.

8. The system of claim 7 , wherein the source voice profile includes a predetermined set of phonological and prosodic characteristics corresponding to a voice of a first individual.

9. The system of claim 8 , wherein the phonological and prosodic characteristics include rhythm, stress, tone, and intonation.

10. The system of claim 7 , further comprising:

an assigning module configured to assign, based on evaluating the phonological data from the set of vocal data, a first quality score to the first set of enunciation data; and

wherein the transmitting module is configured to transmit, in response to determining that the first quality score is greater than a first quality threshold, bonus credits to the first speaker.

11. The system of claim 7 , further comprising:

a detecting module configured to detect, using an incentive system, a transition phase of an entertainment content sequence;

a presenting module configured to present, during the transition phase of the entertainment content sequence, a speech sample collection module configured to record enunciation data for the textual passage; and

an advancing module configured to advance, in response to recording enunciation data for the textual passage, the entertainment content sequence.

12. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable storage medium is not a transitory signal per se, wherein the computer readable program, when executed on a first computing device, causes the first computing device to:

crowd-source a data message configured to include a textual passage;

collect, from a plurality of speakers, a set of vocal data for the textual passage;

map a source voice profile to a subset of the set of vocal data to synthesize the aggregate voice;

calculating, using a natural language processing technique configured to analyze the set of vocal data, a spoken word count for a first set of enunciation data;

assigning, based on evaluating phonological data from the set of vocal data, a first quality score to the first set of enunciation data;

computing, based on the first quality score, the spoken word count, and a predetermined word quantity, reward credits;

transmitting, in response to determining that the first quality score is greater than a first quality threshold, the reward credits to the first speaker; and

transmitting, in response to synthesizing the aggregate voice, the aggregate voice to a remote device.

13. The computer program product of claim 12 , further comprising computer readable program code configured to:

extract phonological data from the set of vocal data, wherein the phonological data includes pronunciation tags, intonation tags, and syllable rates;

convert, based on the phonological data including pronunciation tags, intonation tags and syllable rates, the set of vocal data into a set of phoneme strings; and

apply, to the set of phoneme strings, the source voice profile.

14. The computer program product of claim 12 , further comprising computer readable program code configured to:

detect, by an incentive system, a transition phase of an entertainment content sequence;

present, during the transition phase of the entertainment content sequence, a speech sample collection module configured to record enunciation data for the textual passage; and

advance, in response to recording enunciation data for the textual passage, the entertainment content sequence.