ADAPTIVE DIGITAL ASSISTANT AND SPOKEN GENOME

1 . A computer-implemented method for personalized digital interaction comprising:

selecting a starter vocabulary from a starter vocabulary set;

receiving a plurality of user voice communications from a user;

generating a frequent word list based at least in part on the plurality of user voice communications;

modifying the starter vocabulary with a plurality of words from the frequent word list to generate a personalized lexicon; and

generating a personalized verbal output based at least in part on the personalized lexicon.

2 . The method of claim 1 , further comprising receiving a secondary learning input from a smart device and modifying the personalized vocabulary based at least in part on the secondary learning input.

3 . The method of claim 1 , wherein selecting the starter vocabulary comprises:

receiving a user demographic data set,

comparing the user demographic data set to a plurality of characteristics of the starter vocabulary set, and

determining, based at least in part on the comparison, a preferred starter vocabulary.

4 . The method of claim 1 , further comprising receiving a voice command from the user.

5 . The method of claim 4 , further comprising:

analyzing the voice command to determine a mood; and

adjusting a characteristic of the personalized verbal output based at least in part on the mood.

6 . The method of claim 1 , further comprising selecting a specialized vocabulary and augmenting the personalized lexicon with the specialized vocabulary.

7 . The method of claim 1 , further comprising selecting a set of accent features and adjusting a characteristic of the personalized verbal output based at least in part on the accent features.

8 . The method of claim 1 , wherein modifying the starter vocabulary comprises replacing a word from the starter vocabulary with a frequent word from the frequent word list or augmenting the starter vocabulary with a new word from the frequent word list.

9 . The method of claim 1 , wherein the personalized verbal output comprises a personalized gender, pitch, cadence, tonality, rhythm, accent, timing, slurring, elocution, or combination thereof.

10 . The method of claim 1 , further comprising communicating with an external classification system.

11 . A computer program product for characterization and analysis of human voice, wherein the computer program product comprises:

a computer readable storage medium readable by a processing circuit and storing program instructions for execution by the processing circuit for performing a method comprising:

receiving a plurality of media files, wherein the plurality of media files comprise spoken words;

categorizing the plurality of media files according to spoken genome properties to create a categorized spoken genome database;

receiving a user media preference;

determining a user media profile based at least in part on the user media preference, wherein the media profile comprises a spoken genome property; and

providing a media recommendation based at least in part on the user media profile and the categorized spoken genome database.

12 . The computer program product of claim 11 , wherein the spoken genome property is selected from the group consisting of gender, pitch, cadence, tonality, rhythm, accent, timing, slurring, and elocution.

13 . The computer program product of claim 11 , wherein the media recommendation comprises a recommended television program, a recommended movie, or a recommended audio book.

14 . A processing system for characterization and analysis of human voice comprising:

a processor in communication with one or more types of memory, the processor configured to:

receive a first reference voice sampling, wherein the first reference voice sampling comprises a plurality of reference voices corresponding to a first known reference quality; and

analyze the first voice sampling to determine a spoken genome property corresponding to the first known reference quality.

15 . The processing system of claim 14 , wherein the processor is configured to output the spoken genome property corresponding to the first known reference quality.

16 . The processing system of claim 14 , wherein the processor is configured to:

receive a second reference voice sampling, wherein the second reference voice sampling comprises a plurality of reference voices corresponding to a second known reference quality; and

analyze the second voice sampling to determine a spoken genome property corresponding to the second known reference quality.

17 . The processing system of claim 16 , wherein the processor is further configured to generate a spoken genome database, wherein the spoken genome database comprises:

a first bin comprising the first known reference quality and the spoken genome property corresponding to the first known reference quality, and

a second bin comprising the second known reference quality and the spoken genome property corresponding to the second known reference quality.

18 . The processing system of claim 14 , wherein the processor is further configured to:

receive a target voice input corresponding to a candidate;

determine a spoken genome property corresponding to the target voice input;

compare the target voice input spoken genome property to the spoken genome property corresponding to the first known reference quality; and

determine whether the candidate corresponds to the first known reference quality.

19 . The processing system of claim 18 , wherein the processor is configured to output the determination of whether the candidate corresponds the first known reference quality to a display.

20 . The processing system of claim 14 , wherein the spoken genome property is selected from the group consisting of pitch, cadence, tonality, rhythm, and timing.