Dynamic memory allocation using natural language processing tags

1. A natural language processing system, comprising:

a plurality of storage devices;

a network interface in signal communication with the plurality of storage devices and one or more data sources, wherein the network interface is configured to receive audio files from the one or more data sources;

a memory operable to store artificial intelligence (AI)-defined tags linked with a first set of concepts; and

a processor operably coupled to the network interface and the memory, configured to:

receive a set of audio files;

identify concepts within the set of audio files;

determine a usage frequency for each of the identified concepts, wherein the usage frequency indicates how often each of the identified concepts occurs within the set of audio files;

compare the usage frequency for each identified concept to a usage frequency threshold;

generate an AI-defined tag for each identified concept with a usage frequency that is greater than the usage frequency threshold, wherein each AI-defined tag is linked with the corresponding identified concept;

receive an audio file;

modify metadata for the audio file to include AI-defined tags linked with concepts from the first set of concepts;

identify non-verbal audio information present within the audio file;

determine a context tag based on the identified non-verbal audio information present within the audio file, wherein the determined context tag identifies a sound characteristic that is present within the audio file;

modify the metadata for the audio file to include the determined context tag;

analyze the metadata for audio file to identify tags associated with the audio file;

determine a priority level for the audio file based on the tags associated with the audio file;

determine a data access speed for the audio file based on the determined priority level associated with the audio file;

select a storage location from among the plurality of storage devices based on the determined data access speed; and

send the audio file to the identified storage location.

2. The system of claim 1 , wherein:

a storage device type based at least in part on the determined priority level.

3. The system of claim 2 , wherein the processor is further configured to modify the metadata for the audio file to include the determined priority level for the audio file.

4. The system of claim 1 , wherein the processor is further configured to:

determine how often the audio file has been accessed within a predetermined time period;

determine an activity level for the audio file based on how often the audio file has been access within the predetermined time period, wherein the activity level is a value that decays over time; and

modify the metadata for the audio file to include the activity level for the audio file.

5. The system of claim 1 , wherein:

the memory is operable to store user-defined tags linked with a second set of concepts; and

the tagging engine is further configured to:

modify the metadata for the audio file to include user-defined tags linked with concepts from the second set of concepts.

6. A natural language processing method, comprising:

receiving a set of audio files;

identifying concepts within the set of audio files;

determining a usage frequency for each of the identified concepts, wherein the usage frequency indicates how often each of the identified concepts occurs within the set of audio files;

comparing the usage frequency for each identified concept to a usage frequency threshold; and

generating an AI-defined tag for each identified concept with a usage frequency that is greater than the usage frequency threshold, wherein each AI-defined tag is linked with a concept from a first set of concepts; and

receiving an audio file;

modifying metadata for the audio file to include AI-defined tags linked with concepts from the first set of concepts;

identifying non-verbal audio information present within the audio file;

determining a context tag based on the identified non-verbal audio information present within the audio file, wherein the determined context tag identifies a sound characteristic that is present within the audio file;

modifying the metadata for the audio file to include the determined context tag;

analyzing the metadata for the audio file to identify tags associated with the audio file;

determining a priority level for the audio file based on the tags associated with the audio file;

determining a data access speed for the audio file based on the determined priority level associated with the audio file;

selecting a storage location from among the plurality of storage devices based on the determined data access speed; and

sending the audio file to the identified storage location.

7. The method of claim 6 , wherein:

selecting a storage device type based at least in part on the determined priority level.

8. The method of claim 7 , further comprising modifying the metadata for the audio file to include the determined priority level for the audio file.

9. The method of claim 6 , further comprising:

determining how often the audio file has been accessed within a predetermined time period;

determining an activity level for the audio file based on how often the audio file has been access within the predetermined time period, wherein the activity level is a value that decays over time; and

modifying the metadata for the audio file to include the activity level for the audio file.

10. The method of claim 6 , further comprising:

modifying the metadata for the audio file to include user-defined tags linked with concepts from a second set of concepts.

11. The method of claim 6 , further comprising:

modifying the metadata for the audio file to include context tags linked with context identifiers, wherein a context identifier identifies non-verbal audio information.

12. A natural language processing device, comprising:

a memory operable to store artificial intelligence (AI)-defined tags linked with a first set of concepts;

a processor operably coupled to the memory, configured to:

receive a set of audio files;

identify concepts within the set of audio files;

determine a usage frequency for each of the identified concepts, wherein the usage frequency indicates how often each of the identified concepts occurs within the set of audio files;

compare the usage frequency for each identified concept to a usage frequency threshold;

generate an AI-defined tag for each identified concept with a usage frequency that is greater than the usage frequency threshold, wherein each AI-defined tag is linked with the corresponding identified concept;

receive an audio file;

modify metadata for the audio file to include AI-defined tags linked with concepts from the first set of concepts;

identify non-verbal audio information present within the audio file;

determine a context tag based on the identified non-verbal audio information present within the audio file, wherein the determined context tag identifies a sound characteristic that is present within the audio file;

modify the metadata for the audio file to include the determined context tag;

analyze the metadata for the audio file to identify tags associated with the audio file;

determine a priority level for the audio file based on the tags associated with the audio file;

determine a data access speed for the audio file based on the determined priority level associated with the audio file;

select a storage location from among a plurality of storage devices based on the determined data access speed; and

send the audio file to the identified storage location.

13. The device of claim 12 , wherein:

selecting a storage device type based at least in part on the determined priority level.

14. The device of claim 13 , wherein the processor is further configured to modify the metadata for the audio file to include the determined priority level for the audio file.

15. The device of claim 12 , wherein the processor is further configured to:

determine how often the audio file has been accessed within a predetermined time period;

determine an activity level for the audio file based on how often the audio file has been access within the predetermined time period, wherein the activity level is a value that decays over time; and

modify the metadata for the audio file to include the activity level for the audio file.