2. Applications

[Ranjeeth Kumar Thunga <rkthunga@humanmarkup.org>]

This is the closest thing we currently have to a formal applications document from our previous discussion, much of the items contributed by Andrew "kiwano" Reitemeyer.  This is probably the best starting block to build our formal applications document. 

 

The deliverable in front of calls is actually much more than a list of possible applications, containing precisely how applications can (and should) interface with HumanML.

 

http://groups.yahoo.com/group/humanmarkup/files/Applications/Examples/applications

 

-----

Ranjeeth Kumar Thunga

rkthunga@humanmarkup.org

(646) 456-9076

 

HUMANMARKUP APPLICATIONS
--------------------------

- parsing and marking up existing literature (a la Terry's LFReD ) as an aid
to comprehension - useful for archaic
or translated documents where use of adjectives and punctuation my mislead
- parsing and marking up existing literature to enable searches to be
performed - searching a body of literature e.g. Byron for emotional states
rather than keywords
- parsing and marking up existing literature in order to strip emotional
content out - research documents for example.
- mark up to enhance small text messages - email, text chat , SMS
- mark up to take advantage of HumanML enhanced browsers
- marking up text intended to be used in conjunction with another media form
eg comic books
- marking up human behaviour e.g stage directions, choreography, story
boards
- marking up text for use in human audio delivery e.g. speaches, HumanML
enhanced stage directions, RPGs
- marking up text for machine audio delivery systems
- automatic marking up of speech to text systems for later reconversion to
audio
- automatic marking up of speech to text systems using biometrics
- automatic marking up of speech to text systems for later reconversion to
audio with faithful reproduction of emotional voice characteristics
- marking up dialog for use in computer-generated theatre, RPGs and talking
heads
- use of visible tags to augment poetry visually i.e. HumanML code poetry
- markup to enable automatic mood music generation to accompany text
passages or scenes, acts ..
- markup to enable intelligent agents to possess and dynamically alter
internal emotional states
- parsing and marking up existing literature (a la Terry's LFReD ) as an aid
to comprehension - useful for archaic
or translated documents where use of adjectives and punctuation my mislead
- parsing and marking up existing literature to enable searches to be
performed - searching a body of literature e.g. Byron for emotional states
rather than keywords
- parsing and marking up existing literature in order to strip emotional
content out - research documents for example.
- mark up to enhance small text messages - email, text chat , SMS
- mark up to take advantage of HumanML enhanced browsers
- marking up text intended to be used in conjunction with another media form
eg comic books
- marking up human behaviour e.g stage directions, choreography, story
boards
- marking up text for use in human audio delivery e.g. speaches, HumanML
enhanced stage directions, RPGs
- marking up text for machine audio delivery systems
- automatic marking up of speech to text systems for later reconversion to
audio
- automatic marking up of speech to text systems using biometrics
- automatic marking up of speech to text systems for later reconversion to
audio with faithful reproduction of emotional voice characteristics
- marking up dialog for use in computer-generated theatre, RPGs and talking
heads
- use of visible tags to augment poetry visually i.e. HumanML code poetry
- markup to enable automatic mood music generation to accompany text
passages or scenes, acts ..
- markup to enable intelligent agents to possess and dynamically alter
internal emotional states.

-Simulation of communications such as creating scenarios that 
can then be rendered into a visualization format
-Annotation of texts or other communications forms to provide 
meta information for the purpose of interpretation
-ransformation of annotated texts both in batch and real time 
modes
(These can be implemented for such tasks as entertainment, what-if 
case exploration, business to business communications, agent-based 
negotiation, and others.)

-poet can strongly enrich presentation of text, words
    -interrogations office can use HumanML to embed human 
characteristics
within convicts' records
    -different colors for inter-office email corresponding 
to 'serious' vs.
'tongue-in-cheek'
    -legal proceedings/transcripts can embed humanml information
    -psychiatric case reports can embed explicit psychological
characteristics within case reports
    -end long drawn out debates by coming to clear terms on what each
person's intentions are