Could your computer please be more polite? Thank you
Method automatically makes requests more polite

Date:
June 30, 2020
Source:
Carnegie Mellon University
Summary:
In a tense time when a pandemic rages, politicians wrangle for
votes and protesters demand racial justice, a little politeness and
courtesy go a long way. Now researchers have developed an automated
method for making communications more polite. Specifically, the
method takes nonpolite directives or requests -- those that use
either impolite or neutral language -- and restructures them or
adds words to make them more well- mannered.



FULL STORY ==========================================================================
In a tense time when a pandemic rages, politicians wrangle for votes and protesters demand racial justice, a little politeness and courtesy go a
long way. Now researchers at Carnegie Mellon University have developed
an automated method for making communications more polite.


========================================================================== Specifically, the method takes nonpolite directives or requests --
those that use either impolite or neutral language -- and restructures
them or adds words to make them more well-mannered. "Send me the
data," for instance, might become "Could you please send me the data?"
The researchers will present their study on politeness transfer at the Association for Computational Linguistics annual meeting, which will be
held virtually beginning July 5.

The idea of transferring a style or sentiment from one communication
to another -- turning negative statements positive, for instance -- is something language technologists have been doing for some time. Shrimai Prabhumoye, a Ph.D.

student in CMU's Language Technologies Institute (LTI), said performing politeness transfer has long been a goal.

"It is extremely relevant for some applications, such as if you want
to make your emails or chatbot sound more polite or if you're writing
a blog," she said. "But we could never find the right data to perform
this task." She and LTI master's students Aman Madaan, Amrith Setlur and Tanmay Parekh solved that problem by generating a dataset of 1.39 million sentences labeled for politeness, which they used for their experiments.



==========================================================================
The source of these sentences might seem surprising. They were derived
from emails exchanged by employees of Enron, a Texas-based energy company
that, until its demise in 2001, was better known for corporate fraud
and corruption than for social niceties. But half a million corporate
emails became public as a result of lawsuits surrounding Enron's fraud
scandal and subsequently have been used as a dataset for a variety of
research projects.

But even with a dataset, the researchers were challenged simply to
define politeness.

"It's not just about using words such as 'please' and 'thank you,'"
Prabhumoye said. Sometimes, it means making language a bit less direct,
so that instead of saying "you should do X," the sentence becomes
something like "let us do X." And politeness varies from one culture
to the next. It's common for native North Americans to use "please" in
requests to close friends, but in Arab culture it would be considered
awkward, if not rude. For their study, the CMU researchers restricted
their work to speakers of North American English in a formal setting.

The politeness dataset was analyzed to determine the frequency and
distribution of words in the polite and nonpolite sentences. Then the
team developed a "tag and generate" pipeline to perform politeness
transfers. First, impolite or nonpolite words or phrases are tagged and
then a text generator replaces each tagged item. The system takes care
not to change the meaning of the sentence.

"It's not just about cleaning up swear words," Prabhumoye said of the
process.

Initially, the system had a tendency to simply add words to sentences,
such as "please" or "sorry." If "Please help me" was considered polite,
the system considered "Please please please help me" even more polite.

But over time the scoring system became more realistic and the changes
became subtler. First person singular pronouns, such as I, me and
mine, were replaced by first person plural pronouns, such as we, us and
our. And rather than position "please" at the beginning of the sentence,
the system learned to insert it within the sentence: "Could you please
send me the file?" Prabhumoye said the researchers have released their
labeled dataset for use by other researchers, hoping to encourage them
to further study politeness.


========================================================================== Story Source: Materials provided by Carnegie_Mellon_University. Note:
Content may be edited for style and length.


==========================================================================


Link to news story: https://www.sciencedaily.com/releases/2020/06/200630072046.htm

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