DialogTag 1.1.3

A python library to classify dialogue tag.

DialogTag

Dialogue act classification is the task of classifying an utterance with respect to the function it serves in a dialogue, i.e. the act the speaker is performing. This python library essentially does dialogue act classification on the Switchboard corpus.

The Switchboard-1 corpus is a telephone speech corpus, consisting of about 2,400 two-sided telephone conversation among 543 speakers with about 70 provided conversation topics. The dataset includes the audio files and the transcription files, as well as information about the speakers and the calls. A subset of the Switchboard-1 corpus consisting of 1155 conversations was used. The resulting tags include dialogue acts like statement-non-opinion, acknowledge, statement-opinion, agree/accept, etc.

Annotated example:

Speaker: A, Dialogue Act: Yes-No-Question, Utterance: So do you go to college right now?

The original dataset contained around 42 tags but here we brought them down to 38 by removing a few redundant and ad-hoc tags. The available tags:

TAG	EXAMPLE
Statement-non-opinion	Me, I'm in the legal department.
Acknowledge (Backchannel)	Uh-huh.
Statement-opinion	I think it's great
Agree/Accept	That's exactly it.
Appreciation	I can imagine.
Yes-No-Question	Do you have to have any special training?
Yes answers	Yes.
Conventional-closing	Well, it's been nice talking to you.
Uninterpretable	But, uh, yeah
Wh-Question	Well, how old are you?
No answers	No.
Response Acknowledgement	Oh, okay.
Hedge	I don't know if I'm making any sense or not.
Declarative Yes-No-Question	So you can afford to get a house?
Other	Well give me a break, you know.
Backchannel in question form	Is that right?
Quotation	You can't be pregnant and have cats
Summarize/reformulate	Oh, you mean you switched schools for the kids.
Affirmative non-yes answers	It is.
Action-directive	Why don't you go first
Collaborative Completion	Who aren't contributing.
Repeat-phrase	Oh, fajitas
Open-Question	How about you?
Rhetorical-Questions	Who would steal a newspaper?
Hold before answer/agreement	I'm drawing a blank.
Negative non-no answers	Uh, not a whole lot.
Signal-non-understanding	Excuse me?
Conventional-opening	How are you?
Or-Clause	or is it more of a company?
Dispreferred answers	Well, not so much that.
3rd-party-talk	My goodness, Diane, get down from there.
Offers, Options Commits	I'll have to check that out
Self-talk	What's the word I'm looking for
Downplayer	That's all right.
Maybe/Accept-part	Something like that
Tag-Question	Right?
Declarative Wh-Question	You are what kind of buff?
Apology	I'm sorry.
Thanking	Hey thanks a lot

Installation

We recommend Python 3.7 or higher, Tensorflow 2.0.0 or higher and Transformers v3.0.0 or higher.

Install with pip

Install the DialogTag with pip:

pip install -U DialogTag

Install from sources

Alternatively, you can also clone the latest version from the repository and install it directly from the source code:

pip install -e .

DialogTag in action

This quick example will show you how to use DialogTag in your code.

from dialog_tag import DialogTag

model = DialogTag('distilbert-base-uncased')

sentence = "I'll probably go to shopping today."
output = model.predict_tag(sentence)
print(output)
# output: 'Statement-non-opinion'

sentence = "Why are you asking me this question again and again?"
output = model.predict_tag(sentence)
print(output)
# output: 'Wh-Question'

Available pre-trained models

Update: We now have bert-base-uncased model available!

Currently we have only distilbert-base-uncased available. We're planning to extend it to bert-base-uncased and roberta-base. Stay tuned for further updates!

License

This project is licensed under the MIT License - see the LICENSE.md file for details