'NRF said

He Said, She Said: Gender in the ACL Anthology

Studies of gender balance in academic computer science are typically based on statistics on enrollment and graduation. Going beyond these coarse measures of gender participation, we conduct a fine-grained study of gender in the field of Natural Language Processing. We use topic models (Latent Dirichlet Allocation) to explore the research topics of men and women in the ACL Anthology Network. We ...

I said, you said: the production effect gets personal.

Saying a word out loud makes it more memorable than simply reading it silently. This robust finding has been labeled the production effect and has been attributed to the enhanced distinctiveness of produced relative to unproduced items (MacLeod et al. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 671-685, 2010). Produced items have the additional information that they...

He said, she said: demystifying the dreaded disciplinary hearing.

"He Said She Said" ― a Male/Female Corpus of Polish

Gender differences in language use have long been of interest in linguistics. The task of automatic gender attribution has been considered in computational linguistics as well. Most research of this type is done using (usually English) texts with authorship metadata. In this paper, we propose a new method of male/female corpus creation based on gender-specific first-person expressions. The meth...

You said that?

We present a method for generating a video of a talking face. The method takes as inputs: (i) still images of the target face, and (ii) an audio speech segment; and outputs a video of the target face lip synched with the audio. The method runs in real time and is applicable to faces and audio not seen at training time. To achieve this we propose an encoder-decoder CNN model that uses a joint em...