Sho Akamine
@shoakamine.bsky.social
440 followers 440 following 33 posts
Ph.D candidate @mpi-nl.bsky.social studying multimodal alignment in social interaction. Interested in #mulitmodality, #interaction, #kinematics, #stats, #causal_inference. Okinawa🇯🇵 → Nijmegen🇳🇱
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shoakamine.bsky.social
If anyone is interested in using WhisperX to transcribe speech, this tutorial is for you!! In this tutorial, I provide an easy-to-use pipeline where you will get a time-aligned transcript as a Praat TextGrid file, a TSV file, and a subtitle file🙌
github.com/ShoAkamine/w...
GitHub - ShoAkamine/whisperx_tutorial
Contribute to ShoAkamine/whisperx_tutorial development by creating an account on GitHub.
github.com
shoakamine.bsky.social
Some of the popular chain restaurant recommendations: Sushiro, Kurasushi, Tsurutontan (udon noodles), Ohtoya (Japanese), Yayoi Ken (Japanese), Gyoza no Ohsho (Chinese), Coco curry. Hope you enjoy Japan!!
Reposted by Sho Akamine
shoakamine.bsky.social
You are right. That's why I'm trying to develop a good understanding so that I can make my judgments! And your summer school really helped me understand stats better :)
shoakamine.bsky.social
I think it’d be a great addition! Especially because I saw recommendations against using BF due to its sensitivity to priors, so instead using CI or HDI for NHST. That’s why I got confused when I read the statement in your book. I’ll read more papers/books and try to get a full understanding on this
shoakamine.bsky.social
Thank you so much for all the recommended readings!!!
shoakamine.bsky.social
Thank you so much for the elaborate answer! It was very informative!!
Reposted by Sho Akamine
shoakamine.bsky.social
I'm currently reading the paper. Thanks a lot for your suggestion!
shoakamine.bsky.social
Thank you for the response! I think one should reject the null in case 1 and fail to reject in case 2, although "0.0000001" is a tiny diff. I see the point here, but doesn't this issue apply to any discrete decisions based on continuous measures? Or would this be less of a problem for Bayes factor?
shoakamine.bsky.social
Please help me learn! I see people using CI for hypothesis testing (whether 95% CIs for slope cover 0), but Nicenboim, Schad &Vasishth say in their fantastic book that "just by looking at the [CIs], we cannot make inferences about whether a null hypothesis can be rejected". Why is this the case?
Reposted by Sho Akamine
carorowland.bsky.social
Children are incredible language learning machines. But how do they do it? Our latest paper, just published in TICS, synthesizes decades of evidence to propose four components that must be built into any theory of how children learn language. 1/
www.cell.com/trends/cogni... @mpi-nl.bsky.social
Constructing language: a framework for explaining acquisition
Explaining how children build a language system is a central goal of research in language acquisition, with broad implications for language evolution, adult language processing, and artificial intelli...
www.cell.com
shoakamine.bsky.social
I see, good to know! I’ll try segmented regression and splines and see which one makes more sense for my data ;)
shoakamine.bsky.social
Yes, that’s exactly what I had in mind! Didn’t know that they are called segmented regression. Thanks for your reply😊
Reposted by Sho Akamine
dingdingpeng.the100.ci
At this point, I might as well --
Here's an infographic showing different ways to include age as a predictor. The top shows two extremes, just as a plain old numerical predictor (imposes linear trajectory) vs. categorical predictor (imposes nothing whatsoever). And then three solutions in between!
Infographic illustrating different ways to model age.
First panel shows two "extreme" cases; including age as a linear numerical predictor (df = 1) or including age as a categorical predictor (df = number of years of age minus 1).
Second panel shows an intermediate solution in which age is categorized into broader bins (df = number of categories minus 1, here 5 - 1 = 4).
Third panel shows an intermediate solution in which age is included with a polynomial (df = degrees of freedom of the polynomial, here 4).
Fourth panel shows an intermediate solution in which age is modeled with the help of splines (df = degrees of freedom of the splines, here 4).
shoakamine.bsky.social
This is amazing!!! Would it also make sense to model age as a continuous predictor within different age bins? So instead of getting one point estimate (flat line) for the in-between solution, we would fit a regression line in each binned age so that the flat lines will follow the date better?
shoakamine.bsky.social
Thanks a lot, Martha!!
Reposted by Sho Akamine
dingemansemark.bsky.social
Sho presents his work validating dynamic time warping to a rapt #ISGS2025 audience. Lots of engagement afterwards #ProudSupervisor
Sho Akamine presenting on dynamic time warping on a large stage at ISGS 2025 in Nijmegen Sho answering questions
shoakamine.bsky.social
If you can't attend the talk but are interested in the work, we have a preprint available!!
osf.io/preprints/ps...
OSF
osf.io
shoakamine.bsky.social
Are you at #ISGS2025 today? Come see my talk in the kinematics session! I'll present my PhD work validating dynamic time warping (DTW) as a measure of gesture form similarity with manual ratings. We show that DTW can be an efficient, useful proxy for gesture form similarity!
Reposted by Sho Akamine
martinamellana.bsky.social
Excited to present at ISGS25 this Thursday morning in Nijmegen!
Together with @shariceclough.bsky.social , we’ll be sharing our work on the role of gesture in narrative recall across Alzheimer’s, MCI, and healthy aging.
Looking forward to great discussions! 💪🏻🧠🗣️
#ISGS25