Mujahid Khalifah in his PhD research just showed that Japanese emotional speech models created from artificial voice datasets match original data in emotional expression.
You do not need to collect huge high quality datasets for each emotion to produce a good emotional voice. Just use a raw voice model and fine-tune it for specific emotion(s) on small emotional data - even artificial data (!). The emotions will still be perfectly understandable.
Whats more, you can just train a voice model from scratch only on artificial data - it will be worse, but still perfectly usable (!).
This result for Japanese language holds up for basically all age groups, genders, nationalities, even for people who don't know Japanese (!).
This also confirms my own theory.
It shows that when people obtain a new technology, (1) they already know the technology a bit and (2) prefer to smoothly adopt it, focusing on its overall utility rather than minor imperfections.
Thus - the theory of Uncanny Valley is incorrect.
And if you think of it, it's actually quite obvious. Technology is always developing, so by the time there actually are life-like humanoid robots to use at home, we will be well acquainted with them not to feel uncanny with them (although spoiler - its pure sci-fi AI-robot-hype).
So - Mori was wrong in his "The Uncanny Valley" paper. It seems he was imagining things from his own perspective, rather than taking into account the progress of technology and society.
But, on the bright side - your next Siri will be more naturally emotional. ☺️
@UnrollHelper unroll
• • •
Missing some Tweet in this thread? You can try to
force a refresh
"Initial Exploration into Sarcasm and Irony Through Machine Translation"
was just published in Natural Language Processing Journal @ElsevierConnect @sciencedirect
Check 🧵 for highlights and data
With ChiaZhengLin, @mich_ptaszynski, @mar_kar_, @JuusoEronen, and Fumito Masui, we study if it's harder to translate irony compared to straightforward speech. We also specify the optimal conditions for finetuning transformers to translate irony, and compare with zero-shot GPT3.5.
@mar_kar_ @JuusoEronen Citation and open access PDF below.
Chia, Z. L., Ptaszynski, M., Karpinska, M., Eronen, J., & Masui, F. (2024) "Initial exploration into sarcasm and irony through machine translation", Natural Language Processing Journal, 100106
⚡️Username toxicity paper alert⚡️
In our first huge-scale study (over 300 k users!) we found out that users with toxic usernames produced more toxic content and were more likely to have their account suspended. 😱 authors.elsevier.com/c/1fN212f~UWIs… doi.org/10.1016/j.chb.…
Oh, and the system that we made for this research can be tried out completely for free right here! 👇 username.samurailabs.ai
So, I guess, it's time to review my own usernames as well... 😅