Tootfinder

Mumbition
Great Australian Pods Podcast Directory: #GreatAusPods

You know, even if Wes Streeting was right, this is an absolutely shitty way to be talking about someone else. Wes Streeting should be ashamed of this.
#ukpolitics https://f…

Best for Britain (@bestforbritain.org)
@rthonwesstreeting.bsky.social: "Nigel Farage should not be trusted with healthcare in our country." "If that's the sort of health advice Nigel Farage is taking, maybe that's why he is the same age as Brad Bitt but looks 20 years older."

There’s a Dinosaur ‘Mummy Zone.’ Here’s What Scientists Found There. https://www.404media.co/theres-a-dinosaur-mummy-zone-heres-what-scientists-found-there/

🇺🇦 #NowPlaying on KEXP's #StreetSounds
MANN ft. 50 Cent:
🎵 Buzzin Remix
#MANNft50Cent
https://djcaraby.bandcamp.com/track/buzzin-remix
https://open.spotify.com/track/7BmI4hAj6dXIQgA77ZlOzm

pkg query --evaluate '%o = base' '%o\n\n%e\n\n----\n\n'
Why does it not get descriptions of installed base packages?
pkg-query(8)
<https://man.freebsd.org/cgi/man.cgi?query=pkg-query&sektion=8&manpath=freebsd-…

MEMBOT: Memory-Based Robot in Intermittent POMDP
Youzhi Liang, Eyan Noronha
https://arxiv.org/abs/2509.11225 https://arxiv.org/pdf/2509.11225

MEMBOT: Memory-Based Robot in Intermittent POMDP
Robotic systems deployed in real-world environments often operate under con- ditions of partial and often intermittent observability, where sensor inputs may be noisy, occluded, or entirely unavailable due to failures or environmental con- straints. Traditional reinforcement learning (RL) approaches that assume full state observability are ill-equipped for such challenges. In this work, we introduce MEMBOT, a modular memory-based architecture designed to address intermittent partial observabili…

@… thinks a written constitution would somehow impede a #Fascist takeover of the United Kingdom. I admire his optimism: look how well it's working in the United States.
I mean, a written constitution …

Evaluating the Representation of Vowels in Wav2Vec Feature Extractor: A Layer-Wise Analysis Using MFCCs
Domenico De Cristofaro, Vincenzo Norman Vitale, Alessandro Vietti
https://arxiv.org/abs/2508.17914

Evaluating the Representation of Vowels in Wav2Vec Feature Extractor: A Layer-Wise Analysis Using MFCCs
Automatic Speech Recognition has advanced with self-supervised learning, enabling feature extraction directly from raw audio. In Wav2Vec, a CNN first transforms audio into feature vectors before the transformer processes them. This study examines CNN-extracted information for monophthong vowels using the TIMIT corpus. We compare MFCCs, MFCCs with formants, and CNN activations by training SVM classifiers for front-back vowel identification, assessing their classification accuracy to evaluate pho…

@… try the --label option of zdb(8), to tell whether the four labels are present and correct.
<https://man.freebsd.org/cgi/man.cgi?qu