Tootfinder

Replaced article(s) found for eess.AS. https://arxiv.org/list/eess.AS/new
[1/1]:
- Unifying Diarization, Separation, and ASR with Multi-Speaker Encoder
Muhammad Shakeel, Yui Sudo, Yifan Peng, Chyi-Jiunn Lin, Shinji Watanabe
https://arxiv.org/abs/2508.20474 https://mastoxiv.page/@arXiv_eessAS_bot/115110974009150613
- CALM: Joint Contextual Acoustic-Linguistic Modeling for Personalization of Multi-Speaker ASR
Muhammad Shakeel, Yosuke Fukumoto, Chikara Maeda, Chyi-Jiunn Lin, Shinji Watanabe
https://arxiv.org/abs/2601.22792 https://mastoxiv.page/@arXiv_eessAS_bot/116000207024295325
- How Much Does Machine Identity Matter in Anomalous Sound Detection at Test Time?
Kevin Wilkinghoff, Keisuke Imoto, Zheng-Hua Tan
https://arxiv.org/abs/2602.16253 https://mastoxiv.page/@arXiv_eessAS_bot/116096185732811365
- LMU-Based Sequential Learning and Posterior Ensemble Fusion for Cross-Domain Infant Cry Classific...
Niloofar Jazaeri, Hilmi R. Dajani, Marco Janeczek, Martin Bouchard
https://arxiv.org/abs/2603.02245 https://mastoxiv.page/@arXiv_eessAS_bot/116169771215037748
- Adapting a Text-to-Audio Model for Room Impulse Response Generation
Kirak Kim, Sungyoung Kim
https://arxiv.org/abs/2603.09708 https://mastoxiv.page/@arXiv_eessAS_bot/116209762413602825
- Repurposing Image Diffusion Models for Training-Free Music Style Transfer on Mel-spectrograms
Heehwan Wang, Joonwoo Kwon, Sooyoung Kim, Jungwoo Seo, Shinjae Yoo, Yuewei Lin, Jiook Cha
https://arxiv.org/abs/2411.15913 https://mastoxiv.page/@arXiv_csSD_bot/113548024475383386
- DeePen: Penetration Testing for Audio Deepfake Detection
M\"uller, Kawa, Stan, Doan, Jung, Choong, Sperl, B\"ottinger
https://arxiv.org/abs/2502.20427 https://mastoxiv.page/@arXiv_csCR_bot/114097333876265997
- Re-evaluating Minimum Bayes Risk Decoding for Automatic Speech Recognition
Yuu Jinnai
https://arxiv.org/abs/2510.19471 https://mastoxiv.page/@arXiv_csCL_bot/115422969877240889
- Aliasing-Free Neural Audio Synthesis
Yicheng Gu, Junan Zhang, Chaoren Wang, Jerry Li, Zhizheng Wu, Lauri Juvela
https://arxiv.org/abs/2512.20211 https://mastoxiv.page/@arXiv_csSD_bot/115773521971327576
- TiCo: Time-Controllable Spoken Dialogue Model
Kai-Wei Chang, Wei-Chih Chen, En-Pei Hu, Hung-yi Lee, James Glass
https://arxiv.org/abs/2603.22267 https://mastoxiv.page/@arXiv_csCL_bot/116283643505371784
toXiv_bot_toot

Além dessa daqui (https://social.linux.pizza/@matematico314/116738933329024322), achei aqui agora uma montagem tosca que fiz uma vez para a data.

Vz-GAL Dusty Star-Forming Galaxies: Revisiting the CO-H2 Conversion Factor Tension
Prachi Prajapati, Axel Weiss, Dominik Riechers, Tom J. L. C. Bakx, Leindert A. Boogaard, Diana Ismail, Pierre Cox, Andrew J. Baker, Roberto Neri, Matthew Lehnert, Chentao Yang, Emilio Romano-Diaz, Hiddo S. B. Algera, Stefano Berta, Edoardo Borsato, Kirsty M. Butler, Asantha Cooray, Bethany Jones, Amelie Saintonge, Paul van der Werf
https://arxiv.org/abs/2607.18440 https://arxiv.org/pdf/2607.18440 https://arxiv.org/html/2607.18440
arXiv:2607.18440v1 Announce Type: new
Abstract: The CO luminosity-to-H$_2$ mass conversion factor ($\alpha_{CO}$) remains a debated uncertainty in determining molecular gas masses of high-redshift dusty star-forming galaxies (DSFGs). Dynamical mass constraints have often favored $\alpha_{CO}=0.8$~$M_{\odot}~{(K~km~{s}^{-1}~{pc}^{2})}^{-1}$, whereas dust- and radiative-transfer-based methods imply higher values. We revisit this ``tension" using the largest homogeneous sample of 21 unlensed $z\sim1-4$ DSFGs, with securely measured \coonezero luminosities from the VLA \vzgal survey and resolved ($\sim{0.1}^{\prime\prime}$) ALMA 1~mm dust continuum imaging. For 12 galaxies with robust modeling constraints, we derive molecular gas masses using dust spectral energy distribution modeling and the TUNER LVG framework, adopting a solar-metallicity gas-to-dust mass ratio of 100. Although not fully independent due to shared assumptions on dust properties, these approaches yield mutually consistent gas masses corresponding to $\alpha_{CO}\sim1.5-11.5$, with a median near the Galactic $\alpha_{CO}=4.3$. Isotropic virial dynamical masses agree with these gas masses when realistic molecular gas sizes are adopted, while our proposed ``mixed" (rotating, pressure-supported, thick-disk) estimator systematically underestimates dynamical masses, producing low $\alpha_{CO}$ limits. Using GN20 ($z=4.055$) as a case study, we show that resolved gas geometry and kinematics reconcile the discrepancy with LVG-derived $\alpha_{CO}$. Our results suggest that current data do not require $\alpha_{CO}=0.8$, and intermediate to near-Galactic values remain dynamically viable given uncertainties in gas geometry, dust properties, and gas-to-dust ratios. Further progress in calibrating $\alpha_{CO}$ in the early universe will require resolved molecular gas observations, physically motivated ISM modeling, and stringent constraints on dust properties.
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Major U.S. cloud providers are urging Washington to push back against South Korea’s planned overhaul of the security approval system for cloud providers serving its government agencies.
https://www.koreajoongangdaily.com/busines

U.S. cloud giants challenge South Korea's public cloud security overhaul
Amazon Web Services, Microsoft Azure and Google Cloud are pushing back against South Korea’s public cloud security overhaul, warning the new rules could block market access and violate fair trade principles.

#Lenovo website asking me about my age, am I buying porn or alcohol, no! I am filling in a review about a charger I bought 🤔
Well I guess they'll never know what I think about that charger then..
#AgeVerification

Let me get this straight. Xbox leadership believes the way to winning back people with great exclusives is by firing the people who make them — the people whose expertise they already paid billions to acquire? Sure. Seems really smart! https://www.eurogamer.net/xbox-layoffs-business-reset

These are prolly my fav Thierry Mugler sci fi fits just cuz the other ones give me so much more difficulty in imagining their movement

Cowboys acquire LB Dee Winters in a trade that nets the 49ers a 5th-round pick in the NFL draft https://www.foxsports.com/articles/nfl/cowboys-acquire-lb-dee-winters-in-a-trade-that-nets-the-49ers-a-5thround-pick…

«Face Š la rapidité des progrès, Yoshua Bengio invite Š ne pas céder Š la passivité. ‹Il faut se dire qu'on a la possibilité de choisir›, insiste-t-il, en comparant la situation au mouvement climatique. Si suffisamment de citoyens et citoyennes prennent le sujet au sérieux, les gouvernements finiront par agir, Š condition que la mobilisation soit mondiale, avance-t-il.»
Mwahahaha! Oui, ça marche bien pour le climat.

L'expert Yoshua Bengio alerte sur les dérives de l'IA à Genève
Yoshua Bengio, un des pionniers de l'intelligence artificielle, était l'invité de Tout un Monde mercredi depuis le sommet "AI for Good" à Genève. Il y explique en quoi l'IA développe des comportements risqués et comment tenter d'y remédier.

Estimating stellar metallicities from Gaia DR3 XP data using LAMOST DR10
Divyansh Srivastava, Andrzej Niedzielski, Rodolfo Smiljanic
https://arxiv.org/abs/2607.18707 https://arxiv.org/pdf/2607.18707 https://arxiv.org/html/2607.18707
arXiv:2607.18707v1 Announce Type: new
Abstract: Gaia DR3 provides astrophysical parameters for hundreds of millions of stars, but the metallicities [M/H] from its GSP-Phot module suffer from systematic biases. We estimate stellar metallicities from Gaia DR3 data using the homogeneous spectroscopic iron abundances [Fe/H] of LAMOST DR10 as training labels. We cross-matched LAMOST DR10 with Gaia DR3 and trained a gradient-boosted decision-tree regressor (XGBoost) on 1.20 million AFGK stars using only Gaia-derived inputs and proxies. We validated the estimates on held-out LAMOST stars, GALAH DR4, APOGEE DR17, and 46 open clusters, and applied the model to measure the radial metallicity gradient of the Milky Way disk. On the held-out test set, the model achieves a mean absolute error of 0.052 dex and $R^2=0.94$ with negligible bias, compared with 0.242 dex for GSP-Phot on the same stars. The estimates transfer well to external surveys, with mean absolute errors of 0.066 dex for GALAH and 0.068 dex for APOGEE. For open clusters, the median difference between our estimated [Fe/H] and spectroscopic values is 0.041 dex, smaller than both GSP-Phot (0.248 dex) and a previous APOGEE-trained XGBoost model (0.067 dex). Applied to the Galactic disk, our model recovers a broken thin-disk radial gradient, with inner and outer slopes of $ 0.119$ and $-0.058\,\mathrm{dex\,kpc^{-1}}$, respectively, and a break near 5.9 kpc, as well as an open-cluster gradient of $-0.066\,\mathrm{dex\,kpc^{-1}}$; both agree with previous high-resolution spectroscopic studies. Our [Fe/H] estimates are accurate to 0.05-0.07 dex for AFGK stars with $[\mathrm{Fe/H}]\gtrsim-2.5$; below this limit, the predictions should be treated as lower bounds. The catalogue and trained model are publicly available on Zenodo and are suitable for chemical studies of the Milky Way.
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