Tootfinder

This https://arxiv.org/abs/2505.19099 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning
We present SeePhys, a large-scale multimodal benchmark for LLM reasoning grounded in physics questions ranging from middle school to PhD qualifying exams. The benchmark covers 7 fundamental domains spanning the physics discipline, incorporating 21 categories of highly heterogeneous diagrams. In contrast to prior works where visual elements mainly serve auxiliary purposes, our benchmark features a substantial proportion of vision-essential problems (75\%) that mandate visual information extracti…

Competing Interactions and the Effects of Uniaxial Out-of-plane Perturbations in the Honeycomb Antiferromagnet Na$_2$Co$_2$TeO$_6$
J. Arneth, R. Kalaivanan, R. Sankar, K. -Y. Choi, R. Klingeler
https://arxiv.org/abs/2506.06189

Competing Interactions and the Effects of Uniaxial Out-of-plane Perturbations in the Honeycomb Antiferromagnet Na$_2$Co$_2$TeO$_6$
Despite exhibiting magnetic long-range order below $T_\mathrm{N} = 26.7\,\mathrm{K}$, the honeycomb cobaltate Na$_2$Co$_2$TeO$_6$ is predicted to enter a Kitaev spin liquid state when subjected to small external perturbations. While most of the reported literature investigates the effects of magnetic fields applied parallel to the honeycomb layers, we present high-resolution capacitance dilatometry studies for fields perpendicular to the Co-planes up to $15\,\mathrm{T}$. Grüneisen analysis rev…

Audio-Aware Large Language Models as Judges for Speaking Styles
Cheng-Han Chiang, Xiaofei Wang, Chung-Ching Lin, Kevin Lin, Linjie Li, Radu Kopetz, Yao Qian, Zhendong Wang, Zhengyuan Yang, Hung-yi Lee, Lijuan Wang
https://arxiv.org/abs/2506.05984

Audio-Aware Large Language Models as Judges for Speaking Styles
Audio-aware large language models (ALLMs) can understand the textual and non-textual information in the audio input. In this paper, we explore using ALLMs as an automatic judge to assess the speaking styles of speeches. We use ALLM judges to evaluate the speeches generated by SLMs on two tasks: voice style instruction following and role-playing. The speaking style we consider includes emotion, volume, speaking pace, word emphasis, pitch control, and non-verbal elements. We use four spoken langu…

This https://arxiv.org/abs/2312.00885 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Divisible minimal codes
Minimal codes are linear codes where all non-zero codewords are minimal, i.e., whose support is not properly contained in the support of another codeword. The minimum possible length of such a $k$-dimensional linear code over $\mathbb{F}_q$ is denoted by $m(k,q)$. Here we determine $m(7,2)$, $m(8,2)$, and $m(9,2)$, as well as full classifications of all codes attaining $m(k,2)$ for $k\le 7$ and those attaining $m(9,2)$. We give improved upper bounds for $m(k,2)$ for all $10\le k\le 17$. It turn…

Model selection using the HII galaxy Hubble diagram
Jun-Jie Wei, Fulvio Melia
https://arxiv.org/abs/2506.04819 https://arxiv.org/pdf/…

Model selection using the HII galaxy Hubble diagram
The proposal to use HII galaxies (HIIGx) and giant extragalactic HII regions (GEHR) as standard candles to construct the Hubble diagram at redshifts beyond the current reach of Type Ia supernovae has gained considerable support recently with the addition of five new HIIGx discovered by JWST. The updated sample of 231 sources now extends the redshift range of these objects to $z\sim 7.5$, mapping the Universe's expansion over $95\%$ of its current age. In this {\it Letter} we use these sources f…

Cryogenic Optical Lattice Clock with $1.7\times 10^{-20}$ Blackbody Radiation Stark Uncertainty
Youssef S. Hassan, Kyle Beloy, Jacob L. Siegel, Takumi Kobayashi, Eric Swiler, Tanner Grogan, Roger C. Brown, Tristan Rojo, Tobias Bothwell, Benjamin D. Hunt, Adam Halaoui, Andrew D. Ludlow
https://arxiv.org/abs/2506.05304

Birational geometry of weighted complete intersections of type $(12, 14)$ in $\mathbb{P} (1, 2, 3, 4, 7, 11)$
Takuzo Okada
https://arxiv.org/abs/2506.00323

Birational geometry of weighted complete intersections of type $(12, 14)$ in $\mathbb{P} (1, 2, 3, 4, 7, 11)$
We show that any quasismooth Fano threefold weighted complete intersections of type $(12, 14)$ in $\mathbb{P} (1, 2, 3, 4, 7, 11)$ is birationally solid.

Thermodynamics and Shadows of Kerr black holes endowed with a global monopole charge
Balendra Pratap Singh, Md Sabir Ali
https://arxiv.org/abs/2506.02653 h…

Thermodynamics and Shadows of Kerr black holes endowed with a global monopole charge
In this article, we present the thermodynamic and shadow properties of rotating black holes with global monopole charge. The angular diameter of Sgr A$^{*}$ black hole is 48.7 $\pm$ 7 $μas$, which is 8 $kps$ far away having a mass of $M = 4.0_{-0.6}^{+1.1} \times 10^6 M\odot$ as observed by Event Horizon Telescope and for the M87 black hole, the observed angular diameter is $θ_d = 42 \pm 3 μ$as, which is almost $16$ $Mpc$ far away with a mass of $M = (6.5 \pm 0.7) \times 10^9 M_\odot$. The g…

TADA: Training-free Attribution and Out-of-Domain Detection of Audio Deepfakes
Adriana Stan, David Combei, Dan Oneata, Hora Cucu
https://arxiv.org/abs/2506.05802

TADA: Training-free Attribution and Out-of-Domain Detection of Audio Deepfakes
Deepfake detection has gained significant attention across audio, text, and image modalities, with high accuracy in distinguishing real from fake. However, identifying the exact source--such as the system or model behind a deepfake--remains a less studied problem. In this paper, we take a significant step forward in audio deepfake model attribution or source tracing by proposing a training-free, green AI approach based entirely on k-Nearest Neighbors (kNN). Leveraging a pre-trained self-supervi…

[2025-06-06 Fri (UTC), 1 new article found for nlin.PS Pattern Formation and Solitons]
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This https://arxiv.org/abs/2506.04031 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Brightest Group Galaxies IV: Probing Size--Mass Relation and Morphological Quenching in COSMOS-Web from $z = 3.7$
We present a comprehensive study of the structural evolution of Brightest Group Galaxies (BGGs) from redshift $z \simeq 0.08$ to $z = 3.7$ using the \textit{James Webb Space Telescope}'s 255h COSMOS-Web program. This survey provides deep NIRCam imaging in four filters (F115W, F150W, F277W, F444W) across $\sim 0.54~\mathrm{deg}^2$ and MIRI coverage in $\sim 0.2~\mathrm{deg}^2$ of the COSMOS field. High-resolution NIRCam imaging enables robust size and morphological measurements, while multiwavel…

Magnetic excitations in the 1/3 plateau state in InCu$_3$(OH)$_6$Cl$_3$
Moyu Kato, Hiroyuki K. Yoshida, R. Kumar, Yoshihiko Ihara
https://arxiv.org/abs/2506.05645

Magnetic excitations in the 1/3 plateau state in InCu$_3$(OH)$_6$Cl$_3$
Magnetic dynamics in InCu$_3$(OH)$_6$Cl$_3$ was investigated from the NMR relaxation rate measurement. In InCu$_3$(OH)$_6$Cl$_3$, the magnetization isotherm shows a plateau at the 1/3 of full-saturation magnetization, characterizing the 1/3 plateau state. As the 1/3 plateau state appears above 7 T upto 14 T, the microscopic magnetic properties were investigated with the NMR measurement in steady fields. The temperature and field dependence of $1/T_1$ measurement reveals a gap in the magnetic ex…

Diarization-Aware Multi-Speaker Automatic Speech Recognition via Large Language Models
Yuke Lin, Ming Cheng, Ze Li, Beilong Tang, Ming Li
https://arxiv.org/abs/2506.05796

Diarization-Aware Multi-Speaker Automatic Speech Recognition via Large Language Models
Multi-speaker automatic speech recognition (MS-ASR) faces significant challenges in transcribing overlapped speech, a task critical for applications like meeting transcription and conversational analysis. While serialized output training (SOT)-style methods serve as common solutions, they often discard absolute timing information, limiting their utility in time-sensitive scenarios. Leveraging recent advances in large language models (LLMs) for conversational audio processing, we propose a novel…

Transient dynamics of associative memory models
David G. Clark
https://arxiv.org/abs/2506.05303 https://arxiv.org/pdf/2506.05303

Transient dynamics of associative memory models
Associative memory models such as the Hopfield network and its dense generalizations with higher-order interactions exhibit a "blackout catastrophe"--a discontinuous transition where stable memory states abruptly vanish when the number of stored patterns exceeds a critical capacity. This transition is often interpreted as rendering networks unusable beyond capacity limits. We argue that this interpretation is largely an artifact of the equilibrium perspective. We derive dynamical mean-field equ…

Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition
Mu Yang, Szu-Jui Chen, Jiamin Xie, John Hansen
https://arxiv.org/abs/2506.05706

Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition
One challenge of integrating speech input with large language models (LLMs) stems from the discrepancy between the continuous nature of audio data and the discrete token-based paradigm of LLMs. To mitigate this gap, we propose a method for integrating vector quantization (VQ) into LLM-based automatic speech recognition (ASR). Using the LLM embedding table as the VQ codebook, the VQ module aligns the continuous representations from the audio encoder with the discrete LLM inputs, enabling the LLM…

[2025-06-06 Fri (UTC), 7 new articles found for cs.GR Graphics]
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Low-Resource Domain Adaptation for Speech LLMs via Text-Only Fine-Tuning
Yangui Fang, Jing Peng, Xu Li, Yu Xi, Chengwei Zhang, Guohui Zhong, Kai Yu
https://arxiv.org/abs/2506.05671

Low-Resource Domain Adaptation for Speech LLMs via Text-Only Fine-Tuning
Recent advances in automatic speech recognition (ASR) have combined speech encoders with large language models (LLMs) through projection, forming Speech LLMs with strong performance. However, adapting them to new domains remains challenging, especially in low-resource settings where paired speech-text data is scarce. We propose a text-only fine-tuning strategy for Speech LLMs using unpaired target-domain text without requiring additional audio. To preserve speech-text alignment, we introduce a …

This https://arxiv.org/abs/2402.14796 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Explicit formulae for linear characters of $Γ_0(N)$
We give explicit formulae for a class of complex linear unitary characters of the congruence subgroups $Γ_0(N)$ which involve a variant of Rademacher's $Ψ$ function. We then prove that these characters cover all characters of $Γ_0(N)$ precisely when $N=1,2,3,4,5,6,7,8,10,12,13$.

[2025-06-05 Thu (UTC), 7 new articles found for astro-ph.SR Solar and Stellar Astrophysics]
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This https://arxiv.org/abs/2407.05630 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Enabling 6G Performance in the Upper Mid-Band by Transitioning From Massive to Gigantic MIMO
The initial 6G networks will likely operate in the upper mid-band (7-24 GHz), which has decent propagation conditions but underwhelming new spectrum availability. In this paper, we explore whether we can anyway reach the ambitious 6G performance goals by evolving the multiple-input multiple-output (MIMO) technology from massive in 5G to gigantic in 6G. We describe how many antennas are needed to reach the envisioned 6G peak user rates, how many can realistically be deployed in practical radio e…

Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM
Shumin Lian, Jingwen Tong, Jun Zhang, Liqun Fu
https://arxiv.org/abs/2506.04594

Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM
WiFi networks have achieved remarkable success in enabling seamless communication and data exchange worldwide. The IEEE 802.11be standard, known as WiFi 7, introduces Multi-Link Operation (MLO), a groundbreaking feature that enables devices to establish multiple simultaneous connections across different bands and channels. While MLO promises substantial improvements in network throughput and latency reduction, it presents significant challenges in channel allocation, particularly in dense netwo…

Robust Moment Identification for Nonlinear PDEs via a Neural ODE Approach
Shaoxuan Chen, Su Yang, Panayotis G. Kevrekidis, Wei Zhu
https://arxiv.org/abs/2506.05245

Robust Moment Identification for Nonlinear PDEs via a Neural ODE Approach
We propose a data-driven framework for learning reduced-order moment dynamics from PDE-governed systems using Neural ODEs. In contrast to derivative-based methods like SINDy, which necessitate densely sampled data and are sensitive to noise, our approach based on Neural ODEs directly models moment trajectories, enabling robust learning from sparse and potentially irregular time series. Using as an application platform the nonlinear Schrödinger equation, the framework accurately recovers govern…

Overlap Gap and Computational Thresholds in the Square Wave Perceptron
Marco Benedetti, Andrej Bogdanov, Enrico M. Malatesta, Marc M\'ezard, Gianmarco Perrupato, Alon Rosen, Nikolaj I. Schwartzbach, Riccardo Zecchina
https://arxiv.org/abs/2506.05197

Overlap Gap and Computational Thresholds in the Square Wave Perceptron
Square Wave Perceptrons (SWPs) form a class of neural network models with oscillating activation function that exhibit intriguing ``hardness'' properties in the high-dimensional limit at a fixed signal-to-noise ratio $α= O(1)$. In this work, we examine two key aspects of these models. The first is related to the so-called overlap-gap property, that is a disconnectivity feature of the geometry of the solution space of combinatorial optimization problems proven to cause the failure of a large fa…

COSMOS-Web: MIRI Data Reduction and Number Counts at 7.7$\mu$m using JWST
Santosh Harish, Jeyhan S. Kartaltepe, Daizhong Liu, Anton M. Koekemoer, Caitlin M. Casey, Maximilien Franco, Hollis B. Akins, Olivier Ilbert, Marko Shuntov, Nicole E. Drakos, Mike Engesser, Andreas L. Faisst, Ghassem Gozaliasl, Crystal L. Martin, Michaela Hirschmann, Vasily Kokorev, Erini Lambrides, Henry Joy McCracken, Jed McKinney, Louise Paquereau, Jason Rhodes, Brant E. Robertson

COSMOS-Web: MIRI Data Reduction and Number Counts at 7.7$μ$m using JWST
The COSMOS-Web survey is the largest JWST Cycle 1 General Observer program covering a contiguous ~0.54 deg$^2$ area with NIRCam imaging in four broad-band filters and a non-contiguous ~0.2 deg$^2$ with parallel MIRI imaging in a single broad-band filter, F770W. Here we present a comprehensive overview of the MIRI imaging observations, the data reduction procedure, the COSMOS-Web MIRI photometric catalog, and the first data release including the entire COSMOS-Web MIRI coverage. Data reduction is…

This https://arxiv.org/abs/2404.04502 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

The interplay between additive and symmetric large sets and their combinatorial applications
The study of symmetric structures is a new trend in Ramsey theory. Recently in [7], Di Nasso initiated a systematic study of symmetrization of classical Ramsey theoretical results, and proved a symmetric version of several Ramsey theoretic results. In this paper Di Nasso asked if his method could be adapted to find new non-linear Diophantine equations that are partition regular [7,Final remarks (4)]. By analyzing additive, multiplicative, and symmetric large sets, we construct new partition reg…

This https://arxiv.org/abs/2410.14652 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Two-dimensional many-body localized systems coupled to a heat bath
We numerically investigate the effect of coupling a two-dimensional many-body localized system to a finite heat bath, using shallow quantum circuits as a variational ansatz. Specifically, we simulate optical lattice experiments with two components of ultracold bosons, where only one species is subject to a random disorder potential and the other acts as a heat bath. We obtain a filling fraction dependent phase diagram with a critical filling consistent with experiments. We also calculate two-po…

[2025-06-05 Thu (UTC), 1 new article found for nlin.PS Pattern Formation and Solitons]
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This https://arxiv.org/abs/2504.18820 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Potential-Driven Metal Cycling: JADES Census of Gas-Phase Metallicity for galaxies at 1 < z < 7
The gravitational potential is established as a critical determinant of gas-phase metallicity (12+log(O/H)) in low-redshift galaxies, whereas its influence remains unconfirmed at high redshifts. We investigate the correlation between gas-phase metallicity and effective radius ($R_{\rm e}$) for a sample of galaxies with redshifts ranging from 1 to 7, drawn from JADES (JWST Advanced Deep Extragalactic Survey) Data Release 3. We calculate the metallicities using four strong-line methods: ${\rm N2S…

This https://arxiv.org/abs/2406.14200 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Gaussian approximation of dynamic cavity equations for linearly-coupled stochastic dynamics
Stochastic dynamics on sparse graphs and disordered systems often lead to complex behaviors characterized by heterogeneity in time and spatial scales, slow relaxation, localization, and aging phenomena. The mathematical tools and approximation techniques required to analyze these complex systems are still under development, posing significant technical challenges and resulting in a reliance on numerical simulations. We introduce a novel computational framework for investigating the dynamics of …

This https://arxiv.org/abs/2409.12068 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

The repetition threshold for ternary rich words
In 2017, Vesti proposed the problem of determining the repetition threshold for infinite rich words, i.e., for infinite words in which all factors of length $n$ contain $n$ distinct nonempty palindromic factors. In 2020, Currie, Mol, and Rampersad proved a conjecture of Baranwal and Shallit that the repetition threshold for binary rich words is $2 + \sqrt{2}/2$. In this paper, we prove a structure theorem for $16/7$-power-free ternary rich words. Using the structure theorem, we deduce that the …

Stokes Waves in Water of Finite Depth
Eleanor Byrnes, Bernard Deconinck, Anastassiya Semenova
https://arxiv.org/abs/2506.03436 https://

Stokes Waves in Water of Finite Depth
Periodic water waves of permanent form traveling at constant speed, the so-called Stokes waves, are studied in water of fixed finite depth using methods previously used in water of infinite depth. We apply our methods to waves of varying steepness over a range of fixed depths in order to determine how a number of physical quantities related to the waves change as the steepness of the waves increases. Finally, we examine the Taylor sign condition for these waves, as well as the complex singulari…

Exploring over 700 massive quiescent galaxies at z = 2-7: Demographics and stellar mass functions
William M. Baker, Francesco Valentino, Claudia del P. Lagos, Kei Ito, Christian Kragh Jespersen, Rashmi Gottumukkala, Jens Hjorth, Danial Langeroodi, Aidan Sedgewick
https://arxiv.org/abs/2506.04119

Exploring over 700 massive quiescent galaxies at z = 2-7: Demographics and stellar mass functions
High-redshift ($z>2$) massive quiescent galaxies are crucial tests of early galaxy formation and evolutionary mechanisms through their cosmic number densities and stellar mass functions (SMFs). We explore a sample of 745 massive ($\rm M_*> 10^{9.5}M_\odot$) quiescent galaxies from $z=2-7$ in over 800 arcmin$^2$ of NIRCam imaging from a compilation of public JWST fields (with a total area $>$ 5 $\times$ previous JWST studies). We compute and report their cosmic number densities, stellar mass fun…

[2025-06-05 Thu (UTC), no new articles found for cond-mat.dis-nn Disordered Systems and Neural Networks]
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[2025-06-06 Fri (UTC), 7 new articles found for eess.AS Audio and Speech Processing]
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This https://arxiv.org/abs/2506.01483 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Inter-Speaker Relative Cues for Text-Guided Target Speech Extraction
We propose a novel approach that utilize inter-speaker relative cues for distinguishing target speakers and extracting their voices from mixtures. Continuous cues (e.g., temporal order, age, pitch level) are grouped by relative differences, while discrete cues (e.g., language, gender, emotion) retain their categories. Relative cues offers greater flexibility than fixed speech attribute classification, facilitating much easier expansion of text-guided target speech extraction datasets. Our exper…

This https://arxiv.org/abs/2505.24080 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The Impact of Galaxy Overdensities and Ionized Bubbles on Ly$α$ Emission $z\sim7.0\mbox{--}8.5$
Ly$α$ spectroscopy with {\it JWST} is opening a new window on the sizes of ionized bubbles through the reionization epoch. Theoretical expectations suggest typical bubble radii should be 0.6--1.5 pMpc at $z\simeq 7$, assuming neutral hydrogen fractions of the intergalactic medium in the range $\overline{x}_{\rm HI}$=0.5--0.7. Here we investigate this picture using {\it JWST} to characterize the environment and Ly$α$ emission of 292 galaxies at $7.0

[2025-06-04 Wed (UTC), 1 new article found for nlin.PS Pattern Formation and Solitons]
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This https://arxiv.org/abs/2505.22251 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Evaluation of LLMs in Speech is Often Flawed: Test Set Contamination in Large Language Models for Speech Recognition
Recent work suggests that large language models (LLMs) can improve performance of speech tasks compared to existing systems. To support their claims, results on LibriSpeech and Common Voice are often quoted. However, this work finds that a substantial amount of the LibriSpeech and Common Voice evaluation sets appear in public LLM pretraining corpora. This calls into question the reliability of findings drawn from these two datasets. To measure the impact of contamination, LLMs trained with or w…

This https://arxiv.org/abs/2505.02927 has been replaced.
initial toot: https://mastoxiv.page/@arX…

The Physics of Local Optimization in Complex Disordered Systems
Limited resources motivate decomposing large-scale problems into smaller, "local" subsystems and stitching together the so-found solutions. We explore the physics underlying this approach and discuss the concept of "local hardness", i.e., complexity from the local solver perspective, in determining the ground states of both P- and NP-hard spin-glasses and related systems. Depending on the model considered, we observe varying scaling behaviors in how errors associated with local predictions deca…

Brightest Group Galaxies IV: Probing Size--Mass Relation and Morphological Quenching in COSMOS-Web from $z = 3.7$
Ghassem Gozaliasl, Lilan Yang, Greta Toni, Fatemeh Abedini, Rafael C. Arango-Toro, Arif Babul, Caitlin M. Casey, Nima Chartap, Nicole E. Drakos, Andreas L. Faisst, Alexis Finoguenov, Maximilien Franco, Gavin Leroy, G\"unther Hasinger, Hossein Hatamnia, Olivier Ilbert, Shuowen Jin, Darshan Kakkad, Atousa Kalantari, Jeyhan S. Kartaltepe, Ali Ahmad Khostovan, Anton M. Koe…

Brightest Group Galaxies IV: Probing Size--Mass Relation and Morphological Quenching in COSMOS-Web from $z = 3.7$
We present a comprehensive study of the structural evolution of Brightest Group Galaxies (BGGs) from redshift $z \simeq 0.08$ to $z = 3.7$ using the \textit{James Webb Space Telescope}'s 255h COSMOS-Web program. This survey provides deep NIRCam imaging in four filters (F115W, F150W, F277W, F444W) across $\sim 0.54~\mathrm{deg}^2$ and MIRI coverage in $\sim 0.2~\mathrm{deg}^2$ of the COSMOS field. High-resolution NIRCam imaging enables robust size and morphological measurements, while multiwavel…

This https://arxiv.org/abs/2407.15101 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Holographic nature of critical quantum states of proteins
The Anderson metal-insulator transition is a fundamental phenomenon in condensed matter physics, describing the transition from a conducting (metallic) to a non-conducting (insulating) state driven by disorder in a material. At the critical point of the Anderson transition, wave functions exhibit multifractal behavior, and energy levels display a universal distribution, indicating non-trivial correlations in the eigenstates. Recent studies have shown that proteins, traditionally considered insu…

This https://arxiv.org/abs/2501.09060 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The COSMOS-Web deep galaxy group catalog up to $z=3.7$
Galaxy groups with $M_{tot} \lesssim 10^{14}$ $M_\odot$ and up to a few tens of members are the most common galaxy environment, marking the transition between field and massive clusters. Identifying groups plays a crucial role in understanding structure formation and galaxy evolution. Modern deep surveys allow us to build well-characterized samples of groups up to the regime where structures were taking shape. We aimed to build the largest deep catalog of galaxy groups to date over the COSMOS-W…

Multivariate Probabilistic Assessment of Speech Quality
Fredrik Cumlin, Xinyu Liang, Victor Ungureanu, Chandan K. A. Reddy, Christian Sch\"uldt, Saikat Chatterjee
https://arxiv.org/abs/2506.04890

Multivariate Probabilistic Assessment of Speech Quality
The mean opinion score (MOS) is a standard metric for assessing speech quality, but its singular focus fails to identify specific distortions when low scores are observed. The NISQA dataset addresses this limitation by providing ratings across four additional dimensions: noisiness, coloration, discontinuity, and loudness, alongside MOS. In this paper, we extend the explored univariate MOS estimation to a multivariate framework by modeling these dimensions jointly using a multivariate Gaussian d…

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition
Yi-Cheng Lin, Huang-Cheng Chou, Yu-Hsuan Li Liang, Hung-yi Lee
https://arxiv.org/abs/2506.04652

EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition
Speech emotion recognition (SER) systems often exhibit gender bias. However, the effectiveness and robustness of existing debiasing methods in such multi-label scenarios remain underexplored. To address this gap, we present EMO-Debias, a large-scale comparison of 13 debiasing methods applied to multi-label SER. Our study encompasses techniques from pre-processing, regularization, adversarial learning, biased learners, and distributionally robust optimization. Experiments conducted on acted and …

[2025-06-04 Wed (UTC), 1 new article found for cond-mat.dis-nn Disordered Systems and Neural Networks]
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Distance to the Galactic centre 7$^\prime$ halo from HI absorption
Debangan Maji, Subhashis Roy
https://arxiv.org/abs/2506.02799 https://

Distance to the Galactic centre 7$^\prime$ halo from HI absorption
Using archival data, we have made an HI absorption study of the 7$^\prime$ halo surrounding the Sgr A complex, observed towards the Galactic centre (GC) region. We find strong HI absorption near velocities of $-$53 km s$^{-1}$, which is due to the 3-kpc arm, placing it beyond 5 kpc from us. We further examined the HI absorption properties towards 5 different parts of the 7$^\prime$ halo. Absorption by +50 km s$^{-1}$ GC cloud is seen towards only 3 parts of the halo, but not towards the other 2…

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Haibin Wu, Yuxuan Hu, Ruchao Fan, Xiaofei Wang, Kenichi Kumatani, Bo Ren, Jianwei Yu, Heng Lu, Lijuan Wang, Yao Qian, Jinyu Li
https://arxiv.org/abs/2506.04518

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Speech language models (Speech LMs) enable end-to-end speech-text modelling within a single model, offering a promising direction for spoken dialogue systems. The choice of speech-text jointly decoding paradigm plays a critical role in performance, efficiency, and alignment quality. In this work, we systematically compare representative joint speech-text decoding strategies-including the interleaved, and parallel generation paradigms-under a controlled experimental setup using the same base lan…

French Listening Tests for the Assessment of Intelligibility, Quality, and Identity of Body-Conducted Speech Enhancement
Thomas Joubaud, Julien Hauret, V\'eronique Zimpfer, \'Eric Bavu
https://arxiv.org/abs/2506.04495

French Listening Tests for the Assessment of Intelligibility, Quality, and Identity of Body-Conducted Speech Enhancement
This study evaluates the Extreme Bandwidth Extension Network (EBEN) model on body-conduction sensors through listening tests. Using the Vibravox dataset, we assess intelligibility with a French Modified Rhyme Test, speech quality with a MUSHRA (MUltiple Stimuli with Hidden Reference and Anchor) protocol and speaker identity preservation with an A/B identification task. The experiments involved male and female speakers recorded with a forehead accelerometer, rigid in-ear and throat microphones. …

Bringing Interpretability to Neural Audio Codecs
Samir Sadok, Julien Hauret, \'Eric Bavu
https://arxiv.org/abs/2506.04492 https://

Bringing Interpretability to Neural Audio Codecs
The advent of neural audio codecs has increased in popularity due to their potential for efficiently modeling audio with transformers. Such advanced codecs represent audio from a highly continuous waveform to low-sampled discrete units. In contrast to semantic units, acoustic units may lack interpretability because their training objectives primarily focus on reconstruction performance. This paper proposes a two-step approach to explore the encoding of speech information within the codec tokens…

Can we reconstruct a dysarthric voice with the large speech model Parler TTS?
Ariadna Sanchez, Simon King
https://arxiv.org/abs/2506.04397 https://

Can we reconstruct a dysarthric voice with the large speech model Parler TTS?
Speech disorders can make communication hard or even impossible for those who develop them. Personalised Text-to-Speech is an attractive option as a communication aid. We attempt voice reconstruction using a large speech model, with which we generate an approximation of a dysarthric speaker's voice prior to the onset of their condition. In particular, we investigate whether a state-of-the-art large speech model, Parler TTS, can generate intelligible speech while maintaining speaker identity. We…

Phi-Omni-ST: A multimodal language model for direct speech-to-speech translation
Yuxuan Hu, Haibin Wu, Ruchao Fan, Xiaofei Wang, Heng Lu, Yao Qian, Jinyu Li
https://arxiv.org/abs/2506.04392

Phi-Omni-ST: A multimodal language model for direct speech-to-speech translation
Speech-aware language models (LMs) have demonstrated capabilities in understanding spoken language while generating text-based responses. However, enabling them to produce speech output efficiently and effectively remains a challenge. In this paper, we present Phi-Omni-ST, a multimodal LM for direct speech-to-speech translation (ST), built on the open-source Phi-4 MM model. Phi-Omni-ST extends its predecessor by generating translated speech using an audio transformer head that predicts audio to…

This https://arxiv.org/abs/2505.19931 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Accelerating Flow-Matching-Based Text-to-Speech via Empirically Pruned Step Sampling
Flow-matching-based text-to-speech (TTS) models, such as Voicebox, E2 TTS, and F5-TTS, have attracted significant attention in recent years. These models require multiple sampling steps to reconstruct speech from noise, making inference speed a key challenge. Reducing the number of sampling steps can greatly improve inference efficiency. To this end, we introduce Fast F5-TTS, a training-free approach to accelerate the inference of flow-matching-based TTS models. By inspecting the sampling traje…

This https://arxiv.org/abs/2505.16044 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Multimodal Biomarkers for Schizophrenia: Towards Individual Symptom Severity Estimation
Studies on schizophrenia assessments using deep learning typically treat it as a classification task to detect the presence or absence of the disorder, oversimplifying the condition and reducing its clinical applicability. This traditional approach overlooks the complexity of schizophrenia, limiting its practical value in healthcare settings. This study shifts the focus to individual symptom severity estimation using a multimodal approach that integrates speech, video, and text inputs. We devel…

This https://arxiv.org/abs/2505.15965 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Analyzing the Impact of Accent on English Speech: Acoustic and Articulatory Perspectives
Advancements in AI-driven speech-based applications have transformed diverse industries ranging from healthcare to customer service. However, the increasing prevalence of non-native accented speech in global interactions poses significant challenges for speech-processing systems, which are often trained on datasets dominated by native speech. This study investigates accented English speech through articulatory and acoustic analysis, identifying simpler coordination patterns and higher average p…

This https://arxiv.org/abs/2504.12423 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Benchmarking Audio Deepfake Detection Robustness in Real-world Communication Scenarios
Existing Audio Deepfake Detection (ADD) systems often struggle to generalise effectively due to the significantly degraded audio quality caused by audio codec compression and channel transmission effects in real-world communication scenarios. To address this challenge, we developed a rigorous benchmark to evaluate the performance of the ADD system under such scenarios. We introduced ADD-C, a new test dataset to evaluate the robustness of ADD systems under diverse communication conditions, inclu…

This https://arxiv.org/abs/2406.05298 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Spectral Codecs: Improving Non-Autoregressive Speech Synthesis with Spectrogram-Based Audio Codecs
Historically, most speech models in machine-learning have used the mel-spectrogram as a speech representation. Recently, discrete audio tokens produced by neural audio codecs have become a popular alternate speech representation for speech synthesis tasks such as text-to-speech (TTS). However, the data distribution produced by such codecs is too complex for some TTS models to predict, typically requiring large autoregressive models to get good quality. Most existing audio codecs use Residual Ve…

This https://arxiv.org/abs/2406.01205 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style Control
In this paper, we present ControlSpeech, a text-to-speech (TTS) system capable of fully cloning the speaker's voice and enabling arbitrary control and adjustment of speaking style. Prior zero-shot TTS models only mimic the speaker's voice without further control and adjustment capabilities while prior controllable TTS models cannot perform speaker-specific voice generation. Therefore, ControlSpeech focuses on a more challenging task: a TTS system with controllable timbre, content, and style at …

This https://arxiv.org/abs/2402.12208 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Language-Codec: Bridging Discrete Codec Representations and Speech Language Models
In recent years, large language models have achieved significant success in generative tasks related to speech, audio, music, and other signal domains. A crucial element of these models is the discrete acoustic codecs, which serve as an intermediate representation replacing the mel-spectrogram. However, there exist several gaps between discrete codecs and downstream speech language models. Specifically, 1) Due to the reconstruction paradigm of the Codec model and the structure of residual vecto…

[2025-06-05 Thu (UTC), 8 new articles found for eess.AS Audio and Speech Processing]
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HiFiTTS-2: A Large-Scale High Bandwidth Speech Dataset
Ryan Langman, Xuesong Yang, Paarth Neekhara, Shehzeen Hussain, Edresson Casanova, Evelina Bakhturina, Jason Li
https://arxiv.org/abs/2506.04152

HiFiTTS-2: A Large-Scale High Bandwidth Speech Dataset
This paper introduces HiFiTTS-2, a large-scale speech dataset designed for high-bandwidth speech synthesis. The dataset is derived from LibriVox audiobooks, and contains approximately 36.7k hours of English speech for 22.05 kHz training, and 31.7k hours for 44.1 kHz training. We present our data processing pipeline, including bandwidth estimation, segmentation, text preprocessing, and multi-speaker detection. The dataset is accompanied by detailed utterance and audiobook metadata generated by o…

Sound Field Reconstruction Using Physics-Informed Boundary Integral Networks
Stefano Damiano, Toon van Waterschoot
https://arxiv.org/abs/2506.03917 https:/…

Sound Field Reconstruction Using Physics-Informed Boundary Integral Networks
Sound field reconstruction refers to the problem of estimating the acoustic pressure field over an arbitrary region of space, using only a limited set of measurements. Physics-informed neural networks have been adopted to solve the problem by incorporating in the training loss function the governing partial differential equation, either the Helmholtz or the wave equation. In this work, we introduce a boundary integral network for sound field reconstruction. Relying on the Kirchhoff-Helmholtz bo…

Tone recognition in low-resource languages of North-East India: peeling the layers of SSL-based speech models
Parismita Gogoi, Sishir Kalita, Wendy Lalhminghlui, Viyazonuo Terhiija, Moakala Tzudir, Priyankoo Sarmah, S. R. M. Prasanna
https://arxiv.org/abs/2506.03606

Tone recognition in low-resource languages of North-East India: peeling the layers of SSL-based speech models
This study explores the use of self-supervised learning (SSL) models for tone recognition in three low-resource languages from North Eastern India: Angami, Ao, and Mizo. We evaluate four Wav2vec2.0 base models that were pre-trained on both tonal and non-tonal languages. We analyze tone-wise performance across the layers for all three languages and compare the different models. Our results show that tone recognition works best for Mizo and worst for Angami. The middle layers of the SSL models ar…

BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing
Masaya Kawamura, Takuya Hasumi, Yuma Shirahata, Ryuichi Yamamoto
https://arxiv.org/abs/2506.03515

BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing
This paper proposes a highly compact, lightweight text-to-speech (TTS) model for on-device applications. To reduce the model size, the proposed model introduces two techniques. First, we introduce quantization-aware training (QAT), which quantizes model parameters during training to as low as 1.58-bit. In this case, most of 32-bit model parameters are quantized to ternary values {-1, 0, 1}. Second, we propose a method named weight indexing. In this method, we save a group of 1.58-bit weights as…

A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations
Petr Grinberg, Ankur Kumar, Surya Koppisetti, Gaurav Bharaj
https://arxiv.org/abs/2506.03425

A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations
Evaluating explainability techniques, such as SHAP and LRP, in the context of audio deepfake detection is challenging due to lack of clear ground truth annotations. In the cases when we are able to obtain the ground truth, we find that these methods struggle to provide accurate explanations. In this work, we propose a novel data-driven approach to identify artifact regions in deepfake audio. We consider paired real and vocoded audio, and use the difference in time-frequency representation as th…

HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar, Swarup Ranjan Behera, Pailla Balakrishna Reddy, Arun Balaji Buduru, Rajesh Sharma
https://arxiv.org/abs/2506.03403

HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition
Compression-based representations (CBRs) from neural audio codecs such as EnCodec capture intricate acoustic features like pitch and timbre, while representation-learning-based representations (RLRs) from pre-trained models trained for speech representation learning such as WavLM encode high-level semantic and prosodic information. Previous research on Speech Emotion Recognition (SER) has explored both, however, fusion of CBRs and RLRs haven't been explored yet. In this study, we solve this gap…

SNIFR : Boosting Fine-Grained Child Harmful Content Detection Through Audio-Visual Alignment with Cascaded Cross-Transformer
Orchid Chetia Phukan, Mohd Mujtaba Akhtar, Girish, Swarup Ranjan Behera, Abu Osama Siddiqui, Sarthak Jain, Priyabrata Mallick, Jaya Sai Kiran Patibandla, Pailla Balakrishna Reddy, Arun Balaji Buduru, Rajesh Sharma
https://

SNIFR : Boosting Fine-Grained Child Harmful Content Detection Through Audio-Visual Alignment with Cascaded Cross-Transformer
As video-sharing platforms have grown over the past decade, child viewership has surged, increasing the need for precise detection of harmful content like violence or explicit scenes. Malicious users exploit moderation systems by embedding unsafe content in minimal frames to evade detection. While prior research has focused on visual cues and advanced such fine-grained detection, audio features remain underexplored. In this study, we embed audio cues with visual for fine-grained child harmful c…

Towards Source Attribution of Singing Voice Deepfake with Multimodal Foundation Models
Orchid Chetia Phukan, Girish, Mohd Mujtaba Akhtar, Swarup Ranjan Behera, Priyabrata Mallick, Pailla Balakrishna Reddy, Arun Balaji Buduru, Rajesh Sharma
https://arxiv.org/abs/2506.03364

Towards Source Attribution of Singing Voice Deepfake with Multimodal Foundation Models
In this work, we introduce the task of singing voice deepfake source attribution (SVDSA). We hypothesize that multimodal foundation models (MMFMs) such as ImageBind, LanguageBind will be most effective for SVDSA as they are better equipped for capturing subtle source-specific characteristics-such as unique timbre, pitch manipulation, or synthesis artifacts of each singing voice deepfake source due to their cross-modality pre-training. Our experiments with MMFMs, speech foundation models and mus…

This https://arxiv.org/abs/2505.20552 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Effect of laboratory conditions on the perception of virtual stages for music
This manuscript presents initial findings critical for supporting augmented acoustics experiments in custom-made hearing booths, addressing a key challenge in ensuring perceptual validity and experimental rigor in these highly sensitive setups. This validation ensures our proposed methodology is sound, guarantees the reliability of future results, and lays the foundational groundwork for subsequent perceptual studies and the development of robust guidelines for laboratory design in virtual acou…

This https://arxiv.org/abs/2504.14906 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

OmniAudio: Generating Spatial Audio from 360-Degree Video
Traditional video-to-audio generation techniques primarily focus on perspective video and non-spatial audio, often missing the spatial cues necessary for accurately representing sound sources in 3D environments. To address this limitation, we introduce a novel task, 360V2SA, to generate spatial audio from 360-degree videos, specifically producing First-order Ambisonics (FOA) audio - a standard format for representing 3D spatial audio that captures sound directionality and enables realistic 3D a…

This https://arxiv.org/abs/2503.07352 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Score-informed Music Source Separation: Improving Synthetic-to-real Generalization in Classical Music
Music source separation is the task of separating a mixture of instruments into constituent tracks. Music source separation models are typically trained using only audio data, although additional information can be used to improve the model's separation capability. In this paper, we propose two ways of using musical scores to aid music source separation: a score-informed model where the score is concatenated with the magnitude spectrogram of the audio mixture as the input of the model, and a mo…

This https://arxiv.org/abs/2410.12266 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

FlashAudio: Rectified Flows for Fast and High-Fidelity Text-to-Audio Generation
Recent advancements in latent diffusion models (LDMs) have markedly enhanced text-to-audio generation, yet their iterative sampling processes impose substantial computational demands, limiting practical deployment. While recent methods utilizing consistency-based distillation aim to achieve few-step or single-step inference, their one-step performance is constrained by curved trajectories, preventing them from surpassing traditional diffusion models. In this work, we introduce FlashAudio with r…

[2025-06-04 Wed (UTC), 17 new articles found for eess.AS Audio and Speech Processing]
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