Zobrazeno 1 - 10
of 85 547
pro vyhledávání: '"Kawaguchi, So"'
Speech Emotion Recognition (SER) often operates on speech segments detected by a Voice Activity Detection (VAD) model. However, VAD models may output flawed speech segments, especially in noisy environments, resulting in degraded performance of subse
Externí odkaz:
http://arxiv.org/abs/2410.13282
The decrease of the chiral pseudocritical temperature $T_{\mathrm{pc}}$ with an applied strong magnetic field has been extensively investigated by various QCD low energy effective models and lattice QCD at physical point. We find that this decreasing
Externí odkaz:
http://arxiv.org/abs/2410.11360
Autor:
Zhu, Chenghao, Harikane, Yuichi, Ouchi, Masami, Ono, Yoshiaki, Onodera, Masato, Tang, Shenli, Isobe, Yuki, Matsuoka, Yoshiki, Kawaguchi, Toshihiro, Umeda, Hiroya, Nakajima, Kimihiko, Liang, Yongming, Xu, Yi, Zhang, Yechi, Sun, Dongsheng, Shimasaku, Kazuhiro, Greene, Jenny, Iwasawa, Kazushi, Kohno, Kotaro, Nagao, Tohru, Schulze, Andreas, Shibuya, Takatoshi, Hilmi, Miftahul, Schramm, Malte
We present deep Subaru/FOCAS spectra for two extreme emission line galaxies (EELGs) at $z\sim 1$ with strong {\sc[Oiii]}$\lambda$5007 emission lines, exhibiting equivalent widths (EWs) of $2905^{+946}_{-578}$ \AA\ and $2000^{+188}_{-159}$ \AA, compar
Externí odkaz:
http://arxiv.org/abs/2410.12198
This paper proposes a zero-shot speech emotion recognition (SER) method that estimates emotions not previously defined in the SER model training. Conventional methods are limited to recognizing emotions defined by a single word. Moreover, we have the
Externí odkaz:
http://arxiv.org/abs/2410.09636
We present our new general relativistic Monte Carlo (MC)-based neutrino radiation hydrodynamics code designed to solve axisymmetric systems with several improvements. The main improvements are as follows: (i) the development of an extended version of
Externí odkaz:
http://arxiv.org/abs/2410.02380
Autor:
Munoz, Gary D. Lopez, Minnich, Amanda J., Lutz, Roman, Lundeen, Richard, Dheekonda, Raja Sekhar Rao, Chikanov, Nina, Jagdagdorj, Bolor-Erdene, Pouliot, Martin, Chawla, Shiven, Maxwell, Whitney, Bullwinkel, Blake, Pratt, Katherine, de Gruyter, Joris, Siska, Charlotte, Bryan, Pete, Westerhoff, Tori, Kawaguchi, Chang, Seifert, Christian, Kumar, Ram Shankar Siva, Zunger, Yonatan
Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both single- and multi-modal models. As the GenAI ecosystem matures, the nee
Externí odkaz:
http://arxiv.org/abs/2410.02828
MIMII-Gen: Generative Modeling Approach for Simulated Evaluation of Anomalous Sound Detection System
Insufficient recordings and the scarcity of anomalies present significant challenges in developing and validating robust anomaly detection systems for machine sounds. To address these limitations, we propose a novel approach for generating diverse an
Externí odkaz:
http://arxiv.org/abs/2409.18542
Due to scarcity of time-series data annotated with descriptive texts, training a model to generate descriptive texts for time-series data is challenging. In this study, we propose a method to systematically generate domain-independent descriptive tex
Externí odkaz:
http://arxiv.org/abs/2409.16647
Large language models (LLMs) have gained increasing attention due to their prominent ability to understand and process texts. Nevertheless, LLMs largely remain opaque. The lack of understanding of LLMs has obstructed the deployment in safety-critical
Externí odkaz:
http://arxiv.org/abs/2409.14381
The probability-scale residual (PSR) is defined as $E\{sign(y, Y^*)\}$, where $y$ is the observed outcome and $Y^*$ is a random variable from the fitted distribution. The PSR is particularly useful for ordinal and censored outcomes for which fitted v
Externí odkaz:
http://arxiv.org/abs/2409.11385