Zobrazeno 1 - 10
of 9 358
pro vyhledávání: '"Nithin, A."'
Inferring causal relationships in the decision-making processes of machine learning algorithms is a crucial step toward achieving explainable Artificial Intelligence (AI). In this research, we introduce a novel causality measure and a distance metric
Externí odkaz:
http://arxiv.org/abs/2411.01881
Autor:
S, Remya Ajai A, Nagaraj, Nithin
Inspired by the human brain's structure and function, Artificial Neural Networks (ANN) were developed for data classification. However, existing Neural Networks, including Deep Neural Networks, do not mimic the brain's rich structure. They lack key f
Externí odkaz:
http://arxiv.org/abs/2410.23351
Autor:
Somasekharan, Nithin, Pan, Shaowu
Representation learning for high-dimensional, complex physical systems aims to identify a low-dimensional intrinsic latent space, which is crucial for reduced-order modeling and modal analysis. To overcome the well-known Kolmogorov barrier, deep auto
Externí odkaz:
http://arxiv.org/abs/2410.18148
Evaluation Of P300 Speller Performance Using Large Language Models Along With Cross-Subject Training
Autor:
Parthasarathy, Nithin, Soetedjo, James, Panchavati, Saarang, Parthasarathy, Nitya, Arnold, Corey, Pouratian, Nader, Speier, William
Amyotrophic lateral sclerosis (ALS), a progressive neuromuscular degenerative disease, severely restricts patient communication capacity within a few years of onset, resulting in a significant deterioration of quality of life. The P300 speller brain
Externí odkaz:
http://arxiv.org/abs/2410.15161
In this paper, we study the problem of finding an envy-free allocation of indivisible goods among multiple agents. EFX, which stands for envy-freeness up to any good, is a well-studied relaxation of the envy-free allocation problem and has been shown
Externí odkaz:
http://arxiv.org/abs/2410.13580
This paper presents a Discrete-Time Model Predictive Controller (MPC) for humanoid walking with online footstep adjustment. The proposed controller utilizes a hierarchical control approach. The high-level controller uses a low-dimensional Linear Inve
Externí odkaz:
http://arxiv.org/abs/2410.06790
META-CAT: Speaker-Informed Speech Embeddings via Meta Information Concatenation for Multi-talker ASR
Autor:
Wang, Jinhan, Wang, Weiqing, Dhawan, Kunal, Park, Taejin, Kim, Myungjong, Medennikov, Ivan, Huang, He, Koluguri, Nithin, Balam, Jagadeesh, Ginsburg, Boris
We propose a novel end-to-end multi-talker automatic speech recognition (ASR) framework that enables both multi-speaker (MS) ASR and target-speaker (TS) ASR. Our proposed model is trained in a fully end-to-end manner, incorporating speaker supervisio
Externí odkaz:
http://arxiv.org/abs/2409.12352
Autor:
Park, Taejin, Medennikov, Ivan, Dhawan, Kunal, Wang, Weiqing, Huang, He, Koluguri, Nithin Rao, Puvvada, Krishna C., Balam, Jagadeesh, Ginsburg, Boris
We propose Sortformer, a novel neural model for speaker diarization, trained with unconventional objectives compared to existing end-to-end diarization models. The permutation problem in speaker diarization has long been regarded as a critical challe
Externí odkaz:
http://arxiv.org/abs/2409.06656
Autor:
Koluguri, Nithin Rao, Bartley, Travis, Xu, Hainan, Hrinchuk, Oleksii, Balam, Jagadeesh, Ginsburg, Boris, Kucsko, Georg
This paper presents a new method for training sequence-to-sequence models for speech recognition and translation tasks. Instead of the traditional approach of training models on short segments containing only lowercase or partial punctuation and capi
Externí odkaz:
http://arxiv.org/abs/2409.05601
A binary code Enc$:\{0,1\}^k \to \{0,1\}^n$ is $(0.5-\epsilon,L)$-list decodable if for all $w \in \{0,1\}^n$, the set List$(w)$ of all messages $m \in \{0,1\}^k$ such that the relative Hamming distance between Enc$(m)$ and $w$ is at most $0.5 -\epsi
Externí odkaz:
http://arxiv.org/abs/2409.01708