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Found 18 papers, 4 papers with code
O2V-Mapping: Online Open-Vocabulary Mapping with Neural Implicit Representation
Online construction of open-ended language scenes is crucial for robotic applications, where open-vocabulary interactive scene understanding is required.
HGS-Mapping: Online Dense Mapping Using Hybrid Gaussian Representation in Urban Scenes
However, integrating 3DGS into a street-view dense mapping framework still faces two challenges, including incomplete reconstruction due to the absence of geometric information beyond the LiDAR coverage area and extensive computation for reconstruction in large urban scenes.
Long-Form Speech Translation through Segmentation with Finite-State Decoding Constraints on Large Language Models
One challenge in speech translation is that plenty of spoken content is long-form, but short units are necessary for obtaining high-quality translations.
UniAP: Unifying Inter- and Intra-Layer Automatic Parallelism by Mixed Integer Quadratic Programming
To the best of our knowledge, UniAP is the first parallel method that can jointly optimize the two categories of parallel strategies to find an optimal solution.
Theory of Periodic Sequence: Bridging Time-Domain and Frequency-Domain for Computational Electromagnetics
Time-periodic form or expression is a ubiquitous natural and man-made phenomenon observable in all the scientific and engineering disciplines.
LAST: Scalable Lattice-Based Speech Modelling in JAX
We introduce LAST, a LAttice-based Speech Transducer library in JAX.
Summative Student Course Review Tool Based on Machine Learning Sentiment Analysis to Enhance Life Science Feedback Efficacy
Often, student opinions are gathered with a general comment section that solicits their feelings towards their courses without polling specifics about course contents.
Alignment Entropy Regularization
Existing training criteria in automatic speech recognition(ASR) permit the model to freely explore more than one time alignments between the feature and label sequences.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Global Normalization for Streaming Speech Recognition in a Modular Framework
We introduce the Globally Normalized Autoregressive Transducer (GNAT) for addressing the label bias problem in streaming speech recognition.
Transformer-based Models of Text Normalization for Speech Applications
Text normalization, or the process of transforming text into a consistent, canonical form, is crucial for speech applications such as text-to-speech synthesis (TTS).
FedJAX: Federated learning simulation with JAX
Federated learning is a machine learning technique that enables training across decentralized data.
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data
We present a theoretical and algorithmic study of the multiple-source domain adaptation problem in the common scenario where the learner has access only to a limited amount of labeled target data, but where the learner has at disposal a large amount of labeled data from multiple source domains.
Generalized logistic growth modeling of the COVID-19 outbreak in 29 provinces in China and in the rest of the world
Japan and Italy are in serious situations with no short-term end to the outbreak to be expected.
Populations and Evolution Biological Physics Applications
Non-rigid Registration Method between 3D CT Liver Data and 2D Ultrasonic Images based on Demons Model
The non-rigid registration between CT data and ultrasonic images of liver can facilitate the diagnosis and treatment, which has been widely studied in recent years.
Minimally Supervised Written-to-Spoken Text Normalization
In speech-applications such as text-to-speech (TTS) or automatic speech recognition (ASR), \emph{text normalization} refers to the task of converting from a \emph{written} representation into a representation of how the text is to be \emph{spoken}.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Node-By-Node Greedy Deep Learning for Interpretable Features
Multilayer networks have seen a resurgence under the umbrella of deep learning.
