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Found 15 papers, 9 papers with code
DiffSim: Taming Diffusion Models for Evaluating Visual Similarity
Diffusion models have fundamentally transformed the field of generative models, making the assessment of similarity between customized model outputs and reference inputs critically important.
Anti-Reference: Universal and Immediate Defense Against Reference-Based Generation
Diffusion models have revolutionized generative modeling with their exceptional ability to produce high-fidelity images.
An End-To-End Stuttering Detection Method Based On Conformer And BILSTM
In the SLT 2024 Stuttering Speech Challenge based on the AS-70 dataset [1], our model improved the mean F1 score by 24. 8% compared to the baseline method and achieved first place.
Automatic Assessment of Dysarthria Using Audio-visual Vowel Graph Attention Network
Currently, research on the automatic assessment of dysarthria primarily focuses on two approaches: one that utilizes expert features combined with machine learning, and the other that employs data-driven deep learning methods to extract representations.
Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
Overall, we hope this survey provides the research community with a comprehensive overview of the advancements in MTL from its inception in 1997 to the present in 2023.
An Audio-textual Diffusion Model For Converting Speech Signals Into Ultrasound Tongue Imaging Data
In this model, the inherent acoustic characteristics of individuals related to the tongue motion details are encoded by using wav2vec 2. 0, while the ASR transcriptions related to the universality of tongue motions are encoded by using BERT.
Effective Open Intent Classification with K-center Contrastive Learning and Adjustable Decision Boundary
In this paper, we introduce novel K-center contrastive learning and adjustable decision boundary learning (CLAB) to improve the effectiveness of open intent classification.
Schema Inference for Interpretable Image Classification
In this paper, we study a novel inference paradigm, termed as schema inference, that learns to deductively infer the explainable predictions by rebuilding the prior deep neural network (DNN) forwarding scheme, guided by the prevalent philosophical cognitive concept of schema.
Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk
However, the humor aspect of natural language is relatively under-investigated, especially in the age of pre-trained language models.
BERT-EMD: Many-to-Many Layer Mapping for BERT Compression with Earth Mover's Distance
In this way, our model can learn from different teacher layers adaptively for various NLP tasks.
Automatic identification of fossils and abiotic grains during carbonate microfacies analysis using deep convolutional neural networks
The machine classifier exhibited 0. 99 precision on minerals, such as dolomite and pyrite.
Multivariate Functional Regression via Nested Reduced-Rank Regularization
We propose a nested reduced-rank regression (NRRR) approach in fitting regression model with multivariate functional responses and predictors, to achieve tailored dimension reduction and facilitate interpretation/visualization of the resulting functional model.
Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
Multi-Task Learning (MTL) aims at boosting the overall performance of each individual task by leveraging useful information contained in multiple related tasks.
Integrative Multi-View Reduced-Rank Regression: Bridging Group-Sparse and Low-Rank Models
Multi-view data have been routinely collected in various fields of science and engineering.
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition
For this purpose, we developed novel techniques that address a key technical challenge: integrating the commands into a song in a way that can be effectively recognized by ASR through the air, in the presence of background noise, while not being detected by a human listener.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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