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Found 19 papers, 5 papers with code
Adversarial Speech Generation and Natural Speech Recovery for Speech Content Protection
Moreover, based on the speech collection, we proposed a neural network-based frame-by-frame mapping method to recover the speech content by converting from the adversarial speech to the human speech.
Multi-Domain Dialogue State Tracking with Top-K Slot Self Attention
In the slot self-attention layers, we force each slot to involve information from the other k prominent slots and mask the rest out.
Dialogue State Tracking
Multi-domain Dialogue State Tracking
+1
HSCNN: A Hybrid-Siamese Convolutional Neural Network for Extremely Imbalanced Multi-label Text Classification
The data imbalance problem is a crucial issue for the multi-label text classification.
Ranked #11 on
Spectral Reconstruction
on ARAD-1K
Multi-task Peer-Review Score Prediction
To handle the small size of published datasets on the target aspect of scores, we propose a multi-task approach to leverage additional information from other aspects of scores for improving the performance of the target.
CaDRec: Contextualized and Debiased Recommender Model
To tackle the skewed distribution, we propose two strategies for disentangling interactions: (1) modeling individual biases to learn unbiased item embeddings, and (2) incorporating item popularity with positional encoding.
Enhanced Coherence-Aware Network with Hierarchical Disentanglement for Aspect-Category Sentiment Analysis
To address the issue of multiple aspect categories and sentiment entanglement, we propose a hierarchical disentanglement module to extract distinct categories and sentiment features.
A Comparative Study on Annotation Quality of Crowdsourcing and LLM via Label Aggregation
Whether Large Language Models (LLMs) can outperform crowdsourcing on the data annotation task is attracting interest recently.
FedCPC: An Effective Federated Contrastive Learning Method for Privacy Preserving Early-Stage Alzheimer's Speech Detection
The early-stage Alzheimer's disease (AD) detection has been considered an important field of medical studies.
GhostVec: A New Threat to Speaker Privacy of End-to-End Speech Recognition System
This paper demonstrates that an attacker can extract speaker information by querying speaker-adapted speech recognition (ASR) systems.
Reprogramming Self-supervised Learning-based Speech Representations for Speaker Anonymization
Current speaker anonymization methods, especially with self-supervised learning (SSL) models, require massive computational resources when hiding speaker identity.
Multiview Representation Learning from Crowdsourced Triplet Comparisons
Crowdsourcing has been used to collect data at scale in numerous fields.
Abstract, Rationale, Stance: A Joint Model for Scientific Claim Verification
In addition, we enhance the information exchanges and constraints among tasks by proposing a regularization term between the sentence attention scores of abstract retrieval and the estimated outputs of rational selection.
Learning from Multiple Annotators by Incorporating Instance Features
Learning from multiple annotators aims to induce a high-quality classifier from training instances, where each of them is associated with a set of possibly noisy labels provided by multiple annotators under the influence of their varying abilities and own biases.
A Neural Local Coherence Analysis Model for Clarity Text Scoring
Local coherence relation between two phrases/sentences such as cause-effect and contrast gives a strong influence of whether a text is well-structured or not.
CrowDEA: Multi-view Idea Prioritization with Crowds
We propose an approach, called CrowDEA, which estimates the embeddings of the ideas in the multiple-criteria preference space, the best viewpoint for each idea, and preference criterion for each evaluator, to obtain a set of frontier ideas.
DeepMet: A Reading Comprehension Paradigm for Token-level Metaphor Detection
Machine metaphor understanding is one of the major topics in NLP.
A Dataset of Crowdsourced Word Sequences: Collections and Answer Aggregation for Ground Truth Creation
To ensure the quality of the crowdsourced data, people can assign multiple workers to one question and then aggregate the multiple answers with diverse quality into a golden one.
Text Categorization by Learning Predominant Sense of Words as Auxiliary Task
Distributions of the senses of words are often highly skewed and give a strong influence of the domain of a document.
HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text Categorization
The lower the HS level, the less the categorization performance.
