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Found 25 papers, 10 papers with code
Low Frame-rate Speech Codec: a Codec Designed for Fast High-quality Speech LLM Training and Inference
Large language models (LLMs) have significantly advanced audio processing through audio codecs that convert audio into discrete tokens, enabling the application of language modeling techniques to audio data.
Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results
Previously, we proposed a miner \cite{10. 1145/3557989. 3566158} that finds statistically significant regional colocation patterns.
Towards Statistically Significant Taxonomy Aware Co-location Pattern Detection
Given a collection of Boolean spatial feature types, their instances, a neighborhood relation (e. g., proximity), and a hierarchical taxonomy of the feature types, the goal is to find the subsets of feature types or their parents whose spatial interaction is statistically significant.
Improving Robustness of LLM-based Speech Synthesis by Learning Monotonic Alignment
Large Language Model (LLM) based text-to-speech (TTS) systems have demonstrated remarkable capabilities in handling large speech datasets and generating natural speech for new speakers.
Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
In contrast to the standard class-conditional CP (CCP) method that uniformly thresholds the class-wise conformity score for each class, the augmented label rank calibration step allows RC3P to selectively iterate this class-wise thresholding subroutine only for a subset of classes whose class-wise top-k error is small.
Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-variability-aware Approach
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty.
SALM: Speech-augmented Language Model with In-context Learning for Speech Recognition and Translation
We present a novel Speech Augmented Language Model (SALM) with {\em multitask} and {\em in-context} learning capabilities.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
FAST: Font-Agnostic Scene Text Editing
However, most of the existing STE methods show inferior editing performance because of (1) complex image backgrounds, (2) various font styles, and (3) varying word lengths within the text.
Probabilistically robust conformal prediction
We propose a novel adaptive PRCP (aPRCP) algorithm to achieve probabilistically robust coverage.
MMC: Multi-Modal Colorization of Images using Textual Descriptions
Handling various objects with different colors is a significant challenge for image colorization techniques.
Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis
Safe deployment of deep neural networks in high-stake real-world applications requires theoretically sound uncertainty quantification.
VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation
We introduce VANI, a very lightweight multi-lingual accent controllable speech synthesis system.
A CNN Based Framework for Unistroke Numeral Recognition in Air-Writing
Air-writing refers to virtually writing linguistic characters through hand gestures in three-dimensional space with six degrees of freedom.
Global Context-Aware Person Image Generation
The proposed strategy enables us to synthesize semantically coherent realistic persons that can blend into an existing scene without altering the global context.
Adapter-Based Extension of Multi-Speaker Text-to-Speech Model for New Speakers
In the proposed approach, a few small adapter modules are added to the original network.
TIPS: Text-Induced Pose Synthesis
In computer vision, human pose synthesis and transfer deal with probabilistic image generation of a person in a previously unseen pose from an already available observation of that person.
Scene Aware Person Image Generation through Global Contextual Conditioning
Finally, the target image is generated from the refined skeleton using another generative network conditioned on a given image of the target person.
Multi-scale Attention Guided Pose Transfer
Pose transfer refers to the probabilistic image generation of a person with a previously unseen novel pose from another image of that person having a different pose.
Shared and Private VAEs with Generative Replay for Continual Learning
We propose a hybrid continual learning model that is more suitable in real case scenarios to address the issues that has a task-invariant shared variational autoencoder and T task-specific variational autoencoders.
Dynamic VAEs with Generative Replay for Continual Zero-shot Learning
Continual zero-shot learning(CZSL) is a new domain to classify objects sequentially the model has not seen during training.
Adversarial Training of Variational Auto-encoders for Continual Zero-shot Learning(A-CZSL)
We propose a continual zero-shot learning model(A-CZSL) that is more suitable in real-case scenarios to address the issue that can learn sequentially and distinguish classes the model has not seen during training.
STEFANN: Scene Text Editor using Font Adaptive Neural Network
In this paper, we propose a method to modify text in an image at character-level.
Effects of Degradations on Deep Neural Network Architectures
Deep convolutional neural networks (CNN) have massively influenced recent advances in large-scale image classification.
Online Stroke and Akshara Recognition GUI in Assamese Language Using Hidden Markov Model
The work describes the development of Online Assamese Stroke & Akshara Recognizer based on a set of language rules.
