Cart
Create Account
Sign In
Showing 1 - 50 of 1951
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Adaptive Normalization For Forecasting Limit Order Book Data Using Convolutional Neural Networks
Deep learning models are capable of achieving state-of-the-art performance on a wide range of time series analysis tasks. However, their performance crucially depends on the employed normalization scheme, while they are usually unable to efficiently handl
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Image Super-Resolution Using Residual Global Context Network
Recent studies have showed that convolutional neural networks (CNN) can effectively improve the performance of single image super-resolution (SR). However, previous methods rarely considered long-range dependencies between pixels and channel-wise interdep
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Gated Hypernet Decoder For Polar Codes
Hypernetworks were recently shown to improve the performance of message passing algorithms for decoding error correcting codes. In this work, we demonstrate how hypernetworks can be applied to decode polar codes by employing a new formalization of the pol
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
We propose a straightforward and cost-effective method to perform diffuse soundfield measurements for calibrating the magnitude response of a microphone array. Typically, such calibration is performed in a diffuse soundfield created in reverberation chamb
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Shape From Bandwidth: Central Projection Case
Consider an unknown surface painted with a band-limited texture. We show that only the knowledge of the bandwidth of the texture is enough to estimate the shape of the surface from a single image taken by a camera. We model the problem as a central projec
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Siamese Content-Attentive Graph Convolutional Network For Personality Recognition Using Physiology
Affective multimedia content has long been used as stimulation to study an individual's personality using physiology. In this work, we propose a novel Siamese Content-Attentive Graph Convolutional Network (SCA-GCN) to learn a discriminative physiology rep
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Deep Matrix Completion On Graphs: Application In Drug Target Interaction Prediction
This work proposes matrix completion via deep matrix factorization on graphs. The work is motivated by the success of two very recent studies on (shallow) matrix completion on graphs and deep matrix factorization (without graphs). We show that the propose
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Adaptive Sequential Interpolator Using Active Learning For Efficient Emulation Of Complex Systems
Many fields of science and engineering require the use of complex and computationally expensive models to understand the involved processes in the system of interest. Nevertheless, due to the high cost involved, the required study becomes a cumbersome pro
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
An Improved Deep Neural Network For Modeling Speaker Characteristics At Different Temporal Scales
This paper presents an improved deep embedding learning method based on a convolutional neural network (CNN) for text-independent speaker verification. Two improvements are proposed for x-vector embedding learning: (1) a multiscale convolution (MSCNN) is
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Batman: Bayesian Target Modelling For Active Inference
Active Inference is an emerging framework for designing intelligent agents. In an Active Inference setting, any task is formulated as a variational free energy minimisation problem on a generative probabilistic model. Goal-directed behaviour relies on a c
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Focusing On Attention: Prosody Transfer And Adaptative Optimization Strategy For Multi-Speaker End-To-End Speech Synthesis
End-to-end speech synthesis can generate high-quality synthetic speech and achieve high similarity scores with low-resource adaptation data. However, the generalization of out-domain texts is still a challenging task. The limited adaptation data leads to
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
An Efficient Alternative To Network Pruning Through Ensemble Learning
Convolutional Neural Networks (CNNs) currently represent the best tool for classification of image content. CNNs are trained in order to develop generalized expressions in form of unique features to distinguish different classes. During this process, one
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Semanticgan: Generative Adversarial Networks For Semantic Image To Photo-Realistic Image Translation
Generative Adversarial Networks (GANs) have shown remarkable success in Semantic label map to Photo-realistic image Translation (S2PT) task. However, the results of the state-of-the-art approaches are often limited to blurriness and artifacts, and still f
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Graph Regularized Tensor Train Decomposition
With the advances in data acquisition technology, tensor objects are collected in a variety of applications including multimedia, medical and hyperspectral imaging. As the dimensionality of tensor objects is usually very high, dimensionality reduction is
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Determined Source Separation Using The Sparsity Of Impulse Responses
In this paper, we propose an over-determined sound source separation method considering the sparsity of impulse responses. Conventional methods, including independent low-rank matrix analysis (ILRMA), have mainly focused on design of realistic sound gener
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Noise-Robust Key-Phrase Detectors For Automated Classroom Feedback
With the goal of giving teachers automated feedback about their classrooms, we investigate how to train automatic speech detectors of key phrases such as good job, thank you, please, and you're welcome. This kind of language conveys support and respect fr
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Learning To Separate Sounds From Weakly Labeled Scenes
Deep learning models for monaural audio source separation are typically trained on large collections of isolated sources, which may not be available in domains such as environmental monitoring. We propose objective functions and network architectures that
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Optimizing Bayesian Hmm Based X-Vector Clustering For The Second Dihard Speech Diarization Challenge
This paper presents an analysis of our diarization system winning the second DIHARD speech diarization challenge, track 1. This system is based on clustering x-vector speaker embeddings extracted every 0.25s from short segments of the input recording. In
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Exocentric To Egocentric Image Generation Via Parallel Generative Adversarial Network
Cross-view image generation has been recently proposed to generate images of one view from another dramatically different view. In this paper we investigate exocentric (third-person) view to egocentric (first-person) view image generation. This is a chall
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Whosecough: In-The-Wild Cougher Verification Using Multitask Learning
Current automatic cough counting systems can determine how many coughs are present in an audio recording. However, they cannot determine who produced the cough. This limits their usefulness as most systems are deployed in locations with multiple people (i
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Exact Sparse Nonnegative Least Squares
We propose a novel approach to solve exactly the sparse nonnegative least squares problem, under hard l0 sparsity constraints. This approach is based on a dedicated branch-and-bound algorithm. This simple strategy is able to compute the optimal solution e
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Converting Written Language To Spoken Language With Neural Machine Translation For Language Modeling
When building a language model (LM) for spontaneous speech, the ideal situation is to have a large amount of spoken, in-domain training data. Having such abundant data, however, is not realistic. We address this problem by generating texts in spoken langu
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Exploring Appropriate Acoustic And Language Modelling Choices For Continuous Dysarthric Speech Recognition
There has been much recent interest in building continuous speech recognition systems for people with severe speech impairments, e.g., dysarthria. However, the datasets that are commonly used are typically designed for tasks other than ASR development, or
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Semi-Supervised Rank Tracking Algorithm For On-Line Unmixing Of Hyperspectral Images
This paper addresses the problem of rank tracking in real time hyperspectral image unmixing methods. Based on the On-line Alternating Direction Method of Multipliers (ADMM), we propose a new hyperspectral unmixing approach that integrates prior informatio
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Compressive Adaptive Bilateral Filtering
We propose a fast algorithm for an adaptive variant of the classical bilateral filter, where the range kernel is allowed to vary from pixel to pixel. Several fast and accurate algorithms have been proposed for bilateral filtering, but they assume that the
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Clock Synchronization Over Networks Using Sawtooth Models
Clock synchronization and ranging over a wireless network with low communication overhead is a challenging goal with tremendous impact. In this paper, we study the use of time-to-digital converters in wireless sensors, which provides clock synchronization
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Generating Empathetic Responses By Looking Ahead The User’S Sentiment
An important aspect of human conversation difficult for machines is conversing with empathy, which is to understand the user's emotion and respond appropriately. Recent neural conversation models that attempted to generate empathetic responses either focu
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Robust Pricing Mechanism For Resource Sustainability Under Privacy Constraint In Competitive Online Learning Multi-Agent Systems
We consider the problem of resource congestion control for competing online learning agents under privacy and security constraints. Based on the non-cooperative game as the model for agents' interaction and the noisy online mirror ascent as the model for
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Time Reversal Based Robust Gesture Recognition Using Wifi
Gesture recognition using wireless sensing opened a plethora of applications in the field of human-computer interaction. However, most existing works are not robust without requiring wearables or tedious training/calibration. In this work, we propose WiGR
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Improving Prosody With Linguistic And Bert Derived Features In Multi-Speaker Based Mandarin Chinese Neural Tts
Recent advances of neural TTS have made ?human parity? synthesized speech possible when a large amount of studio-quality training data from a voice talent is available. However, with only limited, casual recordings from an ordinary speaker, human-like TTS
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
On Regularization Parameter For L0-Sparse Covariance Fitting Based Doa Estimation
In sparse DOA estimation methods, the regularization parameter is generally empirically tuned. In this paper, we provide a statistical method allowing to estimate an admissible interval where it must be chosen. This work is conducted in the case of an Uni
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Optimal Transport Based Change Point Detection And Time Series Segment Clustering
Two common problems in time series analysis are the decomposition of the data stream into disjoint segments, each of which is in some sense ?homogeneous? - a problem that is also referred to as Change Point Detection (CPD) - and the grouping of similar no
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Using Intelligent Reflecting Surfaces For Rank Improvement In Mimo Communications
An intelligent reflecting surface (IRS), consisting of reconfigurable metamaterials, can be used to partially control the radio environment and thereby bring new features to wireless communications. Previous works on IRS have particularly studied the rang
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Retinal Vessel Segmentation Via A Semantics And Multi-Scale Aggregation Network
Precise segmentation of retinal vessels is crucial for a computer-aided diagnosis system of retinal fundus images. However, this task remains challenging due to large variations in scales and poor segmentation of capillary vessels. In this paper, we propo
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Constrained Spectral Clustering For Dynamic Community Detection
Networks are useful representations of many systems with interacting entities, such as social, biological and physical systems. Characterizing the meso-scale organization, i.e. the community structure, is an important problem in network science. Community
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sound Texture Synthesis Using Ri Spectrograms
This article introduces a new parametric synthesis method for sound textures based on existing works in visual and sound texture synthesis. Starting from a base sound signal, an optimization process is performed until the cross-correlations between the fe
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Fully Pipelined Iteration Unrolled Decoders The Road To Tb/S Turbo Decoding
Turbo codes are a well-known code class used for example in the LTE mobile communications standard. They provide built-in rate flexibility and a low-complexity and fast encoding. However, the serial nature of their decoding algorithm makes high-throughput
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Learning To Detect Keyword Parts And Whole By Smoothed Max Pooling
We propose smoothed max pooling loss and its application to keyword spotting systems. The proposed approach jointly trains an encoder (to detect keyword parts) and a decoder (to detect whole keyword) in a semi-supervised manner. The proposed new loss func
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Joint Coding And Modulation In The Ultra-Short Blocklength Regime For Bernoulli-Gaussian Impulsive Noise Channels Using Autoencoders
This paper develops a joint coding and modulation scheme for end-to-end communication system design using an autoencoder architecture in the ultra-short blocklength regime. Unlike the classical approach of separately designing error correction codes and m
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Leveraging Unpaired Text Data For Training End-To-End Speech-To-Intent Systems
Training an end-to-end (E2E) neural network speech-to-intent (S2I) system that directly extracts intents from speech requires large amounts of intent-labeled speech data, which is time consuming and expensive to collect. Initializing the S2I model with an
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Active Learning With Unsupervised Ensembles Of Classifiers
The present work introduces a simple scheme for active classification of data using unsupervised ensembles of classifiers. Uncertainty sampling, with different uncertainty measures, is evaluated for data selection, while an online expectation maximization
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Maximum Likelihood Multi-Speaker Direction Of Arrival Estimation Utilizing A Weighted Histogram
In this contribution, a novel maximum likelihood (ML) based direction of arrival (DOA) estimator for concurrent speakers in a noisy reverberant environment is presented. The DOA estimation task is formulated in the short-time Fourier transform (STFT) in t
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Optimal Joint Channel Estimation And Data Detection By L1-Norm Pca For Streetscape Iot
We prove, for the first time in the literature of communication theory and machine learning, the equivalence of joint maximum-likelihood (ML) optimal channel estimation and data detection (JOCEDD) to the problem of finding the $L_1$-norm principal compone
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Quickest Detection Of Growing Dynamic Anomalies In Networks
The problem of quickest growing dynamic anomaly detection in sensor networks is studied. Initially, the observations at the sensors, which are sampled sequentially by the decision maker, are generated according to a pre-change distribution. At some unknow
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Mt-Gcn For Multi-Label Audio Tagging With Noisy Labels
Multi-label audio tagging is the task of predicting the types of sounds occurring in an audio clip. Recently, large-scale audio datasets such as Google's AudioSet, have allowed researchers to use deep learning techniques for this task but this comes at th
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Small-Footprint Keyword Spotting On Raw Audio Data With Sinc-Convolutions
Keyword Spotting (KWS) enables speech-based user interaction on smart devices. Always-on and battery-powered application scenarios for smart devices put constraints on hardware resources and power consumption, while also demanding high accuracy as well as
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Far-Field Location Guided Target Speech Extraction Using End-To-End Speech Recognition Objectives
Target speech extraction is a specific case of source separation where an auxiliary information like the location or some pre-saved anchor speech examples of the target speaker is used to resolve the permutation ambiguity. Traditionally such systems are o
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Single-Rf Architecture For Multiuser Massive Mimo Via Reflecting Surfaces
In this work, we propose a new single-RF MIMO architecture which enjoys high scalability and energy-efficiency. The transmitter in this proposal consists of a single RF illuminator radiating towards a reflecting surface. Each element on the reflecting sur