Cart
Create Account
Sign In
Showing 301 - 350 of 1951
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Cross-Speaker Silent-Speech Command Word Recognition Using Electro-Optical Stomatography
Speech recognition based on articulatory movements instead of the acoustic signal is of growing interest in the community. In this work, we present the results of a study using a novel measurement technology called Electro-Optical Stomatography to capture
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Learning Semi-Supervised Anonymized Representations By Mutual Information
This paper addresses the problem of removing from a set of data (here images) a given private information, while still allowing other utilities on the processed data. This is obtained by training concurrently a GAN-like discriminator and an autoencoder. T
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Decoding 5G-Nr Communications Via Deep Learning
Upcoming modern communications are based on 5G specifications and aim at providing solutions for novel vertical industries. One of the major changes of the physical layer is the use of Low-Density Parity-Check (LDPC) code for channel coding. Although LDPC
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Teaching Signals And Systems - A First Course In Signal Processing
Signals and systems is a well known fundamental course in signal processing. How this course is taught to a student can spell the difference between whether s/he pursues a career in this field or not. Giving due consideration to this matter, this paper re
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Looking Enhances Listening: Recovering Missing Speech Using Images
Speech is understood better by using visual context; for this reason, there have been many attempts to use images to adapt automatic speech recognition (ASR) systems. Current work, however, has shown that visually adapted ASR models only use images as a r
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Hierarchical Model For Dialog Act Recognition Considering Acoustic And Lexical Context Information
Dialog act recognition (DAR) is important to capture speakers' intention in a dialog system. Traditional methods commonly use the lexical information from transcripts, acoustic information from speech, and dialog context information to do DAR. However, in
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Low-Complexity Map Detector For Distributed Networks
This work describes a generalization of our previous maximum likelihood (ML) detector to a maximum a posteriori (MAP) detector in distributed networks using the diffusion LMS algorithm. Nodes in the network must decide between two concurrent hypotheses co
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Non-Parametric Community Change-Points Detection In Streaming Graph Signals
Detecting changes in network-structured time series data is of utmost importance in critical applications as diverse as detecting denial of service attacks against online service providers or monitoring energy and water supplies. The aim of this paper is
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Detect Insider Attacks Using Cnn In Decentralized Optimization
This paper studies the security issue of a gossip-based distributed projected gradient (DPG) algorithm, when it is applied for solving a decentralized multi-agent optimization. It is known that the gossip-based DPG algorithm is vulnerable to insider attac
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
What Is Best For Spoken Language Understanding: Small But Task-Dependant Embeddings Or Huge But Out-Of-Domain Embeddings?
Word embeddings are shown to be a great asset for several Natural Language and Speech Processing tasks. While they are already evaluated on various NLP tasks, their evaluation on spoken or natural language understanding (SLU) is less studied. The goal of
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Robust Hybrid Precoding For Interference Exploitation In Massive Mimo Systems
In this paper, we consider a multiuser massive MIMO system with hybrid analog-digital precoding architecture. The phase shifters in the hybrid precoding architecture are assumed to be imperfect, where the true values of both phase and magnitude of the pha
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Estimating Centrality Blindly From Low-Pass Filtered Graph Signals
This paper considers blind methods for centrality estimation from graph signals. We model graph signals as the outcome of an unknown low-pass graph filter excited with influences governed by a sparse sub-graph. This model is compatible with a number of da
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Opportunistic Use Of Gnss Signals To Characterize The Environment By Means Of Machine Learning Based Processing
GNSS is widely used to provide positions in an absolute reference frame in Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), where GNSS is merged with the information provided by other sensors. Even if the main goal of GNSS signal process
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Human-Machine Collaboration For Medical Image Segmentation
Image segmentation is a ubiquitous step in almost any medical image study. Deep learning-based approaches achieve state-of-the-art in the majority of image segmentation benchmarks. However, end-to-end training of such models requires sufficient annotation
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Data-Driven Wind Speed Estimation Using Multiple Microphones
A deep neural network (DNN) based approach for estimating the speed of airflows using closely-spaced microphones is proposed. The spatial characteristics of wind noise measured with a small-aperture array are exploited, i.e., the low-frequency spatial coh
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Unsupervised Pretraining Transfers Well Across Languages
Cross-lingual and multi-lingual training of Automatic Speech Recognition (ASR) has been extensively investigated in the supervised setting. This assumes the existence of a parallel corpus of speech and orthographic transcriptions. Recently, contrastive pr
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Object Surface Estimation From Radar Images
In this paper we develop a deep neural network (DNN) method for estimating the object surface from radar 2D image (azimuth-range). The DNN is designed to maintain the input image angular resolution and produces two outputs per each angle, which are a clas
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Inverse Multiple Scattering With Phaseless Measurements
We study the problem of reconstructing an object from phaseless measurements in the context of inverse multiple scattering. Our formulation explicitly decouples the variables that represent the unknown object image and the unknown phase, respectively, in
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Accuracy-Robustness Trade-Off For Positively Weighted Neural Networks
This work proposes a new learning strategy for training a feedforward neural network subject to spectral norm and nonnegativity constraints. Our primary goal is to control the Lipschitz constant of the network in order to make it robust against adversaria
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
Despite the ability to produce human-level speech for in-domain text, attention-based end-to-end text-to-speech (TTS) systems suffer from text alignment failures that increase in frequency for out-of-domain text. We show that these failures can be address
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Building Firmly Nonexpansive Convolutional Neural Networks
Building nonexpansive Convolutional Neural Networks (CNNs) is a challenging problem that has recently gained a lot of attention from the image processing community. In particular, it appears to be the key to obtain convergent Plug-and-Play algorithms. Thi
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Autoregressive Parameter Estimation With Dnn-Based Pre-Processing
In this paper, a method for estimating the autoregressive parameters from a signal segment is proposed. The method is based on a deep neural network (DNN) in combination with the classical Levinson-Durbin recursion (LDR). The DNN acts as a pre-processor f
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Variable Projection For Multiple Frequency Estimation
The estimation of the frequencies of multiple complex sinusoids in the presence of noise is required in many applications such as sonar, speech processing, communications, and power systems. According to previous works [1,2], this problem can be reformula
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Mixup Multi-Attention Multi-Tasking Model For Early-Stage Leukemia Identification
Recently, several image processing and deep learning techniques have been applied to automate the detection of Acute Lymphoblastic Leukemia cells (ALL). However, most of them have consistently focused on classification mature stage cell images into binary
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Effectiveness Of Self-Supervised Pre-Training For Asr
We compare self-supervised representation learning algorithms which either explicitly quantize the audio data or learn representations without quantization. We find the former to be more accurate since it builds a good vocabulary of the data through vq-wa
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Lstm-Based One-Pass Decoder For Low-Latency Streaming
Current state-of-the-art models based on Long-Short Term Memory (LSTM) networks have been extensively used in automatic speech recognition (ASR) to improve the performance of these systems. However, using them under a streaming setup is not straightforwar
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Towards An Intelligent Microscope: Adaptively Learned Illumination For Optimal Sample Classification
Recent machine learning techniques have dramatically changed how we process digital images. However, the way in which we capture images is still largely driven by human intuition and experience. This restriction is in part due to the many available degree
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Cochlear Signal Processing: A Platform For Learning The Fundamentals Of Digital Signal Processing
The first digital signal processing course in most electrical engineering programmes around the world tends to be a significant jump in abstraction for most students. This is a consequence of them being introduced to a large number of mathematical concept
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
The Graphon Fourier Transform
In many network problems, graphs may change by the addition of nodes, or the same problem may need to be solved in multiple similar graphs. This generates inefficiency, as analyses and systems that are not transferable have to be redesigned. To address th
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Gradient Delay Analysis In Asynchronous Distributed Optimization
Gradient-based algorithms play an important role in solving a wide range of stochastic optimization problems. In recent years, implementing such schemes in parallel has become the new paradigm. In this work, we focus on the asynchronous implementation of
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Data-Driven Harmonic Filters For Audio Representation Learning
We introduce a trainable front-end module for audio representation learning that exploits the inherent harmonic structure of audio signals. The proposed architecture, composed of a set of filters, compels the subsequent network to capture harmonic relatio
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
A Priori Estimates Of The Generalization Error For Autoencoders
Autoencoder is a machine learning model which aims for dimensionality reduction, by reconstructing its input through a bottleneck with lower dimension than the input. It is among the most popular models used in unsupervised learning and semi-supervised le
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
One-Bit Sampling In Fractional Fourier Domain
The fractional Fourier transform has found applications in a variety of topics linked with science and engineering. In this context, sampling theory is one of the most well-studied subjects. Since the fractional Fourier transform or the FrFT generalizes t
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Deep Joint Source-Channel Coding Of Images With Feedback
We consider wireless transmission of images in the presence of channel output feedback, by introducing an autoencoder-based deep joint source-channel coding (JSCC) scheme. We achieve impressive results in terms of the end-to-end reconstruction quality for
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Image Processing In Dna
The main obstacles for the practical deployment of DNA-based data storage platforms are the prohibitively high cost of synthetic DNA and the large number of errors introduced during synthesis. In particular, synthetic DNA products contain both individual
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
An Adaptive Linear Estimator Based Approach To Bi-Directional Motion Compensated Prediction
Bi-directional motion compensated prediction is widely utilized in video coding. Conventionally, the encoder searches for two motion vectors pointing to reference frames in both directions, and transmits these motion vectors to the decoder. Recognizing th
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Channel Attention Based Generative Network For Robust Visual Tracking
In recent years, Siamese trackers have achieved great success in visual tracking. Siamese networks can achieve competitive performance in both accuracy and speed. However, they may suffer from the performance degradation due to the case of large pose vari
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Pevd-Based Speech Enhancement In Reverberant Environments
The enhancement of noisy speech is important for applications involving human-to-human interactions, such as telecommunications and hearing aids, as well as human-to-machine interactions, such as voice-controlled systems and robot audition. In this work,
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Coupled Training Of Sequence-To-Sequence Models For Accented Speech Recognition
Accented speech poses significant challenges for state-of-the-art automatic speech recognition (ASR) systems. Accent is a property of speech that lasts throughout an utterance in varying degrees of strength. This makes it hard to isolate the influence of
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Learning From Dances: Pose-Invariant Re-Identification For Multi-Person Tracking
Most existing multi-person tracking approaches rely on appearance based re-identification (re-ID) to resolve the fragmented tracklets. However, simply using appearance information could be insufficient for videos containing severe pose changes, such as sp
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Federated Classification With Low Complexity Reproducing Kernel Hilbert Space Representations
In federated learning, a centralized model is realized based on information received from a group of agents each collecting data. This setting has two major challenges: the agents observe data over different distributions and they have only limited capabi
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Dynamic Attack Scoring Using Distributed Local Detectors
Nowadays, continuously operating critical services increasingly rely on complex cyber-physical systems, which are also known as high-profile targets of cyberattacks, potentially resulting in security breaches that can cause severe damage. This paper prese
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
F0-Consistent Many-To-Many Non-Parallel Voice Conversion Via Conditional Autoencoder
Non-parallel many-to-many voice conversion remains an interesting but challenging speech processing task. Many style-transfer-inspired methods such as generative adversarial networks (GANs) and variational autoencoders (VAEs) has been proposed. Recently,
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sequence-To-Sequence Automatic Speech Recognition With Word Embedding Regularization And Fused Decoding
In this paper, we investigate the benefit that off-the-shelf word embedding can bring to the sequence-to-sequence (seq-to-seq) automatic speech recognition (ASR). We first introduced the word embedding regularization by maximizing the cosine similarity be
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Gated Attentive Convolutional Network Dialogue State Tracker
In task-oriented dialogue systems, dialogue state tracking (DST) is an essential part which aims to estimate user goal at every step of the dialogue. At each turn, DST aims to estimate user goals by current user utterance and last system action. However,
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Kernel Computations From Large-Scale Random Features Obtained By Optical Processing Units
Approximating kernel functions with random features (RFs) has been a successful application of random projections for nonparametric estimation. However, performing random projections presents computational challenges for large-scale problems. Recently, a
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sound Event Localization Based On Sound Intensity Vector Refined By Dnn-Based Denoising And Source Separation
We propose a direction-of-arrival (DOA) estimation method for Sound Event Localization and Detection (SELD). Direct estimation of DOA using a deep neural network (DNN), i.e. completely-data-driven approach, achieves high accuracy. However, there is a gap
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Sight To Sound: An End-To-End Approach For Visual Piano Transcription
Automatic music transcription has primarily focused on transcribing audio to a symbolic music representation (e.g. MIDI or sheet music). However, audio-only approaches often struggle with polyphonic instruments and background noise. In contrast, visual in