Angel Manuel Gomez

Angel Manuel Gomez
University of Granada | UGR · Department of Signal Theory, Telematics and Communications

PhD

About

107
Publications
12,791
Reads
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887
Citations
Citations since 2016
50 Research Items
625 Citations
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2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
Additional affiliations
December 2016 - present
University of Granada
Position
  • Lecturer
October 2010 - February 2011
Griffith University
Position
  • Visiting researcher

Publications

Publications (107)
Article
The identification of the protein fold class is a challenging problem in structural biology. Recent computational methods for fold prediction leverage deep learning techniques to extract protein fold-representative embeddings mainly using evolutionary information in the form of multiple sequence alignment (MSA) as input source. In contrast, protein...
Preprint
Full-text available
The identification of the protein fold class is a challenging problem in structural biology. Recent computational methods for fold prediction leverage deep learning techniques to extract protein fold-representative embeddings mainly using evolutionary information in the form of multiple sequence alignment (MSA) as input source. In contrast, protein...
Article
Full-text available
Background Current state-of-the-art deep learning approaches for protein fold recognition learn protein embeddings that improve prediction performance at the fold level. However, there still exists aperformance gap at the fold level and the (relatively easier) family level, suggesting that it might be possible to learn an embedding space that bette...
Preprint
Full-text available
The COVID-19 pandemic has led to the saturation of public health services worldwide. In this scenario, the early diagnosis of SARS-Cov-2 infections can help to stop or slow the spread of the virus and to manage the demand upon health services. This is especially important when resources are also being stretched by heightened demand linked to other...
Article
This article presents a recursive expectation-maximization algorithm for online multichannel speech enhancement. A deep neural network mask estimator is used to compute the speech presence probability, which is then improved by means of statistical spatial models of the noisy speech and noise signals. The clean speech signal is estimated using beam...
Preprint
Full-text available
This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-acoustic biosignals generated by the human body during speech production to enable communication whenever normal verbal communication is not possible or not desirable. In this review, we focus on the first case and present latest SSI research aimed at prov...
Article
Full-text available
This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-acoustic biosignals generated by the human body during speech production to enable communication whenever normal verbal communication is not possible or not desirable. In this review, we focus on the first case and present latest SSI research aimed at prov...
Article
Full-text available
Motivation: Protein function prediction is a difficult bioinformatics problem. Many recent methods use deep neural networks to learn complex sequence representations and predict function from these. Deep supervised models require a lot of labeled training data which are not available for this task. However, a very large amount of protein sequences...
Article
Full-text available
The identification of a protein fold type from its amino acid sequence provides important insights about the protein 3D structure. In this paper, we propose a deep learning architecture that can process protein residue-level features to address the protein fold recognition task. Our neural network model combines 1D-convolutional layers with gated r...
Preprint
Full-text available
Motivation Protein function prediction is a difficult bioinformatics problem. Many recent methods use deep neural networks to learn complex sequence representations and predict function from these. Deep supervised models require a lot of labeled training data which are not available for this task. However, a very large amount of protein sequences w...
Article
Automatic speaker verification (ASV) systems are exposed to spoofing attacks which may compromise their security. While anti-spoofing techniques have been mainly studied for clean scenarios, it has also been shown that they perform poorly in noisy environments. In this work, we aim at improving the performance of spoofing detection for ASV in clean...
Article
Morales-Artacho, AJ, García-Ramos, A, Pérez-Castilla, A, Padial, P, Gomez, AM, Peinado, AM, Pérez-Córdoba, JL, and Feriche, B. Muscle activation during power-oriented resistance training: continuous vs. cluster set configurations. J Strength Cond Res XX(X): 000-000, 2018-This study examined performance and electromyography (EMG) changes during a po...
Article
Full-text available
This paper deals with speech enhancement in dual-microphone smartphones using beamforming along with postfiltering techniques. The performance of these algorithms relies on a good estimation of the acoustic channel and speech and noise statistics. In this work we present a speech enhancement system that combines the estimation of the relative trans...
Article
Full-text available
This paper proposes a perceptual metric for speech quality evaluation which is suitable, as a loss function, for training deep learning methods. This metric, derived from the perceptual evaluation of the speech quality (PESQ) algorithm, is computed in a per-frame basis and from the power spectra of the reference and processed speech signal. Thus, t...
Article
Full-text available
Many mobile devices now include an extra microphone, frequently placed at their rear, intended to obtain information about the environmental noise for speech de-noising purposes. Although this secondary sensor can be regarded as just another element in a microphone array when performing beamforming, in this paper we show that it can be considered d...
Article
Full-text available
Voice over IP (VoIP) communications are prone to transmission delays and data losses as they are carried out over packet-switched networks which are unable to guarantee real-time packet delivery. Speech codecs used in these channels strongly rely on Packet Loss Concealment (PLC) algorithms, the performance of which can be compromised as frame losse...
Article
Full-text available
This paper describes a technique that generates speech acoustics from articulator movements. Our motivation is to help people who can no longer speak following laryngectomy, a procedure that is carried out tens of thousands of times per year in the Western world. Our method for sensing articulator movement, permanent magnetic articulography, relies...
Conference Paper
Full-text available
En los últimos años las tecnologías TIC se han ido incorporando en los diferentes ámbitos de la enseñanza, desde las pizarras electrónicas para las clases magistrales hasta el uso de tabletas para la visualización de libros docentes en formato electrónico. De hecho, resulta cada vez más frecuente que los docentes empleen sus portátiles para present...
Article
Full-text available
An effective way to increase noise robustness in automatic speech recognition (ASR) systems is feature enhancement based on an analytical distortion model that describes the effects of noise on the speech features. One of such distortion models that has been reported to achieve a good trade-off between accuracy and simplicity is the masking model....
Article
Full-text available
In this paper we carry out a statistical analysis of a multivariate minimum mean square error (MMSE) estimator developed from a nonparametric kernel-based probability density function. This kernel-based MMSE (KMMSE) estimation has been recently proposed by the authors and successfully applied to image and video reconstruction. The statistical analy...
Conference Paper
The performance of many noise-robust automatic speech recognition (ASR) methods, such as vector Taylor series (VTS) feature compensation, heavily depends on an estimation of the noise that contaminates speech. Therefore, providing accurate noise estimates for this kind of methods is crucial as well as a challenge. In this paper we investigate the u...
Conference Paper
The strong interframe dependency present in Code Excited Linear Prediction (CELP) codecs renders the decoder very vulnerable when the Adaptive Codebook (ACB) is desynchronized. Hence, errors affect not only the concealed frame but also all the subsequent frames. In this paper, we have developed a Forward Error Correction (FEC)-based technique which...
Conference Paper
In this paper, we propose an error mitigation scheme which combines two different approaches, a replacement super vector technique which provides replacements to reconstruct both the LPC coefficients and the excitation signal along bursts of lost packets, and a Forward Error Code (FEC) technique in order to minimize the error propagation after the...
Conference Paper
Full-text available
In this paper, a new speech database, the so-called Secu-Voice, is described. This database consists of utterances in Spanish of isolated digits recorded with two different smartphones: a mid-range smart-phone and a high-range one. This database is intended for research on biometrics and secure applications that integrate both automatic speech reco...
Article
Full-text available
One way to improve automatic speech recognition (ASR) performance on the latest mobile devices, which can be employed on a variety of noisy environments, consists of taking advantage of the small microphone arrays embedded in them. Since the performance of the classic beamforming techniques with small microphone arrays is rather limited, specific t...
Article
Full-text available
The importance of packet-based speech transmissions has grown since it offers cheaper and efficient communications. However, frame erasures are a common hurdle in these networks and concealment techniques are necessary to ensure a minimum quality of service. In this paper, we propose a mitigation technique focused on the reconstruction of the linea...
Chapter
Full-text available
This chapter therefore focuses on a key element of NDE systems: a suitable analysis of the captured signals, which may provide useful information to detect, characterize or classify damages. The work developed by the authors on ultrasonic signal processing techniques for testing of composite materials is presented to illustrate the potential of sig...
Article
Full-text available
Most of the algorithms used for information extraction and for processing the amino acid chains that make up proteins treat them as symbolic chains. Fewer algorithms exploit signal processing techniques that require a numerical representation of amino acid chains. However, these algorithms are very powerful for extracting regularities that cannot b...
Conference Paper
Despite their desirable mechanical properties, damage propagation in carbon fiber-reinforced polymers (CFRP) due to manufacturing flaws and continued use may particularly be hard to assess. In this work, damage maps are generated to identify the health state of a CFRP plate from ultrasonic signals obtained under C-Scan mode. This configuration allo...
Article
Full-text available
In this paper we present a new mitigation technique for lost speech frames transmitted over loss-prone packet networks. It is based on an MMSE estimation from the last received frame, which provides replacements not only for the LPC coefficients (envelope) but also for the residual signal (excitation). Although the method is codec-independent, it r...
Article
Full-text available
Latest smartphones often have more than one microphone in order to perform noise reduction. Although research on speech enhancement is already exploiting this new feature, robust speech recognition is not still benefiting from it. In this paper we propose two feature enhancement methods especially developed for the case of a smartphone with a dual-...
Chapter
The inclusion of two or more microphones in smartphones is becoming quite common. These were originally intended to perform noise reduction and few benefit is still being taken from this feature for noise-robust automatic speech recognition (ASR). In this paper we propose a novel system to estimate missing-data masks for robust ASR on dual-micropho...
Conference Paper
This paper presents a recovery scheme for the error-propagation distortion which frequently appears after a frame erasure in CELP-based speech coders, in particular the AMR codec. The extensive use of predictive filters and parameter encoding allow a high-quality speech synthesis in these codecs, but makes them more vulnerable to frame erasures. Th...
Conference Paper
Signal processing has been proven to be an useful tool to characterize damaged materials under ultrasonic nondestructive evaluation. In this work, we hypothesize that the transfer function of multilayered materials for a through-transmission configuration can be represented as a classical all-pole model with sparse coefficients. To test this hypoth...
Article
Full-text available
We propose a speech enhancement-by-resynthesis framework whose strength lies in a common statistical speech model that is shared by the analysis and synthesis stages. First, a spectro-temporal analysis is performed and masked spectro-temporal regions are identified using a noise model. Then, HMM synthesis is used to reconstruct the spectral envelop...