Search results for: Yannis Stylianou

Items from 1 to 20 out of 62 results

article

A study of time-frequency features for CNN-based automatic heart sound classification for pathology detection

Baris Bozkurt, Ioannis Germanakis, Yannis Stylianou

Computers in Biology and Medicine > 2018 > 100 > C > 132-143

This study concerns the task of automatic structural heart abnormality risk detection from digital phonocardiogram (PCG) signals aiming at pediatric heart disease screening applications. Recently, various systems based on convolutional neural networks trained on time-frequency representations of segmental PCG frames have been presented that outperform systems using hand-crafted features. This study...

chapter

Expressive visual text to speech and expression adaptation using deep neural networks

Jonathan Parker, Ranniery Maia, Yannis Stylianou, Roberto Cipolla

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 4920 - 4924

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

In this paper, we present an expressive visual text to speech system (VTTS) based on a deep neural network (DNN). Given an input text sentence and a set of expression tags, the VTTS is able to produce not only the audio speech, but also the accompanying facial movements. The expressions can either be one of the expressions in the training corpus or a blend of expressions from the training corpus....

chapter

Effective emotion recognition in movie audio tracks

Margarita Kotti, Yannis Stylianou

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 5120 - 5124

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

This paper addresses the problem of speech emotion recognition from movie audio tracks. The recently collected Acted Facial Expression in the Wild 5.0 database is used. The aim is to discriminate among angry, happy, and neutral. We extract a relatively small number of features, a subset of which is not commonly used for the emotion recognition task. Those features are fed as input to an ensemble classifier...

chapter

Adaptive gain control and time warp for enhanced speech intelligibility under reverberation

Petko N. Petkov, Yannis Stylianou

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 691 - 695

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Moderate and severe reverberation reduce speech intelligibility as a result of the overlap-masking effect, which constitutes the simultaneous observation of multiple delayed and attenuated copies of the speech signal. Recent progress has been made in ameliorating the degradation in intelligibility by adaptively controlling the signal gain as a function of both the signal statistics and the properties...

chapter

Predicting dialogue success, naturalness, and length with acoustic features

Alexandros Papangelis, Margarita Kotti, Yannis Stylianou

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 5010 - 5014

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Statistical methods for Spoken Dialogue Systems have been shown to reduce the cost of development, while successfully handling a variety of applications. However, such systems are usually trained with simulated users or paid subjects in controlled settings. While this may be sufficient to jump-start learning in the various sub-components, learning is very much dependent on the complete knowledge that...

chapter

Modeling Speech Based on Harmonic Plus Noise Models

Yannis Stylianou

Lecture Notes in Computer Science > Nonlinear Speech Modeling and Applications > Data Driven and Speech Processing Algorithms > 244-260

Hybrid models of speech have received increasing interest from the speech processing community. Splitting the speech signal into a periodic and a non-periodic part increases the quality of prosodic modifications necessary in concatenative speech synthesis systems. This paper focuses on the decomposition of the speech signal into a periodic and a non-periodic part based on a Harmonic plus Noise Model,...

article

Adaptive Gain Control for Enhanced Speech Intelligibility Under Reverberation

Petko N. Petkov, Yannis Stylianou

IEEE Signal Processing Letters > 2016 > 23 > 10 > 1434 - 1438

Overlap-masking reduces speech intelligibility in reverberant environments. In contrast to additive noise, the masking signal depends on the past of the speech signal. An increase in output signal power is followed by an increase in reverberation power. Taking into consideration, the mechanics of reverberation is essential for the development of speech modifications that effectively increase intelligibility...

article

Near and Far Field Speech-in-Noise Intelligibility Improvements Based on a Time–Frequency Energy Reallocation Approach

Tudor-Catalin Zorila, Yannis Stylianou, Tatsuma Ishihara, Masami Akamine

IEEE/ACM Transactions on Audio, Speech, and Language Processing > 2016 > 24 > 10 > 1808 - 1818

An algorithm designed to enhance the intelligibility of speech signals before they are presented in noisy environments was evaluated. The processed and unprocessed speech had the same root-mean square level. Spectral energy was redistributed to increase the signal-to-noise ratio (SNR) in the mid- and high-frequency bands, while the softer segments of speech were increased in level by applying time-domain...

chapter

Bird detection in audio: A survey and a challenge

Dan Stowell, Mike Wood, Yannis Stylianou, Herve Glotin

2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP) > 1 - 6

2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)

Many biological monitoring projects rely on acoustic detection of birds. Despite increasingly large datasets, this detection is often manual or semi-automatic, requiring manual tuning/postprocessing. We review the state of the art in automatic bird sound detection, and identify a widespread need for tuning-free and species-agnostic approaches. We introduce new datasets and an IEEE research challenge...

article

Global Variance in Speech Synthesis With Linear Dynamical Models

Vassilis Tsiaras, Ranniery Maia, Vassilis Diakoloukas, Yannis Stylianou, more

IEEE Signal Processing Letters > 2016 > 23 > 8 > 1057 - 1061

Linear Dynamical Models (LDMs) have been used in speech synthesis recently as an alternative to hidden Markov models (HMMs). Among the advantages of LDMs are the ability to capture the dynamics of speech and the achievement of synthesized speech quality similar to HMM-based speech systems on a smaller footprint. However, such as in the HMM case, LDMs produce over-smoothed trajectories of speech parameters,...

article

Advances in phase-aware signal processing in speech communication

Pejman Mowlaee, Rahim Saeidi, Yannis Stylianou

Speech Communication > 2016 > 81 > C > 1-29

During the past three decades, the issue of processing spectral phase has been largely neglected in speech applications. There is no doubt that the interest of speech processing community towards the use of phase information in a big spectrum of speech technologies, from automatic speech and speaker recognition to speech synthesis, from speech enhancement and source separation to speech coding, is...

chapter

Extraction of Speech-Relevant Information from Modulation Spectrograms

Maria Markaki, Michael Wohlmayer, Yannis Stylianou

Lecture Notes in Computer Science > Progress in Nonlinear Speech Processing > 78-88

In this work, we adopt an information theoretic approach - the Information Bottleneck method to extract the relevant modulation frequencies across both dimensions of a spectrogram, for speech / non-speech discrimination (music, animal vocalizations, environmental noises). A compact representation is built for each sound ensemble, consisting of the maximally informative features. We demonstrate the...

chapter

Nonlinear Speech Features for the Objective Detection of Discontinuities in Concatenative Speech Synthesis

Yannis Pantazis, Yannis Stylianou

Lecture Notes in Computer Science > Nonlinear Speech Modeling and Applications > Task Oriented Speech Applications > 375-383

abstr An objective distance measure which is able to predict audible discontinuities in concatenative speech synthesis systems is very important. Previous results showed that linear approaches are not very effective to detect audible discontinuities. The best result was obtained by using the Kullback-Leibler distance on power spectra with the rate of 37%. In this paper, we present two nonlinear approaches...

chapter

Biometrics: Different Approaches for Using Gaussian Mixture Models in Handwriting

Sascha Schimke, Athanasios Valsamakis, Claus Vielhauer, Yannis Stylianou

Lecture Notes in Computer Science > Communications and Multimedia Security > Work in Progress Track > 261-263

In this work in progress paper we discuss an established as well as a new approache to the use of Gaussian Mixture Models (GMMs) for handwriting biometrics. The technique of GMMs is well explored for the domain of speech processing and we evaluate ways to use them for handwriting biometrics, too.

chapter

On the Detection of Discontinuities in Concatenative Speech Synthesis

Yannis Pantazis, Yannis Stylianou

Lecture Notes in Computer Science > Progress in Nonlinear Speech Processing > 89-100

Last decade considerable work has been done in finding an objective distance measure which is able to predict audible discontinuities in concatenative speech synthesis. Speech segments in concatenative synthesis are extracted from disjoint phonetic contexts and discontinuities in spectral shape and phase mismatches tend to occur at unit boundaries. Many feature sets most of them of spectral nature...

book

Progress in Nonlinear Speech Processing

Yannis Stylianou, Marcos Faundez-Zanuy, Anna Esposito

Lecture Notes in Computer Science

chapter

Iterative estimation of phase using complex cepstrum representation

Ranniery Maia, Yannis Stylianou

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 4990 - 4994

ICASSP 2016 - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

This paper presents a method to iteratively estimate phase information from speech in the cepstrum domain. It assumes that correct markings of pitch periods, which may not correspond to glottal closure instants (GCI), are available and can be used to extract the smooth spectral envelope of speech. By using this information, the minimum-phase cepstrum is derived and used as prior information in a modified...

chapter

High-resolution sinusoidal modeling of unvoiced speech

George P. Kafentzis, Yannis Stylianou

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 4985 - 4989

ICASSP 2016 - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

In this paper, a recently proposed high-resolution Sinusoidal Model, dubbed the extended adaptive Quasi-Harmonic Model (eaQHM), is applied on modeling unvoiced speech sounds. Unvoiced speech sounds are parts of speech that are highly non-stationary in the time-frequency plane. Standard sinusoidal models fail to model them accurately and efficiently, thus introducing artefacts, while the reconstructed...

chapter

Initial investigation of speech synthesis based on complex-valued neural networks

Qiong Hu, Junichi Yamagishi, Korin Richmond, Kartick Subramanian, more

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 5630 - 5634

ICASSP 2016 - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Although frequency analysis often leads us to a speech signal in the complex domain, the acoustic models we frequently use are designed for real-valued data. Phase is usually ignored or modelled separately from spectral amplitude. Here, we propose a complex-valued neural network (CVNN) for directly modelling the results of the frequency analysis in the complex domain (such as the complex amplitude)...

chapter

Multi-stream spectral representation for statistical parametric speech synthesis

Kayoko Yanagisawa, Ranniery Maia, Yannis Stylianou

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) > 5160 - 5164

ICASSP 2016 - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

In statistical parametric speech synthesis such as Hidden Markov Model (HMM) based synthesis, one of the problems is in the over-smoothing of parameters, which leads to a muffled sensation in the synthesised output. In this paper, we propose an approach in which the high frequency spectrum is modelled separately from the low frequency spectrum. The high frequency band, which does not carry much linguistic...

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SPEECH (21)
SPEECH ANALYSIS (15)
SPEECH SYNTHESIS (10)
SPEECH PROCESSING (9)
HIDDEN MARKOV MODELS (8)
ESTIMATION (7)
FREQUENCY ESTIMATION (7)
HARMONIC ANALYSIS (7)
ACOUSTICS (5)
SIGNAL TO NOISE RATIO (5)
SPEECH INTELLIGIBILITY (5)
ADAPTIVE QUASI-HARMONIC MODEL (4)
FEATURE EXTRACTION (4)
FREQUENCY MODULATION (4)
ROBUSTNESS (4)
SINUSOIDAL MODEL (4)
SPEECH ENHANCEMENT (4)
ADAPTATION MODELS (3)
EXTENDED ADAPTIVE QUASI-HARMONIC MODEL (3)
MATHEMATICAL MODEL (3)
NOISE (3)
SPEECH CODING (3)
SPEECH MODIFICATION (3)
STATISTICAL PARAMETRIC SPEECH SYNTHESIS (3)
TIME FREQUENCY ANALYSIS (3)
TRAINING (3)
ADAPTIVE HARMONIC MODEL (2)
AMPLITUDE ESTIMATION (2)
ANALYTICAL MODELS (2)
AUTOMATIC SPEECH RECOGNITION (2)
CLEAR SPEECH (2)
CORRELATION (2)
DATABASES (2)
DISTORTION (2)
DISTORTION MEASUREMENT (2)
HARMONIC MODEL (2)
HIGH-PITCHED (2)
HIGHER ORDER SINGULAR VALUE DECOMPOSITION (2)
HMM-BASED SPEECH SYNTHESIS (2)
IEEE TRANSACTIONS (2)
LINEAR PREDICTION (2)
MEL FREQUENCY CEPSTRAL COEFFICIENT (2)
MODULATION (2)
MUTUAL INFORMATION (2)
NOISE MEASUREMENT (2)
PHASE ESTIMATION (2)
POWER DYNAMICS RECOVERY (2)
REVERBERATION (2)
SINGING VOICE (2)
SINUSOIDAL MODELLING (2)
SPECTRAL ENVELOPE (2)
SPEECH INTELLIGIBILITY IN NOISE (2)
SPEECH MODELING (2)
SPEECH RECOGNITION (2)
SUPPORT VECTOR MACHINES (2)
TRAJECTORY (2)
VOCODERS (2)
VOICE TRANSFORMATION (2)
ABSTRACTS (1)
ACOUSTIC FEATURES (1)
ACTIVE APPEARANCE MODEL (1)
ACTIVE CONTOURS (1)
ADAPTIVE AM-FM SIGNAL DECOMPOSITION (1)
ADAPTIVE MODULATION SPECTRAL FEATURES (1)
ADAPTIVE SIGNAL PROCESSING (1)
ADAPTIVE SINUSOIDAL MODELS (1)
ALGORITHM DESIGN AND ANALYSIS (1)
AM–FM DECOMPOSITION (1)
AM–FM SIGNALS (1)
AM-FM SPEECH DECOMPOSITION (1)
AMPLITUDE MODULATION (1)
ANALYSIS WINDOW (1)
APPROXIMATE GAUSS-NEWTON METHOD (1)
APPROXIMATION ALGORITHMS (1)
ARCTIC (1)
ATTACK TRANSIENTS (1)
AUDIO SIGNAL PROCESSING (1)
AUTOCORRELATION SEQUENCES (1)
AUTOMATED CARDIAC AUSCULTATION (1)
AVERAGE VOICE MODEL (1)
BAYES METHODS (1)
BENIGN LARYNGEAL LESIONS (1)
BIASED ESTIMATOR (1)
BIRDS (1)
BOOSTING (1)
BUSINESS (1)
CASUAL SPEECH (1)
CLASSIFICATION TASK (1)
CLASSIFICATION TREE ANALYSIS (1)
CLOSED PHASE ANALYSIS (1)
CLUSTER ADAPTIVE TRAINING (1)
COMPLEX AMPLITUDE (1)
COMPLEX CEPSTRUM (1)
COMPLEX-VALUED NEURAL NETWORK (1)
COMPLEXITY THEORY (1)
COMPUTATIONAL ETHNOMUSICOLOGY (1)
COMPUTATIONAL MODELING (1)
CONDITIONAL VECTOR QUANTIZATION (1)
CORRELATION METHODS (1)
COVARIANCE MATRICES (1)
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INFONA - science communication portal

Search results for: Yannis Stylianou

A study of time-frequency features for CNN-based automatic heart sound classification for pathology detection

Expressive visual text to speech and expression adaptation using deep neural networks

Effective emotion recognition in movie audio tracks

Adaptive gain control and time warp for enhanced speech intelligibility under reverberation

Predicting dialogue success, naturalness, and length with acoustic features

Modeling Speech Based on Harmonic Plus Noise Models

Adaptive Gain Control for Enhanced Speech Intelligibility Under Reverberation

Near and Far Field Speech-in-Noise Intelligibility Improvements Based on a Time–Frequency Energy Reallocation Approach

Bird detection in audio: A survey and a challenge

Global Variance in Speech Synthesis With Linear Dynamical Models

Advances in phase-aware signal processing in speech communication

Extraction of Speech-Relevant Information from Modulation Spectrograms

Nonlinear Speech Features for the Objective Detection of Discontinuities in Concatenative Speech Synthesis

Biometrics: Different Approaches for Using Gaussian Mixture Models in Handwriting

On the Detection of Discontinuities in Concatenative Speech Synthesis

Progress in Nonlinear Speech Processing

Iterative estimation of phase using complex cepstrum representation

High-resolution sinusoidal modeling of unvoiced speech

Initial investigation of speech synthesis based on complex-valued neural networks

Multi-stream spectral representation for statistical parametric speech synthesis

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