Modeling of Polish Intonation for Statistical-Parametric Speech Synthesis

Wydział NeofilologiiBieżąca praca prezentuje próbę budowy neurobiologicznie umotywowanego modelu mapowań pomiędzy wysokopoziomowymi dyskretnymi kategoriami lingwistycznymi a ciągłym sygnałem częstotliwości podstawowej w polskiej neutralnej mowie czytanej, w oparciu o konwolucyjne sieci neuronowe. Po krótkim wprowadzeniu w problem badawczy w kontekście intonacji, syntezy mowy oraz luki pomiędzy fonetyką a fonologią, praca przedstawia opis uczenia modelu na podstawie specjalnego korpusu mowy oraz ewaluację naturalności konturu F0 generowanego przez wyuczony model za pomocą eksperymentów percepcyjnych typu ABX oraz MOS przy użyciu specjalnie w tym celu zbudowanego resyntezatora Neural Source Filter. Następnie, prezentowane są wyniki eksploracji fonologiczno-fonetycznych mapowań wyuczonych przez model. W tym celu wykorzystana została jedna z tzw. metod wyjaśniających dla sztucznej inteligencji – Layer-wise Relevance Propagation. W pracy przedstawione zostały wyniki powstałej na tej podstawie obszernej analizy ilościowej istotności dla konturu częstotliwości podstawowej każdej z 1297 specjalnie wygenerowanych lingwistycznych kategorii wejściowych modelu oraz ich wielorakich grupowań na różnorodnych poziomach abstrakcji. Pracę kończy dogłębna analiza oraz interpretacja uzyskanych wyników oraz rozważania na temat mocnych oraz słabych stron zastosowanych metod, a także lista proponowanych usprawnień.This work presents an attempt to build a neurobiologically inspired Convolutional Neural Network-based model of the mappings between discrete high-level linguistic categories into a continuous signal of fundamental frequency in Polish neutral read speech. After a brief introduction of the current research problem in the context of intonation, speech synthesis and the phonetic-phonology gap, the work goes on to describe the training of the model on a special speech corpus, and an evaluation of the naturalness of the F0 contour produced by the trained model through ABX and MOS perception experiments conducted with help of a specially built Neural Source Filter resynthesizer. Finally, an in-depth exploration of the phonology-to-phonetics mappings learned by the model is presented; the Layer-wise Relevance Propagation explainability method was used to perform an extensive quantitative analysis of the relevance of 1297 specially engineered linguistic input features and their groupings at various levels of abstraction for the specific contours of the fundamental frequency. The work ends with an in-depth interpretation of these results and a discussion of the advantages and disadvantages of the current method, and lists a number of potential future improvements.Badania przedstawione w pracy zostały cz˛e´sciowo zrealizowane w ramach grantu badawczego Harmonia nr UMO-2014/14/M/HS2/00631 przyznanego przez Narodowe Centrum Nauki

The phonetics of speech breathing : pauses, physiology, acoustics, and perception

Speech is made up of a continuous stream of speech sounds that is interrupted by pauses and breathing. As phoneticians are primarily interested in describing the segments of the speech stream, pauses and breathing are often neglected in phonetic studies, even though they are vital for speech. The present work adds to a more detailed view of both pausing and speech breathing with a special focus on the latter and the resulting breath noises, investigating their acoustic, physiological, and perceptual aspects. We present an overview of how a selection of corpora annotate pauses and pause-internal particles, as well as a recording setup that can be used for further studies on speech breathing. For pauses, this work emphasized their optionality and variability under different tempos, as well as the temporal composition of silence and breath noise in breath pauses. For breath noises, we first focused on acoustic and physiological characteristics: We explored alignment between the onsets and offsets of audible breath noises with the start and end of expansion of both rib cage and abdomen. Further, we found similarities between speech breath noises and aspiration phases of /k/, as well as that breath noises may be produced with a more open and slightly more front place of articulation than realizations of schwa. We found positive correlations between acoustic and physiological parameters, suggesting that when speakers inhale faster, the resulting breath noises were more intense and produced more anterior in the mouth. Inspecting the entire spectrum of speech breath noises, we showed relatively flat spectra and several weak peaks. These peaks largely overlapped with resonances reported for inhalations produced with a central vocal tract configuration. We used 3D-printed vocal tract models representing four vowels and four fricatives to simulate in- and exhalations by reversing airflow direction. We found the direction to not have a general effect for all models, but only for those with high-tongue configurations, as opposed to those that were more open. Then, we compared inhalations produced with the schwa-model to human inhalations in an attempt to approach the vocal tract configuration in speech breathing. There were some similarities, however, several complexities of human speech breathing not captured in the models complicated comparisons. In two perception studies, we investigated how much information listeners could auditorily extract from breath noises. First, we tested categorizing different breath noises into six different types, based on airflow direction and airway usage, e.g. oral inhalation. Around two thirds of all answers were correct. Second, we investigated how well breath noises could be used to discriminate between speakers and to extract coarse information on speaker characteristics, such as age (old/young) and sex (female/male). We found that listeners were able to distinguish between two breath noises coming from the same or different speakers in around two thirds of all cases. Hearing one breath noise, classification of sex was successful in around 64%, while for age it was 50%, suggesting that sex was more perceivable than age in breath noises.Deutsche Forschungsgemeinschaft (DFG) – Projektnummer 418659027: "Pause-internal phonetic particles in speech communication

Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference

Phonetic accommodation to natural and synthetic voices : Behavior of groups and individuals in speech shadowing

The present study investigates whether native speakers of German phonetically accommodate to natural and synthetic voices in a shadowing experiment. We aim to determine whether this phenomenon, which is frequently found in HHI, also occurs in HCI involving synthetic speech. The examined features pertain to different phonetic domains: allophonic variation, schwa epenthesis, realization of pitch accents, word-based temporal structure and distribution of spectral energy. On the individual level, we found that the participants converged to varying subsets of the examined features, while they maintained their baseline behavior in other cases or, in rare instances, even diverged from the model voices. This shows that accommodation with respect to one particular feature may not predict the behavior with respect to another feature. On the group level, the participants of the natural condition converged to all features under examination, however very subtly so for schwa epenthesis. The synthetic voices, while partly reducing the strength of effects found for the natural voices, triggered accommodating behavior as well. The predominant pattern for all voice types was convergence during the interaction followed by divergence after the interaction

Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

Analytical phonetic study of three areas of Al-Farahidiy's legacy

It is the purpose of the present thesis to present an analytical phonetic study of three areas of alFarahidiy1s linguistic legacy in a general phonetic perspective in such a way as to preserve a proper balance between the analytical and historical sides of our subject, Phonetics. Only three areas have been decided upon due to the fact that a comprehensive, analytical study of al Farahidiy's linguistic legacy would be a lifetime-work. The thesis is presented in four major sections: an introduction and an analytical phonetic study of three areas. The introduction deals in general terms with alFarahidiy1s biography and his contributions to fields pertinent to Phonetics, though they are not primarily phonetic. The three areas deal respectively with his approach to verse structure, the time-substratum underlying his system, and his restoration of the principles which lie hid underneath what I have called (since no other term exists) the phoniconic symbols1 of the East Mediterranean scripts. Each analytical section includes either a theoretical, phonetic discuss¬ ion against which alFarahidiy's contribution is projected in terms of its relation to the general phonetic spectrum, or an empirical evidence in support of a hypothesis discovered in the construction of his prosodic system. Towards this end, the first area, following a more or less Stetsonian line, includes a theoretical view of the articulatory actualization of the respir¬ atory potential1 and rhythmicality in Arabic; the second section is focused on the empirical authentication of the time-units which underlie his prosodic system, whilst the third section starts with an analytico-phonetic approach to the East Mediterranean scripts. The thesis is concluded with a general bibliography of works that have been cited or consulted, with a special section allocated to works by or about alFarahidiy. The author is convinced that the soundest basis for an understanding of certain phonological phenomena (particularly, the superimposed stretches, quantity and rhythm) of a living language with a long history behind it, would be an illumination of the path of development it has pursued. Such a path, in normal conditions, is provided by phoneticians or writers on phonetics. It is also the conviction of the author that for an enlightened attitude towards the history of phonetics, especially in olden times when phonetics was a practice not a discipline, an analytical, phonetic approach to the pertinent writing system constitutes a proper springboard. For this reason, equal attention has been paid to the development of the 'pure' iconic and phoniconic writing systems in Mesopotamia and the East Mediterranean in the prelude to alFarahidiy's restoration of certain scriptological, phoniconic principles which lie in the background of the Ugaritic script in his prosodization of the Arabic script

A Comprehensive Review of Data-Driven Co-Speech Gesture Generation

Gestures that accompany speech are an essential part of natural and efficient embodied human communication. The automatic generation of such co-speech gestures is a long-standing problem in computer animation and is considered an enabling technology in film, games, virtual social spaces, and for interaction with social robots. The problem is made challenging by the idiosyncratic and non-periodic nature of human co-speech gesture motion, and by the great diversity of communicative functions that gestures encompass. Gesture generation has seen surging interest recently, owing to the emergence of more and larger datasets of human gesture motion, combined with strides in deep-learning-based generative models, that benefit from the growing availability of data. This review article summarizes co-speech gesture generation research, with a particular focus on deep generative models. First, we articulate the theory describing human gesticulation and how it complements speech. Next, we briefly discuss rule-based and classical statistical gesture synthesis, before delving into deep learning approaches. We employ the choice of input modalities as an organizing principle, examining systems that generate gestures from audio, text, and non-linguistic input. We also chronicle the evolution of the related training data sets in terms of size, diversity, motion quality, and collection method. Finally, we identify key research challenges in gesture generation, including data availability and quality; producing human-like motion; grounding the gesture in the co-occurring speech in interaction with other speakers, and in the environment; performing gesture evaluation; and integration of gesture synthesis into applications. We highlight recent approaches to tackling the various key challenges, as well as the limitations of these approaches, and point toward areas of future development.Comment: Accepted for EUROGRAPHICS 202

Detecting emotions from speech using machine learning techniques

D.Phil. (Electronic Engineering

Emotion Recognition from Speech with Acoustic, Non-Linear and Wavelet-based Features Extracted in Different Acoustic Conditions

ABSTRACT: In the last years, there has a great progress in automatic speech recognition. The challenge now it is not only recognize the semantic content in the speech but also the called "paralinguistic" aspects of the speech, including the emotions, and the personality of the speaker. This research work aims in the development of a methodology for the automatic emotion recognition from speech signals in non-controlled noise conditions. For that purpose, different sets of acoustic, non-linear, and wavelet based features are used to characterize emotions in different databases created for such purpose