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

Voice source characterization for prosodic and spectral manipulation

The objective of this dissertation is to study and develop techniques to decompose the speech signal into its two main components: voice source and vocal tract. Our main efforts are on the glottal pulse analysis and characterization. We want to explore the utility of this model in different areas of speech processing: speech synthesis, voice conversion or emotion detection among others. Thus, we will study different techniques for prosodic and spectral manipulation. One of our requirements is that the methods should be robust enough to work with the large databases typical of speech synthesis. We use a speech production model in which the glottal flow produced by the vibrating vocal folds goes through the vocal (and nasal) tract cavities and its radiated by the lips. Removing the effect of the vocal tract from the speech signal to obtain the glottal pulse is known as inverse filtering. We use a parametric model fo the glottal pulse directly in the source-filter decomposition phase. In order to validate the accuracy of the parametrization algorithm, we designed a synthetic corpus using LF glottal parameters reported in the literature, complemented with our own results from the vowel database. The results show that our method gives satisfactory results in a wide range of glottal configurations and at different levels of SNR. Our method using the whitened residual compared favorably to this reference, achieving high quality ratings (Good-Excellent). Our full parametrized system scored lower than the other two ranking in third place, but still higher than the acceptance threshold (Fair-Good). Next we proposed two methods for prosody modification, one for each of the residual representations explained above. The first method used our full parametrization system and frame interpolation to perform the desired changes in pitch and duration. The second method used resampling on the residual waveform and a frame selection technique to generate a new sequence of frames to be synthesized. The results showed that both methods are rated similarly (Fair-Good) and that more work is needed in order to achieve quality levels similar to the reference methods. As part of this dissertation, we have studied the application of our models in three different areas: voice conversion, voice quality analysis and emotion recognition. We have included our speech production model in a reference voice conversion system, to evaluate the impact of our parametrization in this task. The results showed that the evaluators preferred our method over the original one, rating it with a higher score in the MOS scale. To study the voice quality, we recorded a small database consisting of isolated, sustained Spanish vowels in four different phonations (modal, rough, creaky and falsetto) and were later also used in our study of voice quality. Comparing the results with those reported in the literature, we found them to generally agree with previous findings. Some differences existed, but they could be attributed to the difficulties in comparing voice qualities produced by different speakers. At the same time we conducted experiments in the field of voice quality identification, with very good results. We have also evaluated the performance of an automatic emotion classifier based on GMM using glottal measures. For each emotion, we have trained an specific model using different features, comparing our parametrization to a baseline system using spectral and prosodic characteristics. The results of the test were very satisfactory, showing a relative error reduction of more than 20% with respect to the baseline system. The accuracy of the different emotions detection was also high, improving the results of previously reported works using the same database. Overall, we can conclude that the glottal source parameters extracted using our algorithm have a positive impact in the field of automatic emotion classification

Multi-parametric source-filter separation of speech and prosodic voice restoration

In this thesis, methods and models are developed and presented aiming at the estimation, restoration and transformation of the characteristics of human speech. During a first period of the thesis, a concept was developed that allows restoring prosodic voice features and reconstruct more natural sounding speech from pathological voices using a multi-resolution approach. Inspired from observations with respect to this approach, the necessity of a novel method for the separation of speech into voice source and articulation components emerged in order to improve the perceptive quality of the restored speech signal. This work subsequently represents the main part of this work and therefore is presented first in this thesis. The proposed method is evaluated on synthetic, physically modelled, healthy and pathological speech. A robust, separate representation of source and filter characteristics has applications in areas that go far beyond the reconstruction of alaryngeal speech. It is potentially useful for efficient speech coding, voice biometrics, emotional speech synthesis, remote and/or non-invasive voice disorder diagnosis, etc. A key aspect of the voice restoration method is the reliable separation of the speech signal into voice source and articulation for it is mostly the voice source that requires replacement or enhancement in alaryngeal speech. Observations during the evaluation of above method highlighted that this separation is insufficient with currently known methods. Therefore, the main part of this thesis is concerned with the modelling of voice and vocal tract and the estimation of the respective model parameters. Most methods for joint source filter estimation known today represent a compromise between model complexity, estimation feasibility and estimation efficiency. Typically, single-parametric models are used to represent the source for the sake of tractable optimization or multi-parametric models are estimated using inefficient grid searches over the entire parameter space. The novel method presented in this work proposes advances in the direction of efficiently estimating and fitting multi-parametric source and filter models to healthy and pathological speech signals, resulting in a more reliable estimation of voice source and especially vocal tract coefficients. In particular, the proposed method is exhibits a largely reduced bias in the estimated formant frequencies and bandwidths over a large variety of experimental conditions such as environmental noise, glottal jitter, fundamental frequency, voice types and glottal noise. The methods appears to be especially robust to environmental noise and improves the separation of deterministic voice source components from the articulation. Alaryngeal speakers often have great difficulty at producing intelligible, not to mention prosodic, speech. Despite great efforts and advances in surgical and rehabilitative techniques, currently known methods, devices and modes of speech rehabilitation leave pathological speakers with a lack in the ability to control key aspects of their voice. The proposed multiresolution approach presented at the end of this thesis provides alaryngeal speakers an intuitive manner to increase prosodic features in their speech by reconstructing a more intelligible, more natural and more prosodic voice. The proposed method is entirely non-invasive. Key prosodic cues are reconstructed and enhanced at different temporal scales by inducing additional volatility estimated from other, still intact, speech features. The restored voice source is thus controllable in an intuitive way by the alaryngeal speaker. Despite the above mentioned advantages there is also a weak point of the proposed joint source-filter estimation method to be mentioned. The proposed method exhibits a susceptibility to modelling errors of the glottal source. On the other hand, the proposed estimation framework appears to be well suited for future research on exactly this topic. A logical continuation of this work is the leverage the efficiency and reliability of the proposed method for the development of new, more accurate glottal source models

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy

Conveying expressivity and vocal effort transformation in synthetic speech with Harmonic plus Noise Models

Aquesta tesi s'ha dut a terme dins del Grup en de Tecnologies Mèdia (GTM) de l'Escola d'Enginyeria i Arquitectura la Salle. El grup te una llarga trajectòria dins del cap de la síntesi de veu i fins i tot disposa d'un sistema propi de síntesi per concatenació d'unitats (US-TTS) que permet sintetitzar diferents estils expressius usant múltiples corpus. De forma que per a realitzar una síntesi agressiva, el sistema usa el corpus de l'estil agressiu, i per a realitzar una síntesi sensual, usa el corpus de l'estil corresponent. Aquesta tesi pretén proposar modificacions del esquema del US-TTS que permetin millorar la flexibilitat del sistema per sintetitzar múltiples expressivitats usant només un únic corpus d'estil neutre. L'enfoc seguit en aquesta tesi es basa en l'ús de tècniques de processament digital del senyal (DSP) per aplicar modificacions de senyal a la veu sintetitzada per tal que aquesta expressi l'estil de parla desitjat. Per tal de dur a terme aquestes modificacions de senyal s'han usat els models harmònic més soroll per la seva flexibilitat a l'hora de realitzar modificacions de senyal. La qualitat de la veu (VoQ) juga un paper important en els diferents estils expressius. És per això que es va estudiar la síntesi de diferents emocions mitjançant la modificació de paràmetres de VoQ de baix nivell. D'aquest estudi es van identificar un conjunt de limitacions que van donar lloc als objectius d'aquesta tesi, entre ells el trobar un paràmetre amb gran impacte sobre els estils expressius. Per aquest fet l'esforç vocal (VE) es va escollir per el seu paper important en la parla expressiva. Primer es va estudiar la possibilitat de transferir l'VE entre dues realitzacions amb diferent VE de la mateixa paraula basant-se en la tècnica de predicció lineal adaptativa del filtre de pre-èmfasi (APLP). La proposta va permetre transferir l'VE correctament però presentava limitacions per a poder generar nivells intermitjos d'VE. Amb la finalitat de millorar la flexibilitat i control de l'VE expressat a la veu sintetitzada, es va proposar un nou model d'VE basat en polinomis lineals. Aquesta proposta va permetre transferir l'VE entre dues paraules qualsevols i sintetitzar nous nivells d'VE diferents dels disponibles al corpus. Aquesta flexibilitat esta alineada amb l'objectiu general d'aquesta tesi, permetre als sistemes US-TTS sintetitzar diferents estils expressius a partir d'un únic corpus d'estil neutre. La proposta realitzada també inclou un paràmetre que permet controlar fàcilment el nivell d'VE sintetitzat. Això obre moltes possibilitats per controlar fàcilment el procés de síntesi tal i com es va fer al projecte CreaVeu usant interfícies gràfiques simples i intuïtives, també realitzat dins del grup GTM. Aquesta memòria conclou presentant el treball realitzat en aquesta tesi i amb una proposta de modificació de l'esquema d'un sistema US-TTS per incloure els blocs de DSP desenvolupats en aquesta tesi que permetin al sistema sintetitzar múltiple nivells d'VE a partir d'un corpus d'estil neutre. Això obre moltes possibilitats per generar interfícies d'usuari que permetin controlar fàcilment el procés de síntesi, tal i com es va fer al projecte CreaVeu, també realitzat dins del grup GTM. Aquesta memòria conclou presentant el treball realitzat en aquesta tesi i amb una proposta de modificació de l'esquema del sistema US-TTS per incloure els blocs de DSP desenvolupats en aquesta tesi que permetin al sistema sintetitzar múltiple nivells d'VE a partir d'un corpus d'estil neutre.Esta tesis se llevó a cabo en el Grup en Tecnologies Mèdia de la Escuela de Ingeniería y Arquitectura la Salle. El grupo lleva una larga trayectoria dentro del campo de la síntesis de voz y cuenta con su propio sistema de síntesis por concatenación de unidades (US-TTS). El sistema permite sintetizar múltiples estilos expresivos mediante el uso de corpus específicos para cada estilo expresivo. De este modo, para realizar una síntesis agresiva, el sistema usa el corpus de este estilo, y para un estilo sensual, usa otro corpus específico para ese estilo. La presente tesis aborda el problema con un enfoque distinto proponiendo cambios en el esquema del sistema con el fin de mejorar la flexibilidad para sintetizar múltiples estilos expresivos a partir de un único corpus de estilo de habla neutro. El planteamiento seguido en esta tesis esta basado en el uso de técnicas de procesamiento de señales (DSP) para llevar a cabo modificaciones del señal de voz para que este exprese el estilo de habla deseado. Para llevar acabo las modificaciones de la señal de voz se han usado los modelos harmónico más ruido (HNM) por su flexibilidad para efectuar modificaciones de señales. La cualidad de la voz (VoQ) juega un papel importante en diferentes estilos expresivos. Por ello se exploró la síntesis expresiva basada en modificaciones de parámetros de bajo nivel de la VoQ. Durante este estudio se detectaron diferentes problemas que dieron pié a los objetivos planteados en esta tesis, entre ellos el encontrar un único parámetro con fuerte influencia en la expresividad. El parámetro seleccionado fue el esfuerzo vocal (VE) por su importante papel a la hora de expresar diferentes emociones. Las primeras pruebas se realizaron con el fin de transferir el VE entre dos realizaciones con diferente grado de VE de la misma palabra usando una metodología basada en un proceso filtrado de pre-émfasis adaptativo con coeficientes de predicción lineales (APLP). Esta primera aproximación logró transferir el nivel de VE entre dos realizaciones de la misma palabra, sin embargo el proceso presentaba limitaciones para generar niveles de esfuerzo vocal intermedios. A fin de mejorar la flexibilidad y el control del sistema para expresar diferentes niveles de VE, se planteó un nuevo modelo de VE basado en polinomios lineales. Este modelo permitió transferir el VE entre dos palabras diferentes e incluso generar nuevos niveles no presentes en el corpus usado para la síntesis. Esta flexibilidad está alineada con el objetivo general de esta tesis de permitir a un sistema US-TTS expresar múltiples estilos de habla expresivos a partir de un único corpus de estilo neutro. Además, la metodología propuesta incorpora un parámetro que permite de forma sencilla controlar el nivel de VE expresado en la voz sintetizada. Esto abre la posibilidad de controlar fácilmente el proceso de síntesis tal y como se hizo en el proyecto CreaVeu usando interfaces simples e intuitivas, también realizado dentro del grupo GTM. Esta memoria concluye con una revisión del trabajo realizado en esta tesis y con una propuesta de modificación de un esquema de US-TTS para expresar diferentes niveles de VE a partir de un único corpus neutro.This thesis was conducted in the Grup en Tecnologies M`edia (GTM) from Escola d’Enginyeria i Arquitectura la Salle. The group has a long trajectory in the speech synthesis field and has developed their own Unit-Selection Text-To-Speech (US-TTS) which is able to convey multiple expressive styles using multiple expressive corpora, one for each expressive style. Thus, in order to convey aggressive speech, the US-TTS uses an aggressive corpus, whereas for a sensual speech style, the system uses a sensual corpus. Unlike that approach, this dissertation aims to present a new schema for enhancing the flexibility of the US-TTS system for performing multiple expressive styles using a single neutral corpus. The approach followed in this dissertation is based on applying Digital Signal Processing (DSP) techniques for carrying out speech modifications in order to synthesize the desired expressive style. For conducting the speech modifications the Harmonics plus Noise Model (HNM) was chosen for its flexibility in conducting signal modifications. Voice Quality (VoQ) has been proven to play an important role in different expressive styles. Thus, low-level VoQ acoustic parameters were explored for conveying multiple emotions. This raised several problems setting new objectives for the rest of the thesis, among them finding a single parameter with strong impact on the expressive style conveyed. Vocal Effort (VE) was selected for conducting expressive speech style modifications due to its salient role in expressive speech. The first approach working with VE was based on transferring VE between two parallel utterances based on the Adaptive Pre-emphasis Linear Prediction (APLP) technique. This approach allowed transferring VE but the model presented certain restrictions regarding its flexibility for generating new intermediate VE levels. Aiming to improve the flexibility and control of the conveyed VE, a new approach using polynomial model for modelling VE was presented. This model not only allowed transferring VE levels between two different utterances, but also allowed to generate other VE levels than those present in the speech corpus. This is aligned with the general goal of this thesis, allowing US-TTS systems to convey multiple expressive styles with a single neutral corpus. Moreover, the proposed methodology introduces a parameter for controlling the degree of VE in the synthesized speech signal. This opens new possibilities for controlling the synthesis process such as the one in the CreaVeu project using a simple and intuitive graphical interfaces, also conducted in the GTM group. The dissertation concludes with a review of the conducted work and a proposal for schema modifications within a US-TTS system for introducing the VE modification blocks designed in this dissertation

Methods for speaking style conversion from normal speech to high vocal effort speech

This thesis deals with vocal-effort-focused speaking style conversion (SSC). Specifically, we studied two topics on conversion of normal speech to high vocal effort. The first topic involves the conversion of normal speech to shouted speech. We employed this conversion in a speaker recognition system with vocal effort mismatch between test and enrollment utterances (shouted speech vs. normal speech). The mismatch causes a degradation of the system's speaker identification performance. As solution, we proposed a SSC system that included a novel spectral mapping, used along a statistical mapping technique, to transform the mel-frequency spectral energies of normal speech enrollment utterances towards their counterparts in shouted speech. We evaluated the proposed solution by comparing speaker identification rates for a state-of-the-art i-vector-based speaker recognition system, with and without applying SSC to the enrollment utterances. Our results showed that applying the proposed SSC pre-processing to the enrollment data improves considerably the speaker identification rates. The second topic involves a normal-to-Lombard speech conversion. We proposed a vocoder-based parametric SSC system to perform the conversion. This system first extracts speech features using the vocoder. Next, a mapping technique, robust to data scarcity, maps the features. Finally, the vocoder synthesizes the mapped features into speech. We used two vocoders in the conversion system, for comparison: a glottal vocoder and the widely used STRAIGHT. We assessed the converted speech from the two vocoder cases with two subjective listening tests that measured similarity to Lombard speech and naturalness. The similarity subjective test showed that, for both vocoder cases, our proposed SSC system was able to convert normal speech to Lombard speech. The naturalness subjective test showed that the converted samples using the glottal vocoder were clearly more natural than those obtained with STRAIGHT

Prosodic and Voice Quality Cross-Language Analysis of Storytelling Expressive Categories Oriented to Text-To-Speech Synthesis

Durant segles, la interpretació oral de contes i històries ha sigut una tradició mundial lligada a l’entreteniment, la educació, i la perpetuació de la cultura. En les últimes dècades, alguns treballs s’han centrat en analitzar aquest estil de parla ric en matisos expressius caracteritzats per determinats patrons acústics. En relació a això, també hi ha hagut un interès creixent en desenvolupar aplicacions de contar contes, com ara les de contacontes interactius. Aquesta tesi està orientada a millorar aspectes claus d’aquest tipus d’aplicacions: millorar la naturalitat de la parla sintètica expressiva a partir d’analitzar la parla de contacontes en detall, a més a més de proporcionar un millor llenguatge no verbal a un avatar parlant mitjançant la sincronització de la parla i els gestos. Per aconseguir aquests objectius és necessari comprendre les característiques acústiques d’aquest estil de parla i la interacció de la parla i els gestos. Pel que fa a característiques acústiques de la parla de contacontes, la literatura relacionada ha treballat en termes de prosòdia, mentre que només ha estat suggerit que la qualitat de la veu pot jugar un paper important per modelar les subtileses d’aquest estil. En aquesta tesi, el paper tant de la prosòdia com de la qualitat de la veu en l’estil indirecte de la parla de contacontes en diferents idiomes és analitzat per identificar les principal categories expressives que la composen i els paràmetres acústics que les caracteritzen. Per fer-ho, es proposa una metodologia d’anotació per aquest estil de parla a nivell de oració basada en modes de discurs dels contes (mode narratiu, descriptiu, i diàleg), introduint a més sub-modes narratius. Considerant aquesta metodologia d’anotació, l’estil indirecte d’una història orientada a una audiència jove (cobrint versions en castellà, anglès, francès, i alemany) és analitzat en termes de prosòdia i qualitat de la veu mitjançant anàlisis estadístics i discriminants, després de classificar els àudios de les oracions de la història en les seves categories expressives. Els resultats confirmen l’existència de les categories de contes amb diferències expressives subtils en tots els idiomes més enllà dels estils personals dels narradors. En aquest sentit, es presenten evidències que suggereixen que les categories expressives dels contes es transmeten amb matisos expressius més subtils que en les emocions bàsiques, després de comparar els resultats obtinguts amb aquells de parla emocional. Els anàlisis també mostren que la prosòdia i la qualitat de la veu contribueixen pràcticament de la mateixa manera a l’hora de discriminar entre les categories expressives dels contes, les quals son expressades amb patrons acústics similars en tots els idiomes analitzats. Cal destacar també la gran relació observada en la selecció de categoria per cada oració que han fet servir els diferents narradors encara quan, que sapiguem, no se’ls hi va donar cap indicació. Per poder traslladar totes aquestes categories a un sistema de text a parla basat en corpus, caldria enregistrar un corpus per cada categoria. No obstant, crear diferents corpus ad-hoc esdevé un tasca molt laboriosa. En la tesi, s’introdueix una alternativa basada en una metodologia d’anàlisi orientada a síntesi dissenyada per derivar models de regles des de un petit però representatiu conjunt d’oracions, que poden poder ser utilitzats per generar parla amb estil de contacontes a partir de parla neutra. Els experiments sobre suspens creixent com a prova de concepte mostren la viabilitat de la proposta en termes de naturalitat i similitud respecte un narrador de contes real. Finalment, pel que fa a interacció entre parla i gestos, es realitza un anàlisi de sincronia i èmfasi orientat a controlar un avatar de contacontes en 3D. Al tal efecte, es defineixen indicadors de força tant per els gestos com per la parla. Després de validar-los amb tests perceptius, una regla d’intensitat s’obté de la seva correlació. A més a més, una regla de sincronia es deriva per determinar correspondències temporals entre els gestos i la parla. Aquests anàlisis s’han dut a terme sobre interpretacions neutres i agressives per part d’un actor per cobrir un gran rang de nivells d’èmfasi, com a primer pas per avaluar la integració d’un avatar parlant després del sistema de text a parla.Durante siglos, la interpretación oral de cuentos e historias ha sido una tradición mundial ligada al entretenimiento, la educación, y la perpetuación de la cultura. En las últimas décadas, algunos trabajos se han centrado en analizar este estilo de habla rico en matices expresivos caracterizados por determinados patrones acústicos. En relación a esto, también ha habido un interés creciente en desarrollar aplicaciones de contar cuentos, como las de cuentacuentos interactivos. Esta tesis está orientada a mejorar aspectos claves de este tipo de aplicaciones: mejorar la naturalidad del habla sintética expresiva a partir de analizar el habla de cuentacuentos en detalle, además de proporcionar un mejor lenguaje no verbal a un avatar parlante mediante la sincronización del habla y los gestos. Para conseguir estos objetivos es necesario comprender las características acústicas de este estilo de habla y la interacción del habla y los gestos. En cuanto a características acústicas del habla de narradores de cuentos, la literatura relacionada ha trabajado en términos de prosodia, mientras que sólo ha sido sugerido que la calidad de la voz puede jugar un papel importante para modelar las sutilezas de este estilo. En esta tesis, el papel tanto de la prosodia como de la calidad de la voz en el estilo indirecto del habla de cuentacuentos en diferentes idiomas es analizado para identificar las principales categorías expresivas que componen este estilo de habla y los parámetros acústicos que las caracterizan. Para ello, se propone una metodología de anotación a nivel de oración basada en modos de discurso de los cuentos (modo narrativo, descriptivo, y diálogo), introduciendo además sub-modos narrativos. Considerando esta metodología de anotación, el estilo indirecto de una historia orientada a una audiencia joven (cubriendo versiones en castellano, inglés, francés, y alemán) es analizado en términos de prosodia y calidad de la voz mediante análisis estadísticos y discriminantes, después de clasificar los audios de las oraciones de la historia en sus categorías expresivas. Los resultados confirman la existencia de las categorías de cuentos con diferencias expresivas sutiles en todos los idiomas más allá de los estilos personales de los narradores. En este sentido, se presentan evidencias que sugieren que las categorías expresivas de los cuentos se transmiten con matices expresivos más sutiles que en las emociones básicas, tras comparar los resultados obtenidos con aquellos de habla emocional. Los análisis también muestran que la prosodia y la calidad de la voz contribuyen prácticamente de la misma manera a la hora de discriminar entre las categorías expresivas de los cuentos, las cuales son expresadas con patrones acústicos similares en todos los idiomas analizados. Cabe destacar también la gran relación observada en la selección de categoría para cada oración que han utilizado los diferentes narradores aun cuando, que sepamos, no se les dio ninguna indicación. Para poder trasladar todas estas categorías a un sistema de texto a habla basado en corpus, habría que grabar un corpus para cada categoría. Sin embargo, crear diferentes corpus ad-hoc es una tarea muy laboriosa. En la tesis, se introduce una alternativa basada en una metodología de análisis orientada a síntesis diseñada para derivar modelos de reglas desde un pequeño pero representativo conjunto de oraciones, que pueden ser utilizados para generar habla de cuentacuentos a partir de neutra. Los experimentos sobre suspense creciente como prueba de concepto muestran la viabilidad de la propuesta en términos de naturalidad y similitud respecto a un narrador de cuentos real. Finalmente, en cuanto a interacción entre habla y gestos, se realiza un análisis de sincronía y énfasis orientado a controlar un avatar cuentacuentos en 3D. Al tal efecto, se definen indicadores de fuerza tanto para gestos como para habla. Después de validarlos con tests perceptivos, una regla de intensidad se obtiene de su correlación. Además, una regla de sincronía se deriva para determinar correspondencias temporales entre los gestos y el habla. Estos análisis se han llevado a cabo sobre interpretaciones neutras y agresivas por parte de un actor para cubrir un gran rango de niveles de énfasis, como primer paso para evaluar la integración de un avatar parlante después del sistema de texto a habla.For ages, the oral interpretation of tales and stories has been a worldwide tradition tied to entertainment, education, and perpetuation of culture. During the last decades, some works have focused on the analysis of this particular speaking style rich in subtle expressive nuances represented by specific acoustic cues. In line with this fact, there has also been a growing interest in the development of storytelling applications, such as those related to interactive storytelling. This thesis deals with one of the key aspects of audiovisual storytellers: improving the naturalness of the expressive synthetic speech by analysing the storytelling speech in detail, together with providing better non-verbal language to a speaking avatar by synchronizing that speech with its gestures. To that effect, it is necessary to understand in detail the acoustic characteristics of this particular speaking style and the interaction between speech and gestures. Regarding the acoustic characteristics of storytelling speech, the related literature has dealt with the acoustic analysis of storytelling speech in terms of prosody, being only suggested that voice quality may play an important role for the modelling of its subtleties. In this thesis, the role of both prosody and voice quality in indirect storytelling speech is analysed across languages to identify the main expressive categories it is composed of together with the acoustic parameters that characterize them. To do so, an analysis methodology is proposed to annotate this particular speaking style at the sentence level based on storytelling discourse modes (narrative, descriptive, and dialogue), besides introducing narrative sub-modes. Considering this annotation methodology, the indirect speech of a story oriented to a young audience (covering the Spanish, English, French, and German versions) is analysed in terms of prosody and voice quality through statistical and discriminant analyses, after classifying the sentence-level utterances of the story in their corresponding expressive categories. The results confirm the existence of storytelling categories containing subtle expressive nuances across the considered languages beyond narrators' personal styles. In this sense, evidences are presented suggesting that such storytelling expressive categories are conveyed with subtler speech nuances than basic emotions by comparing their acoustic patterns to the ones obtained from emotional speech data. The analyses also show that both prosody and voice quality contribute almost equally to the discrimination among storytelling expressive categories, being conveyed with similar acoustic patterns across languages. It is also worth noting the strong relationship observed in the selection of the expressive category per utterance across the narrators even when, up to our knowledge, no previous indications were given to them. In order to translate all these expressive categories to a corpus-based Text-To-Speech system, the recording of a speech corpus for each category would be required. However, building ad-hoc speech corpora for each and every specific expressive style becomes a very daunting task. In this work, we introduce an alternative based on an analysis-oriented-to-synthesis methodology designed to derive rule-based models from a small but representative set of utterances, which can be used to generate storytelling speech from neutral speech. The experiments conducted on increasing suspense as a proof of concept show the viability of the proposal in terms of naturalness and storytelling resemblance. Finally, in what concerns the interaction between speech and gestures, an analysis is performed in terms of time and emphasis oriented to drive a 3D storytelling avatar. To that effect, strength indicators are defined for speech and gestures. After validating them through perceptual tests, an intensity rule is obtained from their correlation. Moreover, a synchrony rule is derived to determine temporal correspondences between speech and gestures. These analyses have been conducted on aggressive and neutral performances to cover a broad range of emphatic levels as a first step to evaluate the integration of a speaking avatar after the expressive Text-To-Speech system