SMaTTS: standard malay text to speech system

This paper presents a rule-based text- to- speech (TTS) Synthesis System for Standard Malay, namely SMaTTS. The proposed system using sinusoidal method and some pre- recorded wave files in generating speech for the system. The use of phone database significantly decreases the amount of computer memory space used, thus making the system very light and embeddable. The overall system was comprised of two phases the Natural Language Processing (NLP) that consisted of the high-level processing of text analysis, phonetic analysis, text normalization and morphophonemic module. The module was designed specially for SM to overcome few problems in defining the rules for SM orthography system before it can be passed to the DSP module. The second phase is the Digital Signal Processing (DSP) which operated on the low-level process of the speech waveform generation. A developed an intelligible and adequately natural sounding formant-based speech synthesis system with a light and user-friendly Graphical User Interface (GUI) is introduced. A Standard Malay Language (SM) phoneme set and an inclusive set of phone database have been constructed carefully for this phone-based speech synthesizer. By applying the generative phonology, a comprehensive letter-to-sound (LTS) rules and a pronunciation lexicon have been invented for SMaTTS. As for the evaluation tests, a set of Diagnostic Rhyme Test (DRT) word list was compiled and several experiments have been performed to evaluate the quality of the synthesized speech by analyzing the Mean Opinion Score (MOS) obtained. The overall performance of the system as well as the room for improvements was thoroughly discussed

Design and Implementation of Text To Speech Conversion for Visually Impaired People

A Text-to-speech synthesizer is an application that converts text into spoken word, by analyzing and processing the text using Natural Language Processing (NLP) and then using Digital Signal Processing (DSP) technology to convert this processed text into synthesized speech representation of the text. Here, we developed a useful text-to-speech synthesizer in the form of a simple application that converts inputted text into synthesized speech and reads out to the user which can then be saved as an mp3.file. The development of a text to speech synthesizer will be of great help to people with visual impairment and make making through large volume of text easie

Speech synthesis : Developing a web application implementing speech technology

Speech is a natural media of communication for humans. Text-to-speech (TTS) technology uses a computer to synthesize speech. There are three main techniques of TTS synthesis. These are formant-based, articulatory and concatenative. The application areas of TTS include accessibility, education, entertainment and communication aid in mass transit. A web application was developed to demonstrate the application of speech synthesis technology. Existing speech synthesis engines for the Finnish language were compared and two open source text to speech engines, Festival and Espeak were selected to be used with the web application. The application uses a Linux-based speech server which communicates with client devices with the HTTP-GET protocol. The application development successfully demonstrated the use of speech synthesis in language learning. One of the emerging sectors of speech technologies is the mobile market due to limited input capabilities in mobile devices. Speech technologies are not equally available in all languages. Text in the Oromo language was tested using Finnish speech synthesizers; due to similar rules in orthography of germination of consonants and length of vowels, legible results were gained

A Prosodic Turkish text-to-speech synthesizer

Naturalness in Text-to-Speech systems is very important in achieving high quality waveform. The naturalness of the waveform is highly correlated with phonetic coverage and prosodic features such as, duration and F0 contour. Duration determines the timing for the synthesized phoneme, whereas F0 contour determines fundamental frequency component of the waveform. This thesis presents the development of a prosodic Text-to-Speech System for Turkish Language using the Festival Tool [31]. We describe a complete realization of a new male voice, covering allophones of Turkish using duration and F0 parameters. The duration of the allophones and the word stress have been studied extensively. Sentence stress and phrasal stress are also discussed by in less detail. Carrier words are designed approximately for all allophone-allophone combinations. 1680 carrier words are recorded in a sound-proof recording studio. LPC (linear predictive coding) and RES (residual) parameters are computed. The text normalisation module is implemented for abbreviations and numbers. Durations for the allophones are entered. Sentence level and word level F0 generation modules are implemented. By increasing the number of phonemes and giving prosody we obtained a more natural sounding Text-to-Speech System for Turkish Language

Prosody in text-to-speech synthesis using fuzzy logic

For over a thousand years, inventors, scientists and researchers have tried to reproduce human speech. Today, the quality of synthesized speech is not equivalent to the quality of real speech. Most research on speech synthesis focuses on improving the quality of the speech produced by Text-to-Speech (TTS) systems. The best TTS systems use unit selection-based concatenation to synthesize speech. However, this method is very timely and the speech database is very large. Diphone concatenated synthesized speech requires less memory, but sounds robotic. This thesis explores the use of fuzzy logic to make diphone concatenated speech sound more natural. A TTS is built using both neural networks and fuzzy logic. Text is converted into phonemes using neural networks. Fuzzy logic is used to control the fundamental frequency for three types of sentences. In conclusion, the fuzzy system produces f0 contours that make the diphone concatenated speech sound more natural

Time-domain concatenative text-to-speech synthesis.

A concatenation framework for time-domain concatenative speech synthesis (TDCSS) is presented and evaluated. In this framework, speech segments are extracted from CV, VC, CVC and CC waveforms, and abutted. Speech rhythm is controlled via a single duration parameter, which specifies the initial portion of each stored waveform to be output. An appropriate choice of segmental durations reduces spectral discontinuity problems at points of concatenation, thus reducing reliance upon smoothing procedures. For text-to-speech considerations, a segmental timing system is described, which predicts segmental durations at the word level, using a timing database and a pattern matching look-up algorithm. The timing database contains segmented words with associated duration values, and is specific to an actual inventory of concatenative units. Segmental duration prediction accuracy improves as the timing database size increases. The problem of incomplete timing data has been addressed by using `default duration' entries in the database, which are created by re-categorising existing timing data according to articulation manner. If segmental duration data are incomplete, a default duration procedure automatically categorises the missing speech segments according to segment class. The look-up algorithm then searches the timing database for duration data corresponding to these re-categorised segments. The timing database is constructed using an iterative synthesis/adjustment technique, in which a `judge' listens to synthetic speech and adjusts segmental durations to improve naturalness. This manual technique for constructing the timing database has been evaluated. Since the timing data is linked to an expert judge's perception, an investigation examined whether the expert judge's perception of speech naturalness is representative of people in general. Listening experiments revealed marked similarities between an expert judge's perception of naturalness and that of the experimental subjects. It was also found that the expert judge's perception remains stable over time. A synthesis/adjustment experiment found a positive linear correlation between segmental durations chosen by an experienced expert judge and duration values chosen by subjects acting as expert judges. A listening test confirmed that between 70% and 100% intelligibility can be achieved with words synthesised using TDCSS. In a further test, a TDCSS synthesiser was compared with five well-known text-to-speech synthesisers, and was ranked fifth most natural out of six. An alternative concatenation framework (TDCSS2) was also evaluated, in which duration parameters specify both the start point and the end point of the speech to be extracted from a stored waveform and concatenated. In a similar listening experiment, TDCSS2 stimuli were compared with five well-known text-tospeech synthesisers, and were ranked fifth most natural out of six

Phone-based speech synthesis using neural network with articulatory control.

by Lo Wai Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 151-160).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Applications of Speech Synthesis --- p.2Chapter 1.1.1 --- Human Machine Interface --- p.2Chapter 1.1.2 --- Speech Aids --- p.3Chapter 1.1.3 --- Text-To-Speech (TTS) system --- p.4Chapter 1.1.4 --- Speech Dialogue System --- p.4Chapter 1.2 --- Current Status in Speech Synthesis --- p.6Chapter 1.2.1 --- Concatenation Based --- p.6Chapter 1.2.2 --- Parametric Based --- p.7Chapter 1.2.3 --- Articulatory Based --- p.7Chapter 1.2.4 --- Application of Neural Network in Speech Synthesis --- p.8Chapter 1.3 --- The Proposed Neural Network Speech Synthesis --- p.9Chapter 1.3.1 --- Motivation --- p.9Chapter 1.3.2 --- Objectives --- p.9Chapter 1.4 --- Thesis outline --- p.11Chapter 2 --- Linguistic Basics for Speech Synthesis --- p.12Chapter 2.1 --- Relations between Linguistic and Speech Synthesis --- p.12Chapter 2.2 --- Basic Phonology and Phonetics --- p.14Chapter 2.2.1 --- Phonology --- p.14Chapter 2.2.2 --- Phonetics --- p.15Chapter 2.2.3 --- Prosody --- p.16Chapter 2.3 --- Transcription Systems --- p.17Chapter 2.3.1 --- The Employed Transcription System --- p.18Chapter 2.4 --- Cantonese Phonology --- p.20Chapter 2.4.1 --- Some Properties of Cantonese --- p.20Chapter 2.4.2 --- Initial --- p.21Chapter 2.4.3 --- Final --- p.23Chapter 2.4.4 --- Lexical Tone --- p.25Chapter 2.4.5 --- Variations --- p.26Chapter 2.5 --- The Vowel Quadrilaterals --- p.29Chapter 3 --- Speech Synthesis Technology --- p.32Chapter 3.1 --- The Human Speech Production --- p.32Chapter 3.2 --- Important Issues in Speech Synthesis System --- p.34Chapter 3.2.1 --- Controllability --- p.34Chapter 3.2.2 --- Naturalness --- p.34Chapter 3.2.3 --- Complexity --- p.35Chapter 3.2.4 --- Information Storage --- p.35Chapter 3.3 --- Units for Synthesis --- p.37Chapter 3.4 --- Type of Synthesizer --- p.40Chapter 3.4.1 --- Copy Concatenation --- p.40Chapter 3.4.2 --- Vocoder --- p.41Chapter 3.4.3 --- Articulatory Synthesis --- p.44Chapter 4 --- Neural Network Speech Synthesis with Articulatory Control --- p.47Chapter 4.1 --- Neural Network Approximation --- p.48Chapter 4.1.1 --- The Approximation Problem --- p.48Chapter 4.1.2 --- Network Approach for Approximation --- p.49Chapter 4.2 --- Artificial Neural Network for Phone-based Speech Synthesis --- p.53Chapter 4.2.1 --- Network Approximation for Speech Signal Synthesis --- p.53Chapter 4.2.2 --- Feed forward Backpropagation Neural Network --- p.56Chapter 4.2.3 --- Radial Basis Function Network --- p.58Chapter 4.2.4 --- Parallel Operating Synthesizer Networks --- p.59Chapter 4.3 --- Template Storage and Control for the Synthesizer Network --- p.61Chapter 4.3.1 --- Implicit Template Storage --- p.61Chapter 4.3.2 --- Articulatory Control Parameters --- p.61Chapter 4.4 --- Summary --- p.65Chapter 5 --- Prototype Implementation of the Synthesizer Network --- p.66Chapter 5.1 --- Implementation of the Synthesizer Network --- p.66Chapter 5.1.1 --- Network Architectures --- p.68Chapter 5.1.2 --- Spectral Templates for Training --- p.74Chapter 5.1.3 --- System requirement --- p.76Chapter 5.2 --- Subjective Listening Test --- p.79Chapter 5.2.1 --- Sample Selection --- p.79Chapter 5.2.2 --- Test Procedure --- p.81Chapter 5.2.3 --- Result --- p.83Chapter 5.2.4 --- Analysis --- p.86Chapter 5.3 --- Summary --- p.88Chapter 6 --- Simplified Articulatory Control for the Synthesizer Network --- p.89Chapter 6.1 --- Coarticulatory Effect in Speech Production --- p.90Chapter 6.1.1 --- Acoustic Effect --- p.90Chapter 6.1.2 --- Prosodic Effect --- p.91Chapter 6.2 --- Control in various Synthesis Techniques --- p.92Chapter 6.2.1 --- Copy Concatenation --- p.92Chapter 6.2.2 --- Formant Synthesis --- p.93Chapter 6.2.3 --- Articulatory synthesis --- p.93Chapter 6.3 --- Articulatory Control Model based on Vowel Quad --- p.94Chapter 6.3.1 --- Modeling of Variations with the Articulatory Control Model --- p.95Chapter 6.4 --- Voice Correspondence : --- p.97Chapter 6.4.1 --- For Nasal Sounds ´ؤ Inter-Network Correspondence --- p.98Chapter 6.4.2 --- In Flat-Tongue Space - Intra-Network Correspondence --- p.101Chapter 6.5 --- Summary --- p.108Chapter 7 --- Pause Duration Properties in Cantonese Phrases --- p.109Chapter 7.1 --- The Prosodic Feature - Inter-Syllable Pause --- p.110Chapter 7.2 --- Experiment for Measuring Inter-Syllable Pause of Cantonese Phrases --- p.111Chapter 7.2.1 --- Speech Material Selection --- p.111Chapter 7.2.2 --- Experimental Procedure --- p.112Chapter 7.2.3 --- Result --- p.114Chapter 7.3 --- Characteristics of Inter-Syllable Pause in Cantonese Phrases --- p.117Chapter 7.3.1 --- Pause Duration Characteristics for Initials after Pause --- p.117Chapter 7.3.2 --- Pause Duration Characteristic for Finals before Pause --- p.119Chapter 7.3.3 --- General Observations --- p.119Chapter 7.3.4 --- Other Observations --- p.121Chapter 7.4 --- Application of Pause-duration Statistics to the Synthesis System --- p.124Chapter 7.5 --- Summary --- p.126Chapter 8 --- Conclusion and Further Work --- p.127Chapter 8.1 --- Conclusion --- p.127Chapter 8.2 --- Further Extension Work --- p.130Chapter 8.2.1 --- Regularization Network Optimized on ISD --- p.130Chapter 8.2.2 --- Incorporation of Non-Articulatory Parameters to Control Space --- p.130Chapter 8.2.3 --- Experiment on Other Prosodic Features --- p.131Chapter 8.2.4 --- Application of Voice Correspondence to Cantonese Coda Discrim- ination --- p.131Chapter A --- Cantonese Initials and Finals --- p.132Chapter A.1 --- Tables of All Cantonese Initials and Finals --- p.132Chapter B --- Using Distortion Measure as Error Function in Neural Network --- p.135Chapter B.1 --- Formulation of Itakura-Saito Distortion Measure for Neural Network Error Function --- p.135Chapter B.2 --- Formulation of a Modified Itakura-Saito Distortion (MISD) Measure for Neural Network Error Function --- p.137Chapter C --- Orthogonal Least Square Algorithm for RBFNet Training --- p.138Chapter C.l --- Orthogonal Least Squares Learning Algorithm for Radial Basis Function Network Training --- p.138Chapter D --- Phrase Lists --- p.140Chapter D.1 --- Two-Syllable Phrase List for the Pause Duration Experiment --- p.140Chapter D.1.1 --- 兩字詞 --- p.140Chapter D.2 --- Three/Four-Syllable Phrase List for the Pause Duration Experiment --- p.144Chapter D.2.1 --- 片語 --- p.14

Polyglot voice design for unit selection speech synthesis

Current text-to-speech (TTS) systems are increasingly faced with mixed language textual input. Most TTS systems are designed to allow building synthetic voices for different languages, but each voice is able to ”speak” only one language at a time. In order to synthesize mixed language input, polyglot voices are needed which are able to switch between languages when it is required by textual input. A polyglot voice will typically have one basic language and additionally the ability to synthesize foreign words when these are encountered in the textual input. Design of polyglot voices for unit selection speech synthesis is still a research question. An inherent problem of unit selection speech synthesis is that the synthesis quality is closely related to the contents of the unit database. Concatenation of units not in the database usually results in bad synthesis quality. At the same time, building the database with good coverage of units results in a prohibitively large database if the intended domain of synthesized text is unlimited. Polyglot databases have an additional problem that not only single language units have to be stored in the database, but also the concatenation points of words from foreign languages have to be accounted for. This exceeds the database size even more, so that it is worth exploring whether database size can be reduced by including only single language units in the database and handling multilingual units on synthesis time. The present work is concerned with database design for a polyglot unit selection voice. It’s main aim is to examine whether alternative methods for handling multilingual cross-word diphones result in same or better synthesis quality than including these diphones in the database. Three alternative approaches are suggested and model polyglot voices are built to test these methods. The languages included in the synthesizer are Bosnian, English and German. The output quality of the synthesized multilingual word boundary is tested on Bosnian-English and Bosnian-German word pairs in a perceptual experiment

Articulatory-based Speech Processing Methods for Foreign Accent Conversion

The objective of this dissertation is to develop speech processing methods that enable without altering their identity. We envision accent conversion primarily as a tool for pronunciation training, allowing non-native speakers to hear their native-accented selves. With this application in mind, we present two methods of accent conversion. The first assumes that the voice quality/identity of speech resides in the glottal excitation, while the linguistic content is contained in the vocal tract transfer function. Accent conversion is achieved by convolving the glottal excitation of a non-native speaker with the vocal tract transfer function of a native speaker. The result is perceived as 60 percent less accented, but it is no longer identified as the same individual. The second method of accent conversion selects segments of speech from a corpus of non-native speech based on their acoustic or articulatory similarity to segments from a native speaker. We predict that articulatory features provide a more speaker-independent representation of speech and are therefore better gauges of linguistic similarity across speakers. To test this hypothesis, we collected a custom database containing simultaneous recordings of speech and the positions of important articulators (e.g. lips, jaw, tongue) for a native and non-native speaker. Resequencing speech from a non-native speaker based on articulatory similarity with a native speaker achieved a 20 percent reduction in accent. The approach is particularly appealing for applications in pronunciation training because it modifies speech in a way that produces realistically achievable changes in accent (i.e., since the technique uses sounds already produced by the non-native speaker). A second contribution of this dissertation is the development of subjective and objective measures to assess the performance of accent conversion systems. This is a difficult problem because, in most cases, no ground truth exists. Subjective evaluation is further complicated by the interconnected relationship between accent and identity, but modifications of the stimuli (i.e. reverse speech and voice disguises) allow the two components to be separated. Algorithms to measure objectively accent, quality, and identity are shown to correlate well with their subjective counterparts

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