Current high quality text-to-speech (TTS) systems are based on unit selection from a large database that is both contextually and prosodically rich. These systems, albeit capable of natural voice quality, are computationally expensive and require a very large footprint. Their success is attributed to the dramatic reduction of storage costs in recent times. However, for many TTS applications a smaller footprint is becoming a standard requirement. This thesis presents a new method for representing speech segments that can improve the quality and/or reduce the footprint current concatenative TTS systems. The circular linear prediction (CLP) model is revisited and combined with the constant pitch transform (CPT) to provide a robust representation of speech signals that allows for limited prosodic movements without a perceivable loss in quality. The CLP model assumes that each frame of voiced speech is an infinitely periodic signal. This assumption allows for LPC modeling using the covariance method, with the efficiency of the autocorrelation method. The CPT is combined with this model to provide a database that is uniform in pitch for matching the target prosody during synthesis. With this representation, limited prosody modifications and unit concatenation can be performed without causing audible artifacts. For resolving artifacts caused by pitch modifications in voicing transitions, a method has been introduced for reducing peakiness in the LP spectra by constraining the line spectral frequencies. Two experiments have been conducted to demonstrate the potential for the capabilities of CLP/CPT method. The first is a listening test to determine the ability of this model to realize prosody modifications without perceivable degradation. Utterances are resynthesized using the CLP/CPT method with emphasized prosodics to increase intelligibility in harsh environments. The second experiment compares the quality of utterances synthesized by unit-selection based limited-domain TTS against the CLP/CPT method. The results demonstrate that the CLP/CPT representation, applied to current concatenative TTS systems, can reduce the size of the database and increase the prosodic richness without noticeable degradation in voice quality.

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Elections are one of the most fundamental activities of a democratic society. As is the case in any other aspect of life, developments in technology have resulted changes in the voting procedure from using the traditional paper-based voting to voting by use of electronic means, or e-voting. E-voting involves using different forms of electronic means like / voting machines, voting via the Internet, telephone, SMS and digital interactive television. This thesis concerns voting by telephone, or televoting, it starts by giving a brief overview and evaluation of various models and technologies that are implemented within such systems. The aspects of televoting that have been investigated are technologies that provide a voice interface to the voter and conduct the voting process, namely the Election Markup Language (EML), Automated Speech Recognition (ASR) and Text-to-Speech (TTS).

Lors du fonctionnement d'un turboréacteur, la rotation de l'axe du moteur induit une force centrifuge qui plaque les aubes contre les alvéoles du disque, le long de surfaces appelées " portées ". Au cours de la vie du moteur, des micro-glissements (" fretting ") sont générés au niveau des portées. Ce travail de thèse s'intéresse aux endommagements de type oligocyclique des portées aube/ disque du compresseur Haute Pression (HP) d'un turboréacteur civil. Afin de réduire le frottement et de protéger les pièces, les portées des aubes sont revêtues d'un dépôt épais de CuNiln sur lequel est appliqué un lubrifiant solide. Le système est soumis à des pressions fortes (600MPa) et à des températures élevées (500°C). Des expertises sur pièces ont permis d'identifier des usures importantes et des phénomènes de transfert. Pour simuler expérimentalement le contact, un moyen d'essai de fretting usure en température a été développé dans le cadre de cette thèse. A partir d'une géométrie de contact échelle 1 simplifiée, choisie pour représenter les champs de chargement moteur, le domaine des sollicitations a été balayé et les comportements tribologiques identifiés et caractérisés. L'étude tribologique a permis de mettre en évidence l'influence forte de la force normale sur les mécanismes d'endommagements, dont les scénarios de mise en place ont pu être explicités pour les deux domaines majeurs de sollicitations. Dans un deuxième temps, les endommagements ont été étudiés d'un point de vue physicochimique et le rôle tribochimique joué par les éléments environnementaux (0, N ... ) a été mis en évidence. Pour finir, la comparaison directe des mécanismes identifiés sur banc expérimental et sur le système industriel a permis d'aborder, d'un point de vue critique, l'importance des paramètres choisis pour les équivalences expérience / système industriel ; et de la dynamique de chargement pour garantir la représentativité d'un essai à l'échelle laboratoire.

Magister Scientiae - MSc / Elections are one of the most fundamental activities of a democratic society. As is the case in any other aspect of life, developments in technology have resulted changes in the voting procedure from using the traditional paper-based voting to voting by use of electronic means, or e-voting. E-voting involves using different forms of electronic means like; voting machines, voting via the Internet, telephone, SMS and digital interactive television. This thesis concerns voting by telephone, or televoting, it starts by giving a brief overview and evaluation of various models and technologies that are implemented within such systems. The aspects of televoting that have been investigated are technologies that provide a voice interface to the voter and conduct the voting process, namely the Election Markup Language (EML), Automated Speech Recognition (ASR) and Text-to-Speech (TTS). / South Africa

Various forms of multimedia learning have been shown to aid learners time and time again. One form of multimedia learning that has not been thoroughly studied is reading while listening (RWL). This is especially the case when it comes to the immediate impacts on reading comprehension from practising RWL. Furthermore the recent advancements of Text-To-Speech (TTS) have started to challenge the established notion that real human recorded spoken word is always preferable for learning, also known as The Voice Effect. This study looked at Swedish University students with English as their second language (L2) and examined how their reading comprehension in L2 was performing in three different groups. The groups were Reading Only (RO), Reading-While-Listening with spoken word (RWL-SW) and Reading-While-Listening with text-to-speech (RWL-TTS). The RO group was then compared to The RWL groups. The two RWL groups were also compared on test scores as well as perceived enjoyment and aid from the narration as reported by the participants. Our results did not exhibit any statistically significant difference in reading comprehension between the RO group and the RWL groups. When looking at the results of the reading comprehension test the RO and RWL-TTS groups got the exact same number of correct answers. This suggests that RWL did not have any notable impact on reading comprehension. Furthermore no statistical significant difference was found between the two RWL groups in test scores or perceived enjoyment and aid from the narration. What’s interesting to note is that RWL-SW performed slightly worse than RWL-TTS on the comprehension test. The reported perceived enjoyment and aid from the narration was also notably similar to each other. This suggests that The Voice Effect did not have relevance in this test. / Olika former av multimediainlärning har visat sig hjälpa eleverna gång på gång. En form av multimedieinlärning som inte har studerats grundligt är läsning medan man lyssnar (RWL). Detta gäller särskilt när det gäller de omedelbara effekterna på läsförståelsen av att använda på RWL. Dessutom har de senaste framstegen med text till tal (TTS) börjat utmana den etablerade uppfattningen att verkligt mänskligt inspelat talat ord alltid är att föredra vid inlärning, även kallat “Rösteffekten” (The Voice Effect). I den här studien undersöktes svenska universitetsstudenter med engelska som andraspråk (L2) och hur deras läsförståelse i L2 presterade i tre olika grupper. Grupperna var Reading Only (RO), Reading-While-Listening med en mänsklig talare (RWL-SW) och Reading-While-Listening med text-to-speech (RWL-TTS). RO-gruppen jämfördes sedan med RWL-grupperna. De två RWL-grupperna jämfördes också med avseende på testresultat samt upplevd njutning och hjälp från berättandet enligt deltagarnas rapporter. Våra resultat visade ingen statistiskt signifikant skillnad i läsförståelse mellan RO-gruppen och RWL-grupperna. När man tittar på resultaten av läsförståelsetestet fick RO- och RWL-TTS- grupperna exakt lika många korrekta svar. Detta tyder på att RWL inte hade någon anmärkningsvärd inverkan på läsförståelsen. Dessutom hittades ingen statistiskt signifikant skillnad mellan de två RWL-grupperna när det gäller testresultat eller upplevd njutning och hjälp av uppläsningen. Vad som är intressant att notera är att RWL-SW presterade något sämre än RWL-TTS på läsförståelsetestet. Den rapporterade upplevda uppskattningen och hjälp från uppläsning var också anmärkningsvärt likartade. Detta tyder på att “The Voice Effect” inte hade någon betydelse i detta test.

In this research, our goal was to pinpoint the crucial characteristics that make a voice suitable for an AI psychologist. More importantly, we wanted to explore how Text-To-Speech (TTS) combined with conditional voice controlling, also known as ”prompting”, could be used to incorporate these traits into the voice generation process. This approach allowed us to create synthetic voices that were not just effective, but also tailored to the specific needs of an AI psychologist role. We conducted an exploratory survey to identify key traits such as trustworthiness, safety, sympathy, calmness, and firmness. These traits were then used as prompts in the generation of AI voices using Tortoise, a state-of-the-art text-to-speech system. The generated voices were evaluated through a survey study, resulting in a mean opinion score for different categories corresponding to the prompts. Our findings showed that while the AI-generated voices did not quite match the quality of a real human voice, they were still quite effective in capturing the essence of the prompts and producing the desired voice characteristics. This suggests that prompting within TTS, or the strategic design of prompts, can significantly enhance the effectiveness of AI voices. In addition, we explored the potential impact of AI on the labor market, considering factors such as job displacement and creation, changes in salaries, and the need for reskilling. Our study highlights that AI will have a significant impact on the job market, but the exact nature of this impact remains uncertain. Our findings offer valuable insights into the potential of AI in psychology and highlight the importance of tailoring voice synthesis to specific applications. They lay a solid foundation for future research in this area, fostering continued innovation at the intersection of AI, psychology, and economic viability. / I den här forskningen var vårt mål att lokalisera de avgörande egenskaperna som gör en röst lämplig för en AI-psykolog. Vi ville även utforska hur ”Text-Till-Tal” (TTS) i kombination med villkorlig röststyrning, också kallat prompting, kan användas för att införliva dessa egenskaper i röstgenereringsprocessen. Detta tillvägagångssätt gjorde det möjligt för oss att skapa syntetiska röster som inte bara var effektiva, utan också skräddarsydda för de specifika behoven hos en roll som AI-psykolog. Vi genomförde en utforskande undersökning för att identifiera nyckelegenskaper som pålitlighet, säkerhet, sympati, lugn och fasthet. Dessa egenskaper användes sedan som uppmaningar i genereringen av AI-röster med hjälp av TorToise, ett modern TTS-system. De genererade rösterna utvärderades genom en enkätstudie, vilket resulterade i en genomsnittlig åsiktspoäng för olika kategorier som motsvarar uppmaningarna. Våra resultat visade att även om de AI-genererade rösterna inte riktigt matchade kvaliteten på en riktig mänsklig röst, var de fortfarande ganska effektiva för att fånga kärnan i uppmaningarna och producera de önskade röstegenskaperna. Detta tyder på att TTS kombinerat med prompting, eller den emotionella styrningen av TTS, avsevärt kan förbättra effektiviteten hos AI-röster. Dessutom undersökte vi den potentiella effekten av AI på arbetsmarknaden, med hänsyn till faktorer som förskjutning och skapande av jobb, förändringar i löner och behovet av ny kompetens. Vår studie visar att AI kommer att ha en betydande inverkan på arbetsmarknaden, men den exakta karaktären av denna påverkan är fortfarande osäker. Våra resultat ger värdefulla insikter om potentialen för AI inom psykologi och belyser vikten av att skräddarsy röstsyntes för specifika applikationer. De lägger en solid grund för framtida forskning inom detta område och främjar fortsatt innovation i skärningspunkten mellan AI, psykologi och ekonomisk bärkraft.

A web-based survey was conducted that included 97 practicing school psychologists in California. The results from the survey indicated that the majority (88%) of respondents were knowledgeable about Tourette Syndrome. Many respondents (28%) had never worked with a student with Tourette’s, 20% had at least one case, and 52% indicated that they had worked with more than two cases in their careers as school psychologists. The majority of respondents indicated that their school psychology program did not adequately train them to assess or counsel students with Tourette’s. The majority of participants also did not feel confident to work with students with Tourette’s. As found in the study, school psychologists are in need of training to better serve children with Tourette Syndrome. Children, whether diagnosed with Tourette Syndrome or not, may exhibit difficulties making academic progress because of tic related issues, as well as comorbid disorders such as Attention Deficit Hyperactivity Disorder (ADHD) and Obsessive Compulsive Disorder (OCD). Schools typically are where students spend many hours of their day, and where those who are knowledgeable about Tourette’s can identify and provide needed supports depending on the student’s needs. Therefore, school psychologists play a key role in facilitating proper education regarding Tourette’s to students, teachers, staff, and families, as well as providing academic, behavioral, emotional, and social support a student may need.

After trying Festival Speech Synthesis System, we decided to develop our own TTS framework, conducive to perform the necessary research experiments for developing good quality TTS for Indian languages. In most of the attempts on Indian language TTS, there is no prosody model, provision for handling foreign language words and no phrase break prediction leading to the possibility of introducing appropriate pauses in the synthesized speech. Further, in the Indian context, there is a real felt need for a bilingual TTS, involving English, along with the Indian language. In fact, it may be desirable to also have a trilingual TTS, which can also take care of the language of the neighboring state or Hindi, in addition. Thus, there is a felt need for a full-fledged TTS development framework, which lends itself for experimentation involving all the above issues and more. This thesis work is therefore such a serious attempt to develop a modular, unit selection based TTS framework. The developed system has been tested for its effectiveness to create intelligible speech in Tamil and Kannada. The created system has also been used to carry out two research experiments on TTS. The first part of the work is the design and development of corpus-based concatenative Tamil speech synthesizer in Matlab and C. A synthesis database has been created with 1027 phonetically rich, pre-recorded sentences, segmented at the phone level. From the sentence to be synthesized, specifications of the required target units are predicted. During synthesis, database units are selected that best match the target specification according to a distance metric and a concatenation quality metric. To accelerate matching, the features of the end frames of the database units have been precomputed and stored. The selected units are concatenated to produce synthetic speech. The high values of the obtained mean opinion scores for the TTS output reveal that speech synthesized using our TTS is intelligible and acceptably natural and can possibly be put to commercial use with some additional features. Experiments carried out by others using my TTS framework have shown that, whenever the required phonetic context is not available in the synthesis database., similar phones that are perceptually indistinguishable may be substituted. The second part of the work deals with the design and modification of the developed TTS framework to be embedded in mobile phones. Commercial GSM FR, EFR and AMR speech codecs are used for compressing our synthesis database. Perception experiments reveal that speech synthesized using a highly compressed database is reasonably natural. This holds promise in the future to read SMSs and emails on mobile phones in Indian languages. Finally, we observe that incorporating prosody and pause models for Indian language TTS would further enhance the quality of the synthetic speech. These are some of the potential, unexplored areas ahead, for research in speech synthesis in Indian languages.

Artificial neural network simulators are a research field which attracts the interest of researchers from various fields, from biology to computer science. The final objectives are the understanding of the mechanisms underlying the human brain, how to reproduce them in an artificial environment, and how drugs interact with them. Multiple neural models have been proposed, each with their peculiarities, from the very complex and biologically realistic Hodgkin-Huxley neuron model to the very simple 'leaky integrate-and-fire' neuron. However, despite numerous attempts to understand the learning behaviour of the synapses, few models have been proposed. Spike-Timing-Dependent Plasticity (STDP) is one of the most relevant and biologically plausible models, and some variants (such as the triplet-based STDP rule) have been proposed to accommodate all biological observations. The research presented in this thesis focuses on a novel learning rule, based on the spike-pair STDP algorithm, which provides a statistical approach with the advantage of being less computationally expensive than the standard STDP rule, and is therefore suitable for its implementation on stand-alone computational units. The environment in which this research work has been carried out is the SpiNNaker project, which aims to provide a massively parallel computational substrate for neural simulation. To support such research, two other topics have been addressed: the first is a way to inject spikes into the SpiNNaker system through a non-real-time channel such as the Ethernet link, synchronising with the timing of the SpiNNaker system. The second research topic is focused on a way to route spikes in the SpiNNaker system based on populations of neurons. The three topics are presented in sequence after a brief introduction to the SpiNNaker project. Future work could include structural plasticity (also known as synaptic rewiring); here, during the simulation of neural networks on the SpiNNaker system, axons, dendrites and synapses may be grown or pruned according to biological observations.