This work deals with the text-dependent speaker recognition in systems, where just a few training samples exist. For the purpose of this recognition, the voice imprint based on different features (e.g. MFCC, PLP, ACW etc.) is proposed. At the beginning, there is described the way, how the speech signal is produced. Some speech characteristics important for speaker recognition are also mentioned. The next part of work deals with the speech signal analysis. There is mentioned the preprocessing and also the feature extraction methods. The following part describes the process of speaker recognition and mentions the evaluation of the used methods: speaker identification and verification. Last theoretically based part of work deals with the classifiers which are suitable for the text-dependent recognition. The classifiers based on fractional distances, dynamic time warping, dispersion matching and vector quantization are mentioned. This work continues by design and realization of system, which evaluates all described classifiers for voice imprint based on different features.

Oblasti jako automatické otáčení stránek nebo automatický hudební doprovod jsou studovány již několik desetiletí. Tato práce shrnuje současné metody pro počítačové sledování not v reálném čase. Zabývá se také hudebními příznaky jako jsou chroma třídy a syntetizované spektrální šablony. Dále popisuje klíčové části systému jako krátkodobou Fourierovu transformaci a Dynamické borcení času. V rámci projektu byl navrhnut a vyvinut vlastní systém pro sledování pozice hráče v notách, který byl následně implementován jako mobilní aplikace. Výsledný systém dokáže sledovat i skladby s výrazně odlišným tempem, pauzami během hry nebo drobnými odchylkami od předepsaných not.

Due to the continuous ageing of our society, both the care and the health sector will encounter challenges in maintaining the quality of human care and health standards. While the number of people with diseases such as dementia and physical illness will be rising, we are simultaneously recording a lack of medical personnel such as caregivers and therapists. One possible approach that tackles the described problem is the employment of technical assistance systems that support both medical personnel and elderly living alone at home. This thesis presents approaches to provide assistance for these target groups. In this work, algorithms that are integrated in prototypical assistance systems for vision-based human daily activity, mobility and motion analysis have been developed. The developed algorithms process 3-D point clouds as well as skeleton joint positions to generate meta information concerning activities and the mobility of elderly persons living alone at home. Such type of information was not accessible so far and is now available for monitoring. By generating this meta information, a basis for the detection of long-term and short-term health changes has been created. Besides monitoring meta information, mobilisation for maintaining physical capabilities, either ambulatory or at home, is a further focus of this thesis. Algorithms for the qualitative assessment of physical exercises were therefore investigated. Thereby, motion sequences in the form of skeleton joint trajectories as well as the heat development in active muscles were considered. These algorithms enable an autonomous physical training under the supervision of a virtual therapist even at home. / Aufgrund der voranschreitenden Überalterung unserer Gesellschaft werden sowohl der Pflege- als auch der Gesundheitssektor vor enorme Herausforderungen gestellt. Während die Zahl an vorrangig altersbedingten Erkrankungen, wie Demenz oder physische Erkrankungen des Bewegungsapparates, weiterhin zunehmen wird, stagniert die Zahl an medizinischem Fachpersonal, wie Therapeuten und Pflegekräften. An dieser Stelle besteht das Ziel, die Qualität medizinischer Leistungen auf hohem Niveau zu halten und dabei die Einhaltung von Pflege- und Gesundheitsstandards sicherzustellen. Ein möglicher Ansatz hierfür ist der Einsatz technischer Assistenzsysteme, welche sowohl das medizinische Personal und Angehörige entlasten als auch ältere, insbesondere allein lebende Menschen zu Hause unterstützen können. Die vorliegende Arbeit stellt Ansätze zur Unterstützung der genannten Zielgruppen vor, die prototypisch in Assistenzsystemen zur visuellen, kamerabasierten Analyse von täglichen Aktivitäten, von Mobilität und von Bewegungen bei Trainingsübungen integriert sind. Die entwickelten Algorithmen verarbeiten dreidimensionale Punktwolken und Gelenkpositionen des menschlichen Skeletts, um sogenannte Meta-Daten über tägliche Aktivitäten und die Mobilität einer allein lebenden Person zu erhalten. Diese Informationen waren bis jetzt nicht verfügbar, können allerdings für den Patienten selbst, für medizinisches Personal und Angehörige aufschlussreich sein, denn diese Meta-Daten liefern die Grundlage für die Detektion kurz- und langfristiger Veränderungen im Verhalten oder in der Mobilität, die ansonsten wahrscheinlich unbemerkt geblieben wären. Neben der Erfassung solcher Meta-Informationen liegt ein weiterer Fokus der Arbeit in der Mobilisierung von Patienten durch angeleitetes Training, um ihre Mobilität und körperliche Verfassung zu stärken. Dabei wurden Algorithmen zur qualitativen Bewertung und Vermittlung von Korrekturhinweisen bei physischen Trainingsübungen entwickelt, die auf Trajektorien von Gelenkpositionen und der Wärmeentwicklung in Muskeln beruhen. Diese Algorithmen ermöglichen aufgrund der Nachahmung eines durch den Therapeuten gegebenen Feedbacks ein autonomes Training.

This dissertation investigates how cognates are organized in the bilingual mental lexicon and examines whether orthography in one language, via phonological representations, influences the processing of cognates and false friends in the other language. In light of the framework of two well-known models of bilingual visual word recognition, the Bilingual Interactive Activation (BIA) and the Bilingual Interactive Activation Plus (BIA+), the premise is that there is activation from orthography to phonology across a bilingual’s two languages and that this activation is modulated by the degree of orthographic and phonological code overlap. Two objective metrics were used to assess crosslinguistic similarity of Portuguese-English cognates and false friends that were selected for a cross-language lexical decision task with masked priming. Dynamic time warping (DTW), an algorithm that was originally conceived to compare different speech patterns in automatic speech recognition and to measure acoustic similarity between two time-dependent sequences, was used to compute crosslinguistic phonological similarity. The Normalized Levenshtein Distance (NLD), an algorithm that calculates the minimum number of single-character insertions, deletions or substitutions required to change one word into another and normalizes the result by their lengths, was used to compute crosslinguistic orthographic similarity. Portuguese-English bilinguals who acquired their second language after reaching puberty, and English functional monolinguals who grew up speaking primarily English were recruited to participate in the experimental task. Based on collected reaction time and accuracy data, mixed-effects models analyses are used to estimate the individual effects of crosslinguistic orthographic, phonological and semantic similarity and the role each of them, along with English proficiency, word frequency and length play in the organization of the Portuguese-English bilingual mental lexicon.