532 research outputs found
Building a speech understanding system using word spotting techniques
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 63-65).by Theresa K. Burianek.M.Eng
A Smart Assistant for Visual Recognition of Painted Scenes
Nowadays, smart devices allow people to easily interact with the surrounding environment thanks to existing communication infrastructures, i.e., 3G/4G/5G or WiFi. In the context of a smart museum, data shared by visitors can be used to provide innovative services aimed to improve their cultural experience. In this paper, we consider as case study the painted wooden ceiling of the Sala Magna of Palazzo Chiaramonte in Palermo, Italy and we present an intelligent system that visitors can use to automatically get a description of the scenes they are interested in by simply pointing their smartphones to them. As compared to traditional applications, this system completely eliminates the need for indoor positioning technologies, which are unfeasible in many scenarios as they can only be employed when museum items are physically distinguishable. Experimental analysis aimed to evaluate the performance of the system in terms of accuracy of the recognition process, and the obtained results show its effectiveness in a real-world application scenario
Prototype of a Conversational Assistant for Satellite Mission Operations
The very first artificial satellite, Sputnik, was launched in 1957 marking a new era. Concurrently,
satellite mission operations emerged. These start at launch and finish at the end of mission, when
the spacecraft is decommissioned. Running a satellite mission requires the monitoring and control
of telemetry data, to verify and maintain satellite health, reconfigure and command the spacecraft,
detect, identify and resolve anomalies and perform launch and early orbit operations.
The very first chatbot, ELIZA was created in 1966, and also marked a new era of Artificial Intelligence
Systems. Said systems answer users’ questions in the most diverse domains, interpreting
the human language input and responding in the same manner. Nowadays, these systems are
everywhere, and the list of possible applications seems endless.
The goal of the present master’s dissertation is to develop a prototype of a chatbot for mission
operations. For this purpose implementing a Natural Language Processing (NLP) model for satellite
missions allied to a dialogue flow model. The performance of the conversational assistant is
evaluated with its implementation on a mission operated by the European Space Agency (ESA),
implying the generation of the spacecraft’s Database Knowledge Graph (KG).
Throughout the years, many tools have been developed and added to the systems used to monitor
and control spacecrafts helping Flight Control Teams (FCT) either by maintaining a comprehensive
overview of the spacecraft’s status and health, speeding up failure investigation, or allowing to easily
correlate time series of telemetry data. However, despite all the advances made which facilitate the
daily tasks, the teams still need to navigate through thousands of parameters and events spanning
years of data, using purposely built user interfaces and relying on filters and time series plots.
The solution presented in this dissertation and proposed by VisionSpace Technologies focuses on
improving operational efficiency whilst dealing with the mission’s complex and extensive databases.O primeiro satélite artificial, Sputnik, foi lançado em 1957 e marcou o inÃcio de uma nova era.
Simultaneamente, surgiram as operações de missão de satélites. Estas iniciam com o lançamento
e terminam com desmantelamento do veÃculo espacial, que marca o fim da missão. A operação
de satélites exige o acompanhamento e controlo de dados de telemetria, com o intuito de verificar
e manter a saúde do satélite, reconfigurar e comandar o veÃculo, detetar, identificar e resolver
anomalias e realizar o lançamento e as operações iniciais do satélite.
Em 1966, o primeiro Chatbot foi criado, ELIZA, e também marcou uma nova era, de sistemas
dotados de Inteligência Artificial. Tais sistemas respondem a perguntas nos mais diversos domÃnios,
para tal interpretando linguagem humana e repondendo de forma similar. Hoje em dia, é muito
comum encontrar estes sistemas e a lista de aplicações possÃveis parece infindável.
O objetivo da presente dissertação de mestrado consiste em desenvolver o protótipo de um Chatbot
para operação de satélites. Para este proposito, criando um modelo de Processamento de
Linguagem Natural (NLP) aplicado a missoões de satélites aliado a um modelo de fluxo de diálogo.
O desempenho do assistente conversacional será avaliado com a sua implementação numa
missão operada pela Agência Espacial Europeia (ESA), o que implica a elaboração do grafico de
conhecimentos associado à base de dados da missão.
Ao longo dos anos, várias ferramentas foram desenvolvidas e adicionadas aos sistemas que acompanham
e controlam veÃculos espaciais, que colaboram com as equipas de controlo de missão,
mantendo uma visão abrangente sobre a condição do satélite, acelerando a investigação de falhas,
ou permitindo correlacionar séries temporais de dados de telemetria. No entanto, apesar de todos
os progressos que facilitam as tarefas diárias, as equipas ainda necessitam de navegar por milhares
de parametros e eventos que abrangem vários anos de recolha de dados, usando interfaces para
esse fim e dependendo da utilização de filtros e gráficos de series temporais.
A solução apresentada nesta dissertação e proposta pela VisionSpace Technologies tem como foco
melhorar a eficiência operacional lidando simultaneamente com as suas complexas e extensas bases
de dados
Assessing voice health using smartphones: Bias and random error of acoustic voice parameters captured by different smartphone types
This is the peer reviewed version of the following article: Jannetts, S., Schaeffler, F., Beck, J. M. & Cowen, S. (2019) Assessing voice health using smartphones: Bias and random error of acoustic voice parameters captured by different smartphone types. International Journal of Language & Communication Disorders, 54 (2), pp. 292-305, which has been published in final form at https://doi.org/10.1111/1460-6984.12457. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.BACKGROUND: Occupational voice problems constitute a serious public health issue with substantial financial and human consequences for society. Modern mobile technologies like smartphones have the potential to enhance approaches to prevention and management of voice problems. This paper addresses an important aspect of smartphone-assisted voice care: the reliability of smartphone-based acoustic analysis for voice health state monitoring.
AIM: To assess the reliability of acoustic parameter extraction for a range of commonly used smartphones by comparison with studio recording equipment.
METHODS AND PROCEDURES: Twenty-two vocally healthy speakers (12 female; 10 male) were recorded producing sustained vowels and connected speech under studio conditions using a high-quality studio microphone and an array of smartphones. For both types of utterances, Bland-Altman-Analysis was used
to assess overall reliability for Mean F0; CPPS; Jitter (RAP) and Shimmer %.
OUTCOMES AND RESULTS: Analysis of the systematic and random error indicated significant bias for CPPS across both sustained vowels and passage reading. Analysis of the random error of the devices indicated that that mean F0 and CPPS showed acceptable random error size, while jitter and shimmer random error was judged as problematic.
CONCLUSIONS AND IMPLICATIONS: Confidence in the feasibility of smartphone-based voice assessment is increased by the experimental finding of high levels of reliability for some clinically relevant acoustic
parameters, while the use of other parameters is discouraged. We also challenge the practice of using statistical tests (e.g. t-tests) for measurement reliability assessment.https://onlinelibrary.wiley.com/journal/1460698454pubpub
Modeling Human-Robot-Interaction based on generic Interaction Patterns
Peltason J. Modeling Human-Robot-Interaction based on generic Interaction Patterns. Bielefeld: Bielefeld University; 2014
- …