1,720,982 research outputs found
TOWARDS ARTICULATORY CONTROL OF TALKING HEADS IN HUMANOID ROBOTICS USING A GENETIC-FUZZY IMITATION LEARNING ALGORITHM
No full textIn human heads there is a strong structural linkage between the vocal tract and facial behavior during speech. For a robotic talking head to have human-like behavior, this linkage should be emulated. One way to do that is to estimate the articulatory features from a given utterance and to use them to control a talking head. In this paper, we describe an algorithm to estimate the articulatory features from a spoken sentence using a novel computational model of human vocalization. Our model uses a set of fuzzy rules and genetic optimization. That is, the places of articulation are considered as fuzzy sets whose degrees of membership are the values of the articulatory features. The fuzzy rules represent the relationships between places of articulation and speech acoustic parameters, and the genetic algorithm estimates the degrees of membership of the places of articulation according to an optimization criteria and it performs imitation learning. We verify our model by performing audio-visual subjective tests of animated talking heads showing that the algorithm is able to produce correct results. In particular, subjective listening tests of artificially generated sentences from the articulatory description resulted in an average phonetic accuracy slightly under 80%. Through the analysis of large amounts of natural speech, the algorithm can be used to learn the places of articulation of all phonemes of a given speaker. The estimated places of articulation are then used to control talking heads in humanoid robotics
Spatial map building using fast texture analysis of rotating sonar sensor data for mobile robots
No full textThis paper presents a novel, fast algorithm for accurate detection of the shape of targets around a mobile robot using a single rotating sonar element. The rotating sonar yields an image built up by the reflections of an ultrasonic beam directed at different scan angles. The image is then interpreted with an image-understanding approach based on texture analysis. Several important tasks are performed in this way, such as noise removal, echo correction and restoration. All these processes are obtained by estimating and restoring the degree of texture continuity. Texture analysis, in fact, allows us to look at the image on a large scale thus giving the possibility to infer the overall behavior of the reflection process. The algorithm has been integrated in a mobile robot. However, the algorithm is not suitable for working during the mobile robot movement, rather it can be used during the period when the robot stays in a fixed position
Combining audio and video surveillance with a mobile robot
No full textThis paper presents a Distributed Perception System for application of intelligent surveillance. The system prototype presented in this paper is composed of a static acoustic agent and a static vision agent cooperating with a mobile vision agent mounted on a mobile robot. The audio and video sensors distributed in the environment are used as a single sensor to reveal and track the presence of a person in the surveilled environment. The robot extends the capabilities of the system by adding a mobile sensor (in this work an omnidirectional camera). The mobile omnidirectional camera can be used to have a closer look of the scene or to inspect portions of the environment not covered by the fix sensory agents. In this paper, the hardware and the software architecture of the system and of its sensors are presented. Experiments on the integration of the audio localization data and on the video localization data are reported
Roomfort: An ontology-based comfort management application for hotels
Full text linkBusiness traveling is attracting growing attention due to the expansion of international markets. This fact calls for an increasing attention of the tourism sector toward the needs of business travellers, who often require services that are different from the ones desired by leisure tourists. The application of smart solutions coming from Context Awareness and Ambient Intelligence aimed at promoting guests' comfort and well-being, also in cases in which they have special needs, represents a promising solution to tackle business travellers' requirements and thus, to increase hotels attractiveness and incomes. In this context, this work introduces RoomFort, a smart comfort management system aimed at enhancing comfort of hotel room guests and leveraging on semantic representations of comfort, environment, and sensors. RoomFort provides a set of domain ontologies to formalize comfort-related metrics and to exploit the automatic reasoning capabilities provided by Semantic Web technologies, while gathering data through a network of sensors to ensure guests are provided with tailored comfort profiles during their stays in the hotel. Particular focus has been placed on visual comfort, since indoor lighting features constitute one of the main factors influencing the two main activities that most business travellers accomplish in their hotel room: working and relaxing
Combining audio and video surveillance with a mobile robot
No full textThis paper presents a Distributed Perception System for application of intelligent surveillance. The system prototype presented in this paper is composed of a static acoustic agent and a static vision agent cooperating with a mobile vision agent mounted on a mobile robot. The audio and video sensors distributed in the environment are used as a single sensor to reveal and track the presence of a person in the surveilled environment. The robot extends the capabilities of the system by adding a mobile sensor (in this work an omnidirectional camera). The mobile omnidirectional camera can be used to have a closer look of the scene or to inspect portions of the environment not covered by the fix sensory agents. In this paper, the hardware and the software architecture of the system and of its sensors are presented. Experiments on the integration of the audio localization data and on the video localization data are reported
Improved humanoid vocalization acquisition from a human tutor
No full textThis paper describes an approach which allow a humanoid robot to automatically acquire vocalization capability by learning from a human tutor. The proposed algorithm can, at the same time, synthesize speech utterances from unrestricted text and generate facial movements of the humanoid head synchronized with the generated speech. The algorithm uses fuzzy articulatory rules, derived from the International Phonetic Alphabet (IPA) to allow simpler adaptation to different languages, and genetic optimization of the membership degrees. Experimental results show a good subjective acceptance of the acquired vocalization in terms of quality, naturalness and synchronization. Although the algorithm has been implemented on a virtual talking face, it could eventually be used also in mechanical vocalization systems
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