Abstract:
A device usage monitoring and control system for accomplishing parental monitoring and control of devices connected to a home network includes a permissions module receiving and storing control commands from a parent defining permissions with respect to one or more children. The permissions specify levels of access to devices connected to a home network and/or classifications of media content consumable via the devices. A control module grants a child access to the devices and/or media content via the devices based on the levels of access. A monitoring module monitors the child's usage of the devices and/or the child's consumption of media content via the devices, stores a related usage history, and communicates the usage history to the parent.
Abstract:
A device usage monitoring and control system for accomplishing parental monitoring and control of devices connected to a home network includes a permissions module receiving and storing control commands from a parent defining permissions with respect to one or more children. The permissions specify levels of access to devices connected to a home network and/or classifications of media content consumable via the devices. A control module grants a child access to the devices and/or media content via the devices based on the levels of access. A monitoring module monitors the child's usage of the devices and/or the child's consumption of media content via the devices, stores a related usage history, and communicates the usage history to the parent.
Abstract:
A set of models is developed to represent sound units and these models are then used with the incorrect sound units to determine which generate high likelihood scores. The models generating high likelihood scores for the incorrect sound units represent those that are more likely to be confused. The resulting confusability data may then be used in generating more discriminative speech models and in subsequent pruning of the acoustic decision tree. The confusability data may also be used to develop confusability predictors used for rejection during search and in developing continuous speech recognition models that are optimized to minimize confusability.
Abstract:
Client speaker locations in a speaker space are used to generate speech models for comparison with test speaker data or test speaker speech models. The speaker space can be constructed using training speakers that are entirely separate from the population of client speakers, or from client speakers, or from a mix of training and client speakers. Reestimation of the speaker space based on client environment information is also provided to improve the likelihood that the client data will fall within the speaker space. During enrollment of the clients into the speaker space, additional client speech can be obtained when predetermined conditions are met. The speaker distribution can also be used in the client enrollment step.
Abstract:
The system includes a database of program records representing A/V programs which are available for recording. The system also includes an A/V recording device for receiving a recording command and recording the A/V program. A speech recognizer is provided for receiving the spoken request and translating the spoken request into a text stream having a plurality of words. A natural language processor receives the text stream and processes the words for resolving a semantic content of the spoken request. The natural language processor places the meaning of the words into a task frame having a plurality of key word slots. A dialogue system analyzes the task frame for determining if a sufficient number of key word slots have been filled and prompts the user for additional information for filling empty slots. The dialogue system searches the database of program records using the key words placed within the task frame for selecting the A/V program and generating the recording command for use by the A/V recording device.
Abstract:
A set of speaker dependent models or adapted models is trained upon a comparatively large number of training speakers, one model per speaker, and model parameters are extracted in a predefined order to construct a set of supervectors, one per speaker. Dimensionality reduction is then performed on the set of supervectors to generate a set of eigenvectors that define an eigenvoice space. If desired, the number of vectors may be reduced to achieve data compression. Thereafter, a new speaker provides adaptation data from which a supervector is constructed by constraining this supervector to be in the eigenvoice space based on a maximum likelihood estimation. The resulting coefficients in the eigenspace of this new speaker may then be used to construct a new set of model parameters from which an adapted model is constructed for that speaker. The adapted model may then be further adapted via MAP, MLLR, MLED or the like. The eigenvoice technique may be applied to MLLR transformation matrices or the like; Bayesian estimation performed in eigenspace uses prior knowledge about speaker space density to refine the estimate about the location of a new speaker in eigenspace.
Abstract:
A set of speaker dependent models is trained upon a comparatively large number of training speakers, one model per speaker, and model parameters are extracted in a predefined order to construct a set of supervectors, one per speaker. Principal component analysis is then performed on the set of supervectors to generate a set of eigenvectors that define an eigenvoice space. If desired, the number of vectors may be reduced to achieve data compression. Thereafter, a new speaker provides adaptation data from which a supervector is constructed by constraining this supervector to be in the eigenvoice space. The resulting coefficients in the eigenspace of this new speaker may then be used to construct a new set of model parameters from which an adapted model is constructed for that speaker. Environmental adaptation may be performed by including environmental variations in the training data.
Abstract:
An auxiliary device for equipping the main boom of a mobile crane with an auxiliary boom, wherein a support is mounted near the head of the main boom, by means of which the lifting cable of the main boom may be run to a connection point on the auxiliary boom. The invention further relates to a method for equipping with an auxiliary boom.
Abstract:
A speech processing system is provided for customizing speech parameters across speech applications in a networked environment. The speech processing system includes: a speech processing application residing on a first computing device, where the speech processing application is operable to capture customized speech parameters for a given user and communicate the customized speech parameters across a network; and an intermediary speech processor residing on a second computing device in the networked environment, where the intermediary speech processor adapted to receive the customized speech parameters and is operable to transform the customized speech parameters for use on a third computing device.
Abstract:
A telescopic crane, includes a substructure, a superstructure rotatably mounted onto the substructure, a counterweight and a telescoping boom structure which includes a main boom slewable about a luffing plane. The main boom has a boom base and at least one telescope section received in the boom base and displaceable between retracted and extended positions. At least one guy support is mounted to the boom structure and connected to a guy rope which extends substantially longitudinally in the direction of the boom structure. The guy support is oriented with respect to the luffing plane at an inclination which is so selected that a lateral load acting on the boom structure is partially or entirely received by the guying.