2250 results about "Ambiguity" patented technology

An ultra wideband (UWB) or short-pulse transmission system that enables precise tracking or geolocation of a target over distances of several kilometers. The system includes a set of N (where N>2) untethered UWB transceivers located at fixed positions, an untethered UWB receiver at the target, and a processor at the target for resolving time-of-flight measurement ambiguities of received pulses to determine precise geolocation by solving a set of equations according to time-of-flight measurements and surveyed positions of N-1 transceivers. To eliminate a clock distribution system, self-synchronizing of pulse timing is achieved by generating a start pulse at one of the untethered transceivers. Alternatively, a timing source may be provided by a GPS or other timing generator at the transceivers in order to synchronize emissions of their pulses.

A system and method for a highly interactive style of speech-to-speech translation is provided. The interactive procedures enable a user to recognize, and if necessary correct, errors in both speech recognition and translation, thus providing robust translation output than would otherwise be possible. The interactive techniques for monitoring and correcting word ambiguity errors during automatic translation, search, or other natural language processing tasks depend upon the correlation of Meaning Cues and their alignment with, or mapping into, the word senses of third party lexical resources, such as those of a machine translation or search lexicon. This correlation and mapping can be carried out through the creation and use of a database of Meaning Cues, i.e., SELECT. Embodiments described above permit the intelligent building and application of this database, which can be viewed as an interlingua, or language-neutral set of meaning symbols, applicable for many purposes. Innovative techniques for interactive correction of server-based speech recognition are also described.

Disclosed is a semantic user interface system that allows text information to be tagged with machine-readable IDs that are associated with concepts for conveying information without any ambiguity or without being hampered by the limitations of human languages. Typically, a plurality of vocabularies are stored across a network, and each vocabulary includes a plurality of machine-readable IDs each corresponding to a concept and at least one keyword corresponding to each machine-readable ID. An input interface accepts text information, selects those machine-readable IDs whose keywords match up with the text information, and returns a list of candidates each corresponding to one of the selected machine-readable IDs and including a corresponding description. The machine-readable IDs can carry information in the form of concepts without any ambiguity as opposed to text information. This system can be applied to web and database searches, publishing messages to selected subscribers, interfacing of applications software, machine translations, etc.

The present invention provides a speech recognition system combined with one or more alternate input modalities to ensure efficient and accurate text input. The speech recognition system achieves less than perfect accuracy due to limited processing power, environmental noise, and/or natural variations in speaking style. The alternate input modalities use disambiguation or recognition engines to compensate for reduced keyboards, sloppy input, and/or natural variations in writing style. The ambiguity remaining in the speech recognition process is mostly orthogonal to the ambiguity inherent in the alternate input modality, such that the combination of the two modalities resolves the recognition errors efficiently and accurately. The invention is especially well suited for mobile devices with limited space for keyboards or touch-screen input.

In embodiments of the present invention, a system and computer-implemented method for enabling dictation may include parsing standard reports in order to identify a plurality of logical phrases in the report used for discrete sections and descriptions. In the report method, the phrases may be parsed and identifier words throughout the report may be compared to eliminate ambiguities. The method may then involve constructing text macros that follow the parsed text, thereby enabling the user to speak the identifiers to indicate full, formatted text. Finally, the report method may involve constructing a mnemonic document so both beginner and experienced users can easily read the identifiers out loud to produce a report. The result of the method is an intuitive, notes-style way to use speech commands to quickly produce a standard, formatted report.

Disclosed herein is a system for rapidly resolving position with centimeter-level accuracy for a mobile or stationary receiver [4]. This is achieved by estimating a set of parameters that are related to the integer cycle ambiguities which arise in tracking the carrier phase of satellite downlinks [5,6]. In the preferred embodiment, the technique involves a navigation receiver [4] simultaneously tracking transmissions [6] from Low Earth Orbit Satellites (LEOS) [2] together with transmissions [5] from GPS navigation satellites [1]. The rapid change in the line-of-sight vectors from the receiver [4] to the LEO signal sources [2], due to the orbital motion of the LEOS, enables the resolution with integrity of the integer cycle ambiguities of the GPS signals [5] as well as parameters related to the integer cycle ambiguity on the LEOS signals [6]. These parameters, once identified, enable real-time centimeter-level positioning of the receiver [4]. In order to achieve high-precision position estimates without the use of specialized electronics such as atomic clocks, the technique accounts for instabilities in the crystal oscillators driving the satellite transmitters, as well as those in the reference [3] and user [4] receivers. In addition, the algorithm accommodates as well as to LEOS that receive signals from ground-based transmitters, then re-transmit frequency-converted signals to the ground.

A system for, and method of, representing and resolving ambiguity in natural language text and a spoken dialogue system incorporating the system for representing and resolving ambiguity or the method. In one embodiment, the system for representing and resolving ambiguity includes: (1) a context tracker that places the natural language text in context to yield candidate attribute-value (AV) pairs and (2) a candidate scorer, associated with the context tracker, that adjusts a confidence associated with each candidate AV pair based on system intent.

Ambiguities with respect to a user topic interest may be resolved so that useful topic-relevant ads can be presented. Such ambiguities may be resolved by monitoring user behavior, determining a user topic interest (e.g., from a plurality of different candidate topics) based on the monitored behavior, and serving ads relevant to the determined user topic interest.

The system implements a novel method for personalized filtering of information and automated generation of user-specific recommendations. The system uses a statistical latent class model, also known as Probabilistic Latent Semantic Analysis, to integrate data including textual and other content descriptions of items to be searched, user profiles, demographic information, query logs of previous searches, and explicit user ratings of items. The system learns one or more statistical models based on available data. The learning may be reiterated once additional data is available. The statistical model, once learned, is utilized in various ways: to make predictions about item relevance and user preferences on un-rated items, to generate recommendation lists of items, to generate personalized search result lists, to disambiguate a users query, to refine a search, to compute similarities between items or users, and for data mining purposes such as identifying user communities.

A unified approach, a fusion technique, a space-time constraint, a methodology, and system architecture are provided. The unified approach is to fuse the outputs of monocular and stereo video trackers, RFID and localization systems and biometric identification systems. The fusion technique is provided that is based on the transformation of the sensory information from heterogeneous sources into a common coordinate system with rigorous uncertainties analysis to account for various sensor noises and ambiguities. The space-time constraint is used to fuse different sensor using the location and velocity information. Advantages include the ability to continuously track multiple humans with their identities in a large area. The methodology is general so that other sensors can be incorporated into the system. The system architecture is provided for the underlying real-time processing of the sensors.

The design of typable devices, in particular, touch-typable devices embodying ambiguous codes, presents numerous ergonomic problems. Solutions for these problems are herein disclosed. This invention teaches methods for the selection of ambiguous codes from the classes of strongly-touch-typable ambiguous codes and substantially optimal ambiguous codes for touch-typable devices such as computers, telephones, pagers, personal digital assistants, smart cards, television set-top devices and other information appliances, given design constraints such as the size, shape, and computational capacity of the device, the typical uses of the device, and conventional constraints such as respect of alphabetic ordering or Qwerty ordering.

A system allows a user to submit an ambiguous search query and to receive potentially disambiguated search results. In one implementation, a search engine's conventional alphanumeric index is translated into a second index that is ambiguated in the same manner as which the user's input is ambiguated. The user's ambiguous search query is compared to this ambiguated index, and the corresponding documents are provided to the user as search results.

The invention discloses an attention CNNs and CCR-based text sentiment analysis method and belongs to the field of natural language processing. The method comprises the following steps of 1, training a semantic word vector and a sentiment word vector by utilizing original text data and performing dictionary word vector establishment by utilizing a collected sentiment dictionary; 2, capturing context semantics of words by utilizing a long-short-term memory (LSTM) network to eliminate ambiguity; 3, extracting local features of a text in combination with convolution kernels with different filtering lengths by utilizing a convolutional neural network; 4, extracting global features by utilizing three different attention mechanisms; 5, performing artificial feature extraction on the original text data; 6, training a multimodal uniform regression target function by utilizing the local features, the global features and artificial features; and 7, performing sentiment polarity prediction by utilizing a multimodal uniform regression prediction method. Compared with a method adopting a single word vector, a method only extracting the local features of the text, or the like, the text sentiment analysis method can further improve the sentiment classification precision.