Abstract: A constraint-based speech recognition system for use with a form-filling application employed over a telephone system is disclosed. The system comprises an input signal, wherein the input signal includes both speech input and non-speech input of a type generated by a user via a manually operated device. The system further comprises a constraint module operable to access an information database containing information suitable for use with speech recognition, and to generate candidate information based on the non-speech input and the information database, wherein the candidate information corresponds to a portion of the information. The system further comprises a speech recognition module operable to recognize speech based on the speech input and the candidate information. In an exemplary embodiment, the manually operated device is a touch-tone telephone keypad, and the information database is a lexicon encoded according to classes defined by the keys of the keypad.

Abstract: An automated form filling system includes an input receptive of a plurality of information inputs from a plurality of information sources. An information fuser is operable to select information from the plurality of information inputs based on a comparison of the information inputs, and based on knowledge relating to reliability of the information sources. A form filler is operable to fill an electronic form with the selected information.

Abstract: A navigation apparatus is disclosed which may be used by law enforcement personnel for rapid intervention to a location while adding safety and reliability to the process. The apparatus includes a computer system, having an operating system, memory and a user interface. The system further includes a positioning system, such as a GPS system for determining the position of a vehicle. The positioning system communicates with the operating system. An information database, communicating with the operating system, contains data related to routing information concerning routes for travel by the vehicle. The routing information includes safety information concerning route safety in the traveling region accessible by the vehicle. The apparatus further includes a routing system in communication with the operating system that determines a route based at least in part on the routing information.

Abstract: A reduced dimensionality eigenvoice analytical technique is used during training to develop context-dependent acoustic models for allophones. The eigenvoice technique is also used during run time upon the speech of a new speaker. The technique removes individual speaker idiosyncrasies, to produce more universally applicable and robust allophone models. In one embodiment the eigenvoice technique is used to identify the centroid of each speaker, which may then be “subtracted out” of the recognition equation. In another embodiment maximum likelihood estimation techniques are used to develop common decision tree frameworks that may be shared across all speakers when constructing the eigenvoice representation of speaker space.

Abstract: The remote control unit supports multi-modal dialog with the user, through which the user can easily select programs for viewing or recording. The remote control houses a microphone into which the user can input natural language speech. The input speech is recognized and interpreted by a natural language parser that extracts the semantic content of the user's speech. The parser works in conjunction with an electronic program guide, through which the remote control system is able to ascertain what programs are available for viewing or recording and supply appropriate prompts to the user. In one embodiment, the remote control includes a touch screen display upon which the user may view prompts or make selections by pen input or tapping. Selections made on the touch screen automatically limit the context of the ongoing dialog between user and remote control, allowing the user to interact naturally with the unit.

Abstract: Linear approximation of the background noise is applied after feature extraction and prior to speaker adaptation to allow the speaker adaptation system to adapt the speech models to the enrolling user without distortion from background noise. The linear approximation is applied in the feature domain, such as in the cepstral domain. Any adaptation technique that is commutative in the feature domain may be used.

Abstract: An e-mail message process is provided for use with a personal digital assistant which allows for the use of input speech messaging which is converted to text using a focused language model which is downloaded by a cellular phone connection to an Internet server which provides the focused language model based upon a topic for the intended e-mail message. The text that is generated from the input speech method can be summarized by the e-mail message processor and can be edited by the user. The generated e-mail message can then be transmitted again via cellular connection to an Internet e-mail server for transmitting the e-mail message to a recipient.

Abstract: A reduced dimensionality eigenvoice analytical technique is used during training to develop context-dependent acoustic models for allophones. Re-estimation processes are performed to more strongly separate speaker-dependent and speaker-independent components of the speech model. The eigenvoice technique is also used during run time upon the speech of a new speaker. The technique removes individual speaker idiosyncrasies, to produce more universally applicable and robust allophone models. In one embodiment the eigenvoice technique is used to identify the centroid of each speaker, which may then be “subtracted out” of the recognition equation.

Abstract: The improved noise adaptation technique employs a linear or non-linear transformation to the set of Jacobian matrices corresponding to an initial noise condition. An &agr;-adaptation parameter or artificial intelligence operation is employed in a linear or non-linear way to increase the adaptation bias added to the speech models. This corrects shortcomings of conventional Jacobian adaptation, which tend to underestimate the effect of noise. The improved adaptation technique is further enhanced by a reduced dimensionality, principal component analysis technique that reduces the computational burden, making the adaptation technique beneficial in embedded recognition systems.

Abstract: A navigation apparatus is disclosed which may be used by law enforcement personnel for rapid intervention to a location while adding safety and reliability to the process. The apparatus includes a computer system, having an operating system, memory and a user interface. The system further includes a positioning system, such as a GPS system for determining the position of a vehicle. The positioning system communicates with the operating system. An information database, communicating with the operating system, contains data related to routing information concerning routes for travel by the vehicle. The routing information includes safety information concerning route safety in the traveling region accessible by the vehicle. The apparatus further includes a routing system in communication with the operating system that determines a route based at least in part on the routing information.

Abstract: The discriminative clustering technique tests a provided set of Gaussian distributions corresponding to an acoustic vector space. A distance metric, such as the Bhattacharyya distance, is used to assess which distributions are sufficiently proximal to be merged into a new distribution. Merging is accomplished by computing the centroid of the new distribution by minimizing the Bhattacharyya distance between the parameters of the Gaussian distributions being merged.

Abstract: A method and apparatus for data entry by voice under adverse conditions is disclosed. More specifically it provides a way for efficient and robust form filling by voice. A form can typically contain one or several fields that must be filled in. The user communicates to a speech recognition system and word spotting is performed upon the utterance. The spotted words of an utterance form a phrase that can contain field-specific values and/or commands. Recognized values are echoed back to the speaker via a text-to-speech system. Unreliable or unsafe inputs for which the confidence measure is found to be low (e.g. ill-pronounced speech or noises) are rejected by the spotter. Speaker adaptation is furthermore performed transparently to improve speech recognition accuracy. Other input modalities can be additionally supported (e.g. keyboard and touch-screen). The system maintains a dialogue history to enable editing and correction operations on all active fields.

Abstract: A speech synthesizer customization system provides a mechanism for generating a hierarchical customized user database. The customization system has a template management tool for generating the templates based on customization data from a user and associated replicated dynamic synthesis data from a text-to-speech (TTS) synthesizer. The replicated dynamic synthesis data is arranged in a dynamic data structure having hierarchical levels. The customization system further includes a user database that supplements a standard database of the synthesizer. The tool populates the user database with the templates such that the templates enable the user database to uniformly override subsequently generated speech synthesis data at all hierarchical levels of the dynamic data structure.

Abstract: Speech recognition and natural language parsing components are used to extract the meaning of the user's spoken input. The system stores a semantic representation of an electronic activity guide, and the contents of the guide can be mapped into the grammars used by the natural language parser. Thus, when the user wishes to navigate through the complex menu structure of the electronic activity guide, he or she only needs to speak in natural language sentences. The system automatically filters the contents of the guide and supplies the user with on-screen display or synthesized speech responses to the user's request. The system allows the user to communicate in a natural way with a variety of devices communicating with the home network or home gateway.

Abstract: The acoustic speech signal is decomposed into wavelets arranged in an asymmetrical tree data structure from which individual nodes may be selected to best extract local features, as needed to model specific classes of sound units. The wavelet packet transformation is smoothed through integration and compressed to apply a non-linearity prior to discrete cosine transformation. The resulting subband features such as cepstral coefficients may then be used to construct the speech recognizer's speech models. Using the local feature information extracted in this manner allows a single recognizer to be optimized for several different classes of sound units, thereby eliminating the need for parallel path recognizers.

Abstract: A new speaker provides speech from which comparison snippets are extracted. The comparison snippets are compared with initial snippets stored in a recorded snippet database that is associated with a concatenative synthesizer. The comparison of the snippets to the initial snippets produces required sound units. A greedy selection algorithm is performed with the required sound units for identifying the smallest subset of the input text that contains all of the text for the new speaker to read. The new speaker then reads the optimally selected text and sound units are extracted from the human speech such that the recorded snippet database is modified and the speech synthesized adopts the voice quality and characteristics of the new speaker.

Abstract: A speech synthesis system for generating voice dialog for a message frame having a fixed and a variable portion. A prosody module selects a prosodic template for each of the fixed and variable portions wherein at least one portion comprises a phrase of multiple words. An acoustic module selects an acoustic template for each of the fixed and variable portions wherein at least one portion comprises a phrase of multiple words. A frame generator concatenates the respective prosodic templates and acoustic templates. A sound module generates the voice dialog in accordance with the concatenated prosodic and acoustic templates.

Abstract: A method and apparatus is provided to enable a user watching and/or listening to a program to search for new information in the stream of a telecommunications data. The apparatus includes a voice recognition system that recognizes the user's request and causes a search to be performed in the long stream of data of at least one other telecommunication channel. The system includes a storage device for storing and processing the request. Upon recognition of the request, the incoming signal or signals are scanned for matches with the request. Upon finding the match between the request and the incoming signal, information related to the data is brought to the viewer's attention. This can be accomplished by either changing the viewer's station or by bringing in a split screen display forward into the display.

Abstract: The input signal is transformed into the frequency domain and then subdivided into bands corresponding to different frequency ranges. Adaptive thresholds are applied to the data from each frequency band separately. Thus the short-term band-limited energies are tested for the presence or absence of a speech signal. The adaptive threshold values are independently updated for each of the signal paths, using a histogram data structure to accumulate long-term data representing the mean and variance of energy within the respective frequency band. Endpoint detection is performed by a state machine that transitions from the speech absent state to the speech present state, and vice versa, depending on the results of the threshold comparisons. A partial speech detection system handles cases in which the input signal is truncated.

Abstract: A method for performing noise adaptation of a target speech signal input to a speech recognition system, where the target speech signal contains both additive and convolutional noises. The method includes estimating an additive noise bias and a convolutional noise bias; in the target speech signal; and jointly compensating the target speech signal for the additive and convolutional noise biases in a feature domain.