Abstract: The system includes a remotely controlled medical system having a controller in communication with a command device incorporating a microphone. The system further includes a medical device operable by the controller and a sound generator coupled to the controller. The command device incorporating a microphone is paired to the controller for operating the medical device by detecting the sound. The command device incorporating a microphone transmits a signal in response to the sound to the controller to verify the pairing of the command device incorporating a microphone to the controller such that the controller will only operate the medical device in response to a command issued near the sound generator.

Abstract: The system includes a remotely controlled medical system having a controller in communication with a command device incorporating a microphone. The system further includes a medical device operable by the controller and a sound generator coupled to the controller. The command device incorporating a microphone is paired to the controller for operating the medical device by detecting the sound. The command device incorporating a microphone transmits a signal in response to the sound to the controller to verify the pairing of the command device incorporating a microphone to the controller such that the controller will only operate the medical device in response to a command issued near the sound generator.

Abstract: A user authentication system includes a dialogue manager adapted to prompt the user with multiple, selectable pass-phrases. A selection recognizer recognizes user selection of at least one of the multiple, selectable pass-phrases. A user identity analysis module analyzes one or more potential user identities based on adherence of user selection of the pass-phrase to predetermined pass-phrase selection criteria assigned one or more enrolled users.

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 media content distribution system includes a portable device operable to store media content, wirelessly receive input signals, select a portion of the media content based on the input signals, and communicate the selected portion to a user. The system further includes a signaling mechanism disposed at a location and producing an input signal in a range respective to the location. The input signal is selected to ensure that the selected portion of media content includes information relating to the location when the portable device is disposed within the range.

Abstract: A common requirement in automatic speech recognition is to recognize a set of words for any speaker without training the system for each new speaker. A speech recognition system is provided utilizing linear discriminant based phonetic similarities with inter-phonetic unit value normalization. Linear discriminant analysis is utilized using training data with both in-class and out-class sample training utterances for generating linear discriminant vectors for each of the phonetic units. The dot product of each linear discriminant vector and the time spectral pattern vectors generated from the input speech are computed. The resultant raw similarity vectors are then normalized utilizing normalization look-up tables for providing similarity vectors which are utilized by a word matcher for word recognition.

Abstract: A prosody matching template in the form of a tree structure stores indices which point to lookup table and template information prescribing pitch and duration values that are used to add inflection to the output of a text-to-speech synthesizer. The lookup module employs a search algorithm that explores each branch of the tree, assigning penalty scores based on whether the syllable represented by a node of the tree does or does not match the corresponding syllable of the target word. The path with the lowest penalty score is selected as the index into the prosody template table. The system will add nodes by cloning existing nodes in cases where it is not possible to find a one-to-one match between the number of syllables in the target word and the number of nodes in the tree.

Abstract: A media content distribution system includes a portable device operable to store media content, wirelessly receive input signals, select a portion of the media content based on the input signals, and communicate the selected portion to a user. The system further includes a signaling mechanism disposed at a location and producing an input signal in a range respective to the location. The input signal is selected to ensure that the selected portion of media content includes information relating to the location when the portable device is disposed within the range.

Abstract: A navigation and promotion system has a navigation module receptive of information relating to a current location of a user, a target destination, and location-dependent navigational options, wherein the navigation module is adapted to generate a navigational instruction based on the navigational options, the current location, and the target destination. A promotion module is receptive of information relating to user needs, promotional offers, and the target destination. The promotion module is adapted to select a promotional offer based on an inference of user interest, wherein the inference of user interest is based on the target destination. An output is adapted to communicate the navigational instruction and the selected promotional offer to the user.

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 navigation and promotion system has a navigation module receptive of information relating to a current location of a user, a target destination, and location-dependent navigational options, wherein the navigation module is adapted to generate a navigational instruction based on the navigational options, the current location, and the target destination. A promotion module is receptive of information relating to user needs, promotional offers, and the target destination. The promotion module is adapted to select a promotional offer based on an inference of user interest, wherein the inference of user interest is based on the target destination. An output is adapted to communicate the navigational instruction and the selected promotional offer to the user.

Abstract: A common requirement in automatic speech recognition is to recognize a set of words for any speaker without training the system for each new speaker. A speech recognition system is provided utilizing linear discriminant based phonetic similarities with inter-phonetic unit value normalization. Linear discriminant analysis is utilized using training data with both in-class and out-class sample training utterances for generating linear discriminant vectors for each of the phonetic units. The dot product of each linear discriminant vector and the time spectral pattern vectors generated from the input speech are computed. The resultant raw similarity vectors are then normalized utilizing normalization look-up tables for providing similarity vectors which are utilized by a word matcher for word recognition.

Abstract: A distributed speech processing system for constructing speech recognition reference models that are to be used by a speech recognizer in a small hardware device, such as a personal digital assistant or cellular telephone. The speech processing system includes a speech recognizer residing on a first computing device and a speech model server residing on a second computing device. The speech recognizer receives speech training data and processes it into an intermediate representation of the speech training data. The intermediate representation is then communicated to the speech model server. The speech model server generates a speech reference model by using the intermediate representation of the speech training data and then communicates the speech reference model back to the first computing device for storage in a lexicon associated with the speech recognizer.

Abstract: A prosody matching template in the form of a tree structure stores indices which point to lookup table and template information prescribing pitch and duration values that are used to add inflection to the output of a text-to-speech synthesizer. The lookup module employs a search algorithm that explores each branch of the tree, assigning penalty scores based on whether the syllable represented by a node of the tree does or does not match the corresponding syllable of the target word. The path with the lowest penalty score is selected as the index into the prosody template table. The system will add nodes by cloning existing nodes in cases where it is not possible to find a one-to-one match between the number of syllables in the target word and the number of nodes in the tree.

Abstract: A digital word prototype is constructed using one or more speech utterance for a given spoken word or phrase. First, a phone model is used to derive phoneme similarity time series for each of a plurality of phonemes which represent the degree of similarity between the speech utterance and a set of standard phonemes contained in the phone model. Next, the phoneme similarity data is normalized in relation to a non-speech part of the input speech signal. The normalized phoneme similarity data is divided into segments, such that the sum of all normalized phoneme similarity values in a segment are equal for each segment. Next, a word model is constructed from the phoneme similarity data. To do so, within each segment, a summation value is determined by summing over speech frames each of the normalized phoneme similarity values associated with a particular phoneme. In this way, the word model is represented by a vector of summation values that compactly correlate to the normalized phoneme similarity data.

Abstract: The voice dialing server plugs into one or more unused extensions of a branch exchange system to provide each of the users on the system with voice dialing services. To use the system a user simply dials the extension to which the server is attached. The server then prompts the user to supply the name of a party to be called. The name is then looked up in a telephone number dictionary unique to that user. The system then places the telephone call by sending commands to the branch exchange system that simulate the operations a user would perform to connect to an outside line or inside extension and then place the call. The server incorporates a speech processing module having a multistage word recognizer that represents speech in terms of high phoneme similarity values. This representation is highly compact, allowing the word recognizer to perform the recognizer and fine match stages with far less processor overhead than frame-by-frame speech recognizers.

Abstract: The multimodal telephone prompts the user using both a visual display and synthesized voice. It receives user input via keypad and programmable soft keys associated with the display, and also through user-spoken commands. The voice module includes a two stage speech recognizer that models speech in terms of high similarity values. A dialog manager associated with the voice module maintains the visual and verbal systems in synchronism with one another. The dialog manager administers a state machine that records the dialog context. The dialog context is used to ensure that the appropriate visual prompts are displayed--showing what commands are possible at any given point in the dialog. The speech recognizer also uses the dialog context to select the recognized word candidate that is appropriate to the current context.

Abstract: The word hypothesizer reduces the search space for more computationally expensive word recognizers. Each periodic interval of input speech is represented as a vector of phoneme similarity values from which the high similarity regions are selected and parameterized. The hypothesizer computes alignment parameters for each of a plurality of previously stored word prototypes, vis-a-vis the high similarity regions of the input speech utterance. Those word prototypes having the highest recognition scores are selected as word candidates for the fine match recognizer.

Abstract: The multistage word recognizer uses a word reference representation based on reliably detected peaks of phoneme similarity values. The word reference representation captures the basic features of the words by targets that describe the location and shape of stable peaks of phoneme similarity values. The first stage of the word hypothesizer represents each reference word with statistical information on the number of high similarity regions over a predefined number of time intervals. The second stage represents each word by a prototype that consists of a series of phoneme targets and global statistics, namely the average word duration and average match rate. These represent the degree of fit of the word prototype to its training data. Word recognition scores generated in the two stages are converted to dimensionless normalized values and combined by averaging for use in selecting the most probable word candidates.

Abstract: Digitized speech utterances are converted into phoneme similarity data and regions of high similarity are then extracted and used in forming the word prototype. By alignment across speakers unreliable high phoneme similarity regions are eliminated. Word prototype targets are then constructed comprising the following parameters: the phoneme symbol, the average peak height of the phoneme similarity score, the average peak location and the left and right frame locations. For each target a statistical weight is assigned representing the percentage of occurrences the particular high similarity region occurred across all speakers. The word prototype is feature-based allowing a robust speech representation to be constructed without the need for frame-by-frame analysis.