Matsushita Electric Industrial Co., Ltd.

Google Inc.

Datalogic Adc, Inc.

Technology Research Association of Medical Welfare Apparatus

Robert C Boman

Jean-Claude Junqua

Luca Rigazio

Roland Kuhn

Patrick Nguyen

Brian A Hanson

Philippe Rene Morin

Ted H Applebaum

Christophe Cerisara

Luis F Goncalves

Matteo Contolini

John Patrick Flynn

Peter Veprek

Michael Galler

Hector Raul Javkin

Farhana Bandukwala

Nancy Niedzielski

Rathinavelu Chengalvarayan

Kirill Stoimenov

James Ostrowski

Olivier Thyes

Implementations relate to verifying labels for images using image recognition. In some implementations, a method includes obtaining an image associated with location information, obtaining one or more descriptor labels associated with the location information, determining one or more recognized image features depicted in the image, comparing the recognized image features with the descriptor labels, and determining one or more verified labels from the one or more descriptor labels. The verified labels are determined to describe at least one of the one or more recognized image features depicted in the image based on the comparing of the recognized image features with the descriptor labels.

Verifying labels for images using image recognition

A system and method for detecting the presence of known or unknown objects based on visual features is disclosed. In the preferred embodiment, the system is a checkout system for detecting items of merchandise on a shopping cart. The merchandise checkout system preferably includes a feature extractor for extracting visual features from a plurality of images; a motion detector configured to detect one or more groups of the visual features present in at least two of the plurality of images; a classifier to classify each of said groups of the visual features based on one or more classification criteria, wherein each of the one or more parameters is associated with one of said groups of visual features; and an alarm configured to generate an alert if the one or more parameters for any of said groups of the visual features satisfy one or more classification criteria.

System and method for detecting generic items in image sequence

A media capture device has an audio input receptive of user speech relating to a media capture activity in close temporal relation to the media capture activity. A plurality of focused speech recognition lexica respectively relating to media capture activities are stored on the device, and a speech recognizer recognizes the user speech based on a selected one of the focused speech recognition lexica. A media tagger tags captured media with generated speech recognition text, and a media annotator annotates the captured media with a sample of the user speech that is suitable for input to a speech recognizer. Tagging and annotating are based on close temporal relation between receipt of the user speech and capture of the captured media. Annotations may be converted to tags during post processing, employed to edit a lexicon using letter-to-sound rules and spelled word input, or matched directly to speech to retrieve captured media.

Voice tagging, voice annotation, and speech recognition for portable devices with optional post processing

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.

System and method of media content distribution employing portable media content distribution device

The vehicular monitoring system obtains audio information from the speech of occupants within the vehicle and then processes that audio information to extract information about the behavior of the vehicle occupants. Using the behavioral information the system then assesses whether said behavior is in compliance with a predefined set of rules. Severe violations are reported to a third party via cellular telephone or other means. Less severe violations are recorded in a log file that is subsequently uploaded to a networked computer system for review and analysis. The behavioral rules used to assess violations may be modified by the administrative user.

Enhanced automotive monitoring system using sound

A personal item monitoring system includes a monitor having a transmitter and a receiver located therein. At least one radio identification tag is adapted to be coupled to a personal item. Alternatively, the radio identification tag may be pre-installed into the personal item. The monitor emits a radio frequency received by the radio frequency identification tag, and the radio frequency identification tag emits a responding signal if within a detection range. The monitor then alerts a user if the radio identification tag leaves the range of detection.

Personal item monitor using radio frequency identification

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.

Linear discriminant based sound class similarities with unit value normalization

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.

Method for efficient, safe and reliable data entry by voice under adverse conditions

Personalized agent services are provided in a personal messaging device, such as a cellular telephone or personal digital assistant, through services of a speech recognizer that converts speech into text and a text-to-speech synthesizer that converts text to speech. Both recognizer and synthesizer may be server-based or locally deployed within the device. The user dictates an e-mail message which is converted to text and stored. The stored text is sent back to the user as text or as synthesized speech, to allow the user to edit the message and correct transcription errors before sending as e-mail. The system includes a summarization module that prepares short summaries of incoming e-mail and voice mail. The user may access these summaries, and retrieve and organize email and voice mail using speech commands.

Personalized agent for portable devices and cellular phone

System speakers are switched to function as sound input transducers to improve recognizer performance and to support recognizer features. A crossbar switch is selectively activated, either manually or under software control, to allow system loudspeakers to function as sound input transducers that supplement the recognition system microphone or microphone array. Using loudspeakers as 'microphones' improves speech recognition in noisy environments, thus attaining better recognition performance with little added system cost. The loudspeakers, positioned in physically separate locations also provide spatial information that can be used to determine the location of the person speaking and thereby offer different functionality for different persons. Acoustic models are selected based on environmental and vehicle operating conditions and may be adapted dynamically using ambient information obtained using the loudspeakers as sound input transducers.

Speech recognizer performance in car and home applications utilizing novel multiple microphone configurations

The call screener employs a telephone system interface connected between a telephone network and a telephone device of a user. The interface selectively routes calls (and refrain from routing calls) based on the results from the dialogue system. The dialogue system elicits speech from an incoming caller and causes the telephone system interface to route calls from the incoming caller based on a comparison of the elicited speech with a set of stored speaker models. The stored speaker models may be maintained automatically by the system, using either a passive mode, in which calls exceeding a predetermined duration are assumed to be &ldquo;acceptable&rdquo; callers; and a proactive mode in which the system prompts the user at the end of the call to elect whether to save the speech models developed during that call in the acceptable user database. If desired, the user can attach other attributes or special tags to the stored models, indicating special handling or call routing rules to be applied when that caller calls again.

Dialogue device for call screening and classification

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.

Speaker verification and speaker identification based on a priori knowledge

A noise adaptation system and method provide for noise adaptation in a speech recognition system. The method includes the steps of generating a reference model based on a training speech signal, and compensating the reference model for additive noise in the cepstral domain. The reference model is also compensated for convolutional noise in the cepstral domain. In one embodiment, the convolutional noise is compensated for by estimating a convolutional bias between the reference model and a target speech signal. The estimated convolutional bias is transformed with a channel adaptation matrix, and the transformed convolutional bias is added to the reference model in the cepstral domain.

Method for additive and convolutional noise adaptation in automatic speech recognition using transformed matrices

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.

Method for noise adaptation in automatic speech recognition using transformed matrices

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.

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Thousand Oaks, CA, United States of America

Robert C Boman