Abstract: An apparatus, method, and computer program for initiating a word spotting algorithm (220) on one or more wireless communication devices in a first power mode to detect a keyword data sequence (224) embedded within a sampled audio signal (222). In response to detecting the keyword data sequence (226), the word spotting algorithm is terminated and a plurality of identification algorithms (230) consisting of speech, voice, image recognition and a predetermined isolation time criterion are initiated on the one or more wireless communication devices operating in a second power mode to detect the presence of identification data (240). If identification data is detected on a particular wireless communication device it is activated to accept speech and/or voice commands (242).

Abstract: A user is identified and an in-place personalized interactive display provided by detecting, via a first imaging system, one or more unique characteristics of a user's palm, identifying the user via the one or more unique characteristics and a database containing mappings between detectable unique characteristics and user identities, retrieving user-specific interactive content as a function of the identity of the user, projecting, via a second imaging system, the user-specific interactive content onto the user's palm, and detecting, via a third imaging system, a user's interaction with the projected user-specific interactive content. The user may be identified by transmitting the one or more unique characteristics to a remote authentication server and receiving, in response, an identity of the user. User-specific content as a function of the identity of the user may be retrieved from a remote interactive content server.

Abstract: A method for determining a relatedness between a query video and a database video is provided. A processor extracts an audio stream from the query video to produce a query audio stream, extracts an audio stream from the database video to produce a database audio stream, produces a first-sized snippet from the query audio stream, and produces a first-sized snippet from the database audio stream. An estimation is made of a first most probable sequence of latent evidence probability vectors generating the first-sized audio snippet of the query audio stream. An estimation is made of a second most probable sequence of latent evidence probability vectors generating the first-sized audio snippet of the database audio stream. A similarity is measured between the first sequence and the second sequence producing a score of relatedness between the two snippets. Finally a relatedness is determined between the query video and a database video.

Abstract: A user is identified and an in-place personalized interactive display provided by detecting, via a first imaging system, one or more unique characteristics of a user's palm, identifying the user via the one or more unique characteristics and a database containing mappings between detectable unique characteristics and user identities, retrieving user-specific interactive content as a function of the identity of the user, projecting, via a second imaging system, the user-specific interactive content onto the user's palm, and detecting, via a third imaging system, a user's interaction with the projected user-specific interactive content. The user may be identified by transmitting the one or more unique characteristics to a remote authentication server and receiving, in response, an identity of the user. User-specific content as a function of the identity of the user may be retrieved from a remote interactive content server.

Abstract: A method and user terminal are provided that graphically formulate a search query. The method and user terminal display, via a display screen, a multi-dimensional graphical representation of a search query space, receive a plurality of parameters from a user, wherein the parameters define the search query space, position a multi-dimensional icon in the multi-dimensional representation of the search query space, associate one or more of a keyword and multimedia content with the icon, and generate a search query based on the keyword and the position of the icon in the multi-dimensional representation of the search query space. The method and user terminal further may graphically display the results of the corresponding database search, wherein the retrieved content is displayed as one or more icons positioned in a multi-dimensional graph having a plurality of axes associated with the plurality of parameters defining a context of the search query.

Abstract: An apparatus, method, and computer program for initiating a word spotting algorithm (220) on one or more wireless communication devices in a first power mode to detect a keyword data sequence (224) embedded within a sampled audio signal (222). In response to detecting the keyword data sequence (226), the word spotting algorithm is terminated and a plurality of identification algorithms (230) are initiated on the one or more wireless communication devices operating in a second power mode to detect the presence of identification data (240). If identification data is detected on a particular wireless communication device it is activated to accept speech and/or voice commands (242). On the other hand, if identification data is not detected, the plurality of identification algorithms are terminated, and the word spotting algorithm is reinitiated on the one or more wireless communication devices that are then operating in the first power mode (244).

Abstract: A method for determining a relatedness between a query video and a database video is provided. A processor extracts an audio stream from the query video to produce a query audio stream, extracts an audio stream from the database video to produce a database audio stream, produces a first-sized snippet from the query audio stream, and produces a first-sized snippet from the database audio stream. An estimation is made of a first most probable sequence of latent evidence probability vectors generating the first-sized audio snippet of the query audio stream. An estimation is made of a second most probable sequence of latent evidence probability vectors generating the first-sized audio snippet of the database audio stream. A similarity is measured between the first sequence and the second sequence producing a score of relatedness between the two snippets. Finally a relatedness is determined between the query video and a database video.

Abstract: A method of performing a search of a database of speakers, includes: receiving a query speech sample spoken by a query speaker; deriving a query utterance from the query speech sample; extracting query utterance statistics from the query utterance; performing Kernelized Locality-Sensitive Hashing (KLSH) using a kernel function, the KLSH using as input the query utterance statistics and utterance statistics extracted from a plurality of utterances included in a database of speakers in order to select a subset of the plurality of utterances; and comparing, using an utterance comparison equation, the query utterance statistics to the utterance statistics for each utterance in the subset to generate a list of speakers from the database of utterances having a highest similarity to the query speaker.

Abstract: A method of performing a search of a database of speakers, includes: receiving a query speech sample spoken by a query speaker; deriving a query utterance from the query speech sample; extracting query utterance statistics from the query utterance; performing Kernelized Locality-Sensitive Hashing (KLSH) using a kernel function, the KLSH using as input the query utterance statistics and utterance statistics extracted from a plurality of utterances included in a database of speakers in order to select a subset of the plurality of utterances; and comparing, using an utterance comparison equation, the query utterance statistics to the utterance statistics for each utterance in the subset to generate a list of speakers from the database of utterances having a highest similarity to the query speaker.

Abstract: A method and apparatus for robust speech activity detection is disclosed. The method may include calculating autocorrelations by filtering input signals using order statistic filtering, averaging the autocorrelations over a time period, obtaining a voiced speech feature from the averaged autocorrelations, classifying the input signal as one of speech and non-speech based on the obtained voiced speech feature, and outputting only the classified speech signals or the input signals along with the speech/non-speech classification information, to an automated speech recognizer.

Abstract: A voice sample characterization front-end suitable for use in a distributed speech recognition context. A digitized voice sample 31 is split between a low frequency path 32 and a high frequency path 33. Both paths are used to determine spectral content suitable for use when determining speech recognition parameters (such as cepstral coefficients) that characterize the speech sample for recognition purposes. The low frequency path 32 has a thorough noise reduction capability. In one embodiment, the results of this noise reduction are used by the high frequency path 33 to aid in de-noising without requiring the same level of resource capacity as used by the low frequency path 32.

Abstract: A voice sample characterization front-end suitable for use in a distributed speech recognition context. A digitized voice sample 31 is split between a low frequency path 32 and a high frequency path 33. Both paths are used to determine spectral content suitable for use when determining speech recognition parameters (such as cepstral coefficients) that characterize the speech sample for recognition purposes. The low frequency path 32 has a thorough noise reduction capability. In one embodiment, the results of this noise reduction are used by the high frequency path 33 to aid in de-noising without requiring the same level of resource capacity as used by the low frequency path 32.

Abstract: A system for enhancing the signal-to-noise ratio of a speech signal is avoided. A plurality of local energy maximums associated with a speech signal are determined. Presumably, each of these local energy maximums defines a speech pitch period. Typically, human pitch periods are approximately 100-400 Hz depending on the sex and age of the speaker. Because human speech typically includes more energy near the beginning of a pitch period than at the end of the pitch period, and background noise tends to remain relatively constant throughout the pitch period, the speech signal may be enhanced by increasing the energy associated with the beginning of the pitch period and/or by decreasing the energy associated with the end of the pitch period. Preferably, the amount of energy increase in the earlier portion of the pitch period is approximately equal to the amount of energy reduction in the later portion of the pitch period. In this manner, the total energy remains the constant.

Abstract: A system for enhancing the signal-to-noise ratio of a speech signal is disclosed. A plurality of local energy maximums associated with a speech signal are determined. Presumably, each of these local energy maximums defines a speech pitch period. Typically, human pitch periods are approximately 100-400 Hz depending on the sex and age of the speaker. Because human speech typically includes more energy near the beginning of a pitch period than at the end of the pitch period, and background noise tends to remain relatively constant throughout the pitch period, the speech signal may be enhanced by increasing the energy associated with the beginning of the pitch period and/or by decreasing the energy associated with the end of the pitch period. Preferably, the amount of energy increase in the earlier portion of the pitch period is approximately equal to the amount of energy reduction in the later portion of the pitch period. In this manner, the total energy remains the constant.