Patent application number | Description | Published |
20130331674 | APPLICATION OF ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY IN SENSOR SYSTEMS, DEVICES, AND RELATED METHODS - A diagnostic Electrochemical Impedance Spectroscopy (EIS) procedure is applied to measure values of impedance-related parameters for one or more sensing electrodes. The parameters may include real impedance, imaginary impedance, impedance magnitude, and/or phase angle. The measured values of the impedance-related parameters are then used in performing sensor diagnostics, calculating a highly-reliable fused sensor glucose value based on signals from a plurality of redundant sensing electrodes, calibrating sensors, detecting interferents within close proximity of one or more sensing electrodes, and testing surface area characteristics of electroplated electrodes. Advantageously, impedance-related parameters can be defined that are substantially glucose-independent over specific ranges of frequencies. An Application Specific Integrated Circuit (ASIC) enables implementation of the EIS-based diagnostics, fusion algorithms, and other processes based on measurement of EIS-based parameters. | 12-12-2013 |
20130331676 | APPLICATION OF ELECTROCHEMICAL IMPEDANCE SPECTROSCOPY IN SENSOR SYSTEMS, DEVICES, AND RELATED METHODS - A diagnostic Electrochemical Impedance Spectroscopy (EIS) procedure is applied to measure values of impedance-related parameters for one or more sensing electrodes. The parameters may include real impedance, imaginary impedance, impedance magnitude, and/or phase angle. The measured values of the impedance-related parameters are then used in performing sensor diagnostics, calculating a highly-reliable fused sensor glucose value based on signals from a plurality of redundant sensing electrodes, calibrating sensors, detecting interferents within close proximity of one or more sensing electrodes, and testing surface area characteristics of electroplated electrodes. Advantageously, impedance-related parameters can be defined that are substantially glucose-independent over specific ranges of frequencies. An Application Specific Integrated Circuit (ASIC) enables implementation of the EIS-based diagnostics, fusion algorithms, and other processes based on measurement of EIS-based parameters. | 12-12-2013 |
Patent application number | Description | Published |
20130121495 | Sound Mixture Recognition - A sound mixture may be received that includes a plurality of sources. A model may be received that includes a dictionary of spectral basis vectors for the plurality of sources. A weight may be estimated for each of the plurality of sources in the sound mixture based on the model. In some examples, such weight estimation may be performed using a source separation technique without actually separating the sources. | 05-16-2013 |
20130121506 | Online Source Separation - Online source separation may include receiving a sound mixture that includes first audio data from a first source and second audio data from a second source. Online source separation may further include receiving pre-computed reference data corresponding to the first source. Online source separation may also include performing online separation of the second audio data from the first audio data based on the pre-computed reference data. | 05-16-2013 |
20130124200 | Noise-Robust Template Matching - Noise robust template matching may be performed. First features of a first signal may be computed. Based at least on a portion of the first features, second features of a second signal may be computed. A new signal may be generated based on at least another portion of the first features and on at least a portion of the second features. | 05-16-2013 |
20130124462 | Clustering and Synchronizing Content - Clustering and synchronizing content may include extracting audio features for each of a plurality of files that include audio content. The plurality of files may be clustered into one or more clusters. Clustering may include clustering based on a histogram that may be generated for each file pair of the plurality of files. Within each of the clusters, the files of the cluster may be time aligned. | 05-16-2013 |
20130132077 | Semi-Supervised Source Separation Using Non-Negative Techniques - Systems and methods for semi-supervised source separation using non-negative techniques are described. In some embodiments, various techniques disclosed herein may enable the separation of signals present within a mixture, where one or more of the signals may be emitted by one or more different sources. In audio-related applications, for instance, a signal mixture may include speech (e.g., from a human speaker) and noise (e.g., background noise). In some cases, speech may be separated from noise using a speech model developed from training data. A noise model may be created, for example, during the separation process (e.g., “on-the-fly”) and in the absence of corresponding training data. | 05-23-2013 |
20130132082 | Systems and Methods for Concurrent Signal Recognition - Methods and systems for recognition of concurrent, superimposed, or otherwise overlapping signals are described. A Markov Selection Model is introduced that, together with probabilistic decomposition methods, enable recognition of simultaneously emitted signals from various sources. For example, a signal mixture may include overlapping speech from different persons. In some instances, recognition may be performed without the need to separate signals or sources. As such, some of the techniques described herein may be useful in automatic transcription, noise reduction, teaching, electronic games, audio search and retrieval, medical and scientific applications, etc. | 05-23-2013 |
20130132085 | Systems and Methods for Non-Negative Hidden Markov Modeling of Signals - Methods and systems for non-negative hidden Markov modeling of signals are described. For example, techniques disclosed herein may be applied to signals emitted by one or more sources. In some embodiments, methods and systems may enable the separation of a signal's various components. As such, the systems and methods disclosed herein may find a wide variety of applications. In audio-related fields, for example, these techniques may be useful in music recording and processing, source extraction, noise reduction, teaching, automatic transcription, electronic games, audio search and retrieval, and many other applications. | 05-23-2013 |
20130226558 | Language Informed Source Separation - Methods and systems for non-negative hidden Markov modeling of signals are described. For example, techniques disclosed herein may be applied to signals emitted by one or more sources. The modeling may be constrained according to high level information. In some embodiments, methods and systems may enable the separation of a signal's various components. As such, the systems and methods disclosed herein may find a wide variety of applications. In audio-related fields, for example, these techniques may be useful in music recording and processing, source separation/extraction, noise reduction, teaching, automatic transcription, electronic games, audio search and retrieval, and many other applications. | 08-29-2013 |
20130226858 | Feature Estimation in Sound Sources - A sound mixture may be received that includes a plurality of sources. A model may be received for one of the source that includes a dictionary of spectral basis vectors corresponding to that one source. At least one feature of the one source in the sound mixture may be estimated based on the model. In some examples, the estimation may be constrained according to temporal data. | 08-29-2013 |
20140133675 | Time Interval Sound Alignment - Time interval sound alignment techniques are described. In one or more implementations, one or more inputs are received via interaction with a user interface that indicate that a first time interval in a first representation of sound data generated from a first sound signal corresponds to a second time interval in a second representation of sound data generated from a second sound signal. A stretch value is calculated based on an amount of time represented in the first and second time intervals, respectively. Aligned sound data is generated from the sound data for the first and second time intervals based on the calculated stretch value. | 05-15-2014 |
20140135962 | Sound Alignment using Timing Information - Sound alignment techniques that employ timing information are described. In one or more implementations, features and timing information of sound data generated from a first sound signal are identified and used to identify features of sound data generated from a second sound signal. The identified features may then be utilized to align portions of the sound data from the first and second sound signals to each other. | 05-15-2014 |
20140136976 | Sound Alignment User Interface - Sound alignment user interface techniques are described. In one or more implementations, a user interface is output having a first representation of sound data generated from a first sound signal and a second representation of sound data generated from a second sound signal. One or more inputs are received, via interaction with the user interface, that indicate that a first point in time in the first representation corresponds to a second point in time in the second representation. Aligned sound data is generated from the sound data from the first and second sound signals based at least in part on correspondence of the first point in time in the sound data generated from the first sound signal to the second point in time in the sound data generated from the second sound signal. | 05-15-2014 |
20140140517 | Sound Data Identification - Sound data identification techniques are described. In one or more implementations, common sound data and uncommon sound data are identified from a plurality of sound data from a plurality of recordings of an audio source using a collaborative technique. The identification may include recognition of spectral and temporal aspects of the plurality of the sound data from the plurality of the recordings and sharing of the recognized spectral and temporal aspects to identify the common sound data as common to the plurality of recordings and the uncommon sound data as not common to the plurality of recordings. | 05-22-2014 |
20140142947 | Sound Rate Modification - Sound rate modification techniques are described. In one or more implementations, an indication is received of an amount that a rate of output of sound data is to be modified. One or more sound rate rules are applied to the sound data that, along with the received indication, are usable to calculate different rates at which different portions of the sound data are to be modified, respectively. The sound data is then output such that the calculated rates are applied. | 05-22-2014 |
20140148933 | Sound Feature Priority Alignment - Sound feature priority alignment techniques are described. In one or more implementations, features of sound data are identified from a plurality of recordings. Values are calculated for frames of the sound data from the plurality of recordings. The values are based on similarity of the frames of the sound data from the plurality of recordings to each other, the similarity based on the identified features and a priority that is assigned based on the identified features of respective frames. The sound data from the plurality of recordings is then aligned based at least in part on the calculated values. | 05-29-2014 |
20150134691 | Pattern Matching of Sound Data using Hashing - Pattern matching of sound data using hashing is described. In one or more implementations, a query formed from one or more spectrograms of sound data is hashed and used to locate one or more labels in a database of sound signals. Each of the labels is located using a hash of an entry in the database. At least one of the located one or more labels is chosen as corresponding to the query. | 05-14-2015 |
20150142433 | Irregular Pattern Identification using Landmark based Convolution - Pattern identification using convolution is described. In one or more implementations, a representation of a pattern is obtained that is described using data points that include frequency coordinates, time coordinates, and energy values. An identification is made as to whether sound data described using irregularly positioned data points includes the pattern, the identifying including use of a convolution of the frequency or time coordinates to determine correspondence with the representation of the pattern. | 05-21-2015 |
20150181359 | Multichannel Sound Source Identification and Location - Multichannel sound source identification and location techniques are described. In one or more implementations, source separation is performed using a collaborative technique for a plurality of sound data that was captured by respective ones of a plurality of sound capture devices of an audio scene. The source separation is performed by recognizing spectral and temporal aspects from the plurality of sound data and sharing the recognized spectral and temporal aspects, one with another, to identify one or more sound sources in the audio scene. A relative position of the identified one or more sounds sources to the plurality of sound capture devices is determined based on the source separation. | 06-25-2015 |
Patent application number | Description | Published |
20090048846 | Method for Expanding Audio Signal Bandwidth - A method expands a bandwidth of an audio signal by determining a magnitude time-frequency representation |G(ω,t) for example audio signals g(t). A set of frequency marginal probabilities P | 02-19-2009 |
20090062942 | Method and System for Matching Audio Recording - Our invention describes a method and a system for matching securely an unknown audio recording with known audio recordings. A plurality of known audio recordings, each known audio recording associated with an index to information uniquely identifying the known audio recording is stored on a server. An unknown audio recording cross-correlated securely with each of the plurality of known audio recordings to determine a best matching known audio recording, in which the unknown audio recording and the plurality of known audio recordings are encrypted with a public key. A best matching known audio recording is determined securely according to the cross-correlation. Next, the index of the best matching known audio recording is determined securely. Finally, the information associated with the index of the best matching known audio recording is provided securely to a user of the unknown recording. | 03-05-2009 |
20090132245 | Denoising Acoustic Signals using Constrained Non-Negative Matrix Factorization - A method and system denoises a mixed signal. A constrained non-negative matrix factorization (NMF) is applied to the mixed signal. The NMF is constrained by a denoising model, in which the denoising model includes training basis matrices of a training acoustic signal and a training noise signal and statistics of weights of the training basis matrices. The applying produces weight of a basis matrix of the acoustic signal, of the mixed signal. A product of the weights of the basis matrix of the acoustic signal and the training basis matrices of the training acoustic signal and the training noise signal is taken to reconstruct the acoustic signal. The mixed signal can be speech and noise. | 05-21-2009 |
20100054694 | COMBINED VISUAL AND AUDITORY PROCESSING - A computer-implemented method includes segmenting a plurality of video frames of a sequence of video frames into a first portion that includes a selected visual object represented in the video frame and a second portion that includes a background represented in the video frame. The selected visual object is selected by using a selection envelope. | 03-04-2010 |
20130121497 | System and Method for Acoustic Echo Cancellation Using Spectral Decomposition - A method and apparatus for canceling an echo in audio communication is disclosed. The method comprises receiving an audio signal from a network and subsequently detecting a mixture audio signal comprising a target audio signal and an echo audio signal, the echo signal corresponding to the received audio signal. The method then comprises estimating the target audio signal by determining magnitude spectrograms for the mixture and received audio signals respectively, estimating a magnitude spectrogram of the target audio signal dependent on those of the mixture and received audio signal, and generating an output audio signal that estimates the target audio signal, the output audio signal being dependent on the estimated magnitude spectrogram. | 05-16-2013 |
20130121511 | User-Guided Audio Selection from Complex Sound Mixtures - A system and method are described for selecting a target sound object from a sound mixture. In embodiments, a sound mixture comprises a plurality of sound objects superimposed in time. A user can select one of these sound objects by providing reference audio data corresponding to a reference sound object. The system analyzes the audio data and the reference audio data to identify a portion of the audio data corresponding to a target sound object in the mixture that is most similar to the reference sound object. The analysis may include decomposing the reference audio data into a plurality of reference components and the sound mixture into a plurality of components guided by the reference components. The target sound object can be re-synthesized from the target components. | 05-16-2013 |
20130129115 | System and Method for Dynamic Range Extension Using Interleaved Gains - A method and system is presented for sampling analog signals in a manner that avoids the effects of signal clipping due to a limited dynamic range. A method and device for sampling an analog input using multiple gains, or gain mask, is described. By using different gains during different time quanta, a subset of the sampled points may effectively be attenuated before being sampled and converted to a digital representation. If clipping occurs during the sampling process, the true values of the clipped samples may be interpolated using the amplitudes of the non-clipped samples, which may not have been attenuated. Such interpolation may include constructing and/or solving a constraint optimization problem using linear programming. In one embodiment, such a problem may be constructed and/or solved by using sign information from the clipped samples and/or by imposing a sparsity assumption on the signals during the reconstruction process. | 05-23-2013 |