Patents Examined by Shaun Roberts
  • Patent number: 10002621
    Abstract: Apparatus for decoding an encoded audio signal including an encoded core signal, including: a core decoder for decoding the encoded core signal to obtain a decoded core signal; a tile generator for generating one or more spectral tiles having frequencies not included in the decoded core signal using a spectral portion of the decoded core signal; and a cross-over filter for spectrally cross-over filtering the decoded core signal and a first frequency tile having frequencies extending from a gap filling frequency to an upper border frequency or for spectrally cross-over filtering a first frequency tile and a second frequency tile.
    Type: Grant
    Filed: January 20, 2016
    Date of Patent: June 19, 2018
    Assignee: Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V.
    Inventors: Sascha Disch, Ralf Geiger, Christian Helmrich, Frederik Nagel, Christian Neukam, Konstantin Schmidt, Michael Fischer
  • Patent number: 9947330
    Abstract: An improved concept for coding sample values of a spectral envelope is obtained by combining spectrotemporal prediction on the one hand and context-based entropy coding the residuals, on the other hand, while particularly determining the context for a current sample value dependent on a measure of a deviation between a pair of already coded/decoded sample values of the spectral envelope in a spectrotemporal neighborhood of the current sample value. The combination of the spectrotemporal prediction on the one hand and the context-based entropy coding of the prediction residuals with selecting the context depending on the deviation measure on the other hand harmonizes with the nature of spectral envelopes.
    Type: Grant
    Filed: January 19, 2016
    Date of Patent: April 17, 2018
    Assignee: Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V.
    Inventors: Florin Ghido, Andreas Niedermeier
  • Patent number: 9940930
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for securing audio data. In one aspect, a method includes restricting access by the device to audio information detected by a microphone, receiving data indicating that the device is authorized to access audio information detected by the microphone during a limited period of time, and in response to receiving data indicating that the device is authorized to access audio information detected by the microphone during the limited period of time, providing audio information to the device. The method also includes monitoring audio information detected by the microphone during the limited period of time for the presence of a hotword and after the end of the limited period of time, restricting access by the device to audio information detected by the microphone.
    Type: Grant
    Filed: December 7, 2016
    Date of Patent: April 10, 2018
    Inventors: Lee Campbell, Samuel Kramer Beder
  • Patent number: 9928231
    Abstract: Topics are determined for short text messages using an unsupervised topic model. In a training corpus created from a number of short text messages, a vocabulary of words is identified, and for each word a distributed vector representation is obtained by processing windows of the corpus having a fixed length. The corpus is modeled as a Gaussian mixture model in which Gaussian components represent topics. To determine a topic of a sample short text message, a posterior distribution over the corpus topics is obtained using the Gaussian mixture model.
    Type: Grant
    Filed: January 9, 2017
    Date of Patent: March 27, 2018
    Inventor: Vivek Kumar Rangarajan Sridhar
  • Patent number: 9922027
    Abstract: Approaches presented herein enable assignment of translated work to an agent in a customer support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming customer communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the customer communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.
    Type: Grant
    Filed: January 4, 2017
    Date of Patent: March 20, 2018
    Assignee: International Business Machines Corporation
    Inventors: Gary R. Brophy, Dennis D. Koski, Todd A. Mueller, Jeffrey A. Schmidt
  • Patent number: 9916829
    Abstract: A user seeking information relevant to the purchase of a home improvement product or other product submits a query to an automated system. The system transforms the user's voice query into a text statement and searches a knowledge base for candidate responses. Quality scores for the candidate responses are determined. If no candidate response having at least a minimum quality score is identified, the query is sent to a second device associated with an agent. The agent response is provided to the user and stored in the knowledge base for future use.
    Type: Grant
    Filed: August 15, 2013
    Date of Patent: March 13, 2018
    Assignee: Home Depot Product Authority, LLC
    Inventors: Ian O'Neal Beckford, Michael L. Guhl, Anees Haidri, Kevin James Scholz, Paul Sterk
  • Patent number: 9905219
    Abstract: According to one embodiment, a speech synthesis apparatus is provided with generation, normalization, interpolation and synthesis units. The generation unit generates a first parameter using a prosodic control dictionary of a target speaker and one or more second parameters using a prosodic control dictionary of one or more standard speakers based on language information for an input text. The normalization unit normalizes the one or more second parameters based a normalization parameter. The interpolation unit interpolates the first parameter and the one or more normalized second parameters based on weight information to generate a third parameter and the synthesis unit generates synthesized speech using the third parameter.
    Type: Grant
    Filed: August 16, 2013
    Date of Patent: February 27, 2018
    Assignee: Kabushiki Kaisha Toshiba
    Inventors: Kentaro Tachibana, Takehiko Kagoshima, Masahiro Morita
  • Patent number: 9881620
    Abstract: Provided are, among other things, systems, methods and techniques for compressing an audio signal. According to one representative embodiment, an audio signal that includes quantization indexes, identification of segments of such quantization indexes, and indexes of entropy codebooks that have been assigned to such segments is obtained, with a single entropy codebook index having been assigned to each such segment. Potential merging operations in which adjacent ones of the segments potentially would be merged with each are identified, and bit penalties for the potential merging operations are estimated. At least one of the potential merging operations is performed based on the estimated bit penalties, thereby obtaining a smaller updated set of segments of quantization indexes and corresponding assigned codebooks. The quantization indexes in each of the segments in the smaller updated set are then entropy encoded by using the corresponding assigned entropy codebooks, thereby compressing the audio signal.
    Type: Grant
    Filed: December 4, 2016
    Date of Patent: January 30, 2018
    Assignee: Digital Rise Technology Co., Ltd.
    Inventor: Yuli You
  • Patent number: 9875747
    Abstract: A sensor device may include a computing device in communication with multiple microphones. A neural network executing on the computing device may receive audio signals from each microphone. One microphone signal may serve as a reference signal. The neural network may extract differences in signal characteristics of the other microphone signals as compared to the reference signal. The neural network may combine these signal differences into a lossy compressed signal. The sensor device may transmit the lossy compressed signal and the lossless reference signal to a remote neural network executing in a cloud computing environment for decompression and sound recognition analysis.
    Type: Grant
    Filed: July 15, 2016
    Date of Patent: January 23, 2018
    Assignee: GOOGLE LLC
    Inventors: Chanwoo Kim, Rajeev Conrad Nongpiur, Tara Sainath
  • Patent number: 9866938
    Abstract: A microphone system includes a first transducer deployed at a first microphone; a second transducer deployed at a second microphone, the first microphone being physically distinct from the second microphone; a decimator deployed at the second microphone that receives first pulse density modulation (PDM) data from the first transducer and second PDM data from the second transducer and decimates and combines the first PDM data and the second PDM data into combined pulse code modulation (PCM) data; and an interpolator deployed at the second microphone for converting the combined PCM data to combined PDM data, and transmits the combined PDM data to an external processing device.
    Type: Grant
    Filed: February 4, 2016
    Date of Patent: January 9, 2018
    Assignee: Knowles Electronics, LLC
    Inventors: Robert Popper, Dibyendu Nandy, Ramanujapuram Raghuvir, Sarmad Qutub, Oddy Khamharn
  • Patent number: 9858263
    Abstract: A method for predicting a canonical form for an input text sequence includes predicting the canonical form with a neural network model. The model includes an encoder, which generates a first representation of the input text sequence based on a representation of n-grams in the text sequence and a second representation of the input text sequence generated by a first neural network. The model also includes a decoder which sequentially predicts terms of the canonical form based on the first and second representations and a predicted prefix of the canonical form. The canonical form can be used, for example, to query a knowledge base or to generate a next utterance in a discourse.
    Type: Grant
    Filed: May 5, 2016
    Date of Patent: January 2, 2018
    Assignees: Conduent Business Services, LLC, Centre National De La Recherche Scientifique
    Inventors: Chunyang Xiao, Marc Dymetman, Claire Gardent
  • Patent number: 9858945
    Abstract: The present document relates to audio source coding systems which make use of a harmonic transposition method for high frequency reconstruction (HFR), as well as to digital effect processors, e.g. exciters, where generation of harmonic distortion add brightness to the processed signal, and to time stretchers where a signal duration is prolonged with maintained spectral content. A system and method configured to generate a time stretched and/or frequency transposed signal from an input signal is described. The system comprises an analysis filterbank configured to provide an analysis subband signal from the input signal; wherein the analysis subband signal comprises a plurality of complex valued analysis samples, each having a phase and a magnitude. Furthermore, the system comprises a subband processing unit configured to determine a synthesis subband signal from the analysis subband signal using a subband transposition factor Q and a subband stretch factor S.
    Type: Grant
    Filed: July 10, 2017
    Date of Patent: January 2, 2018
    Assignee: Dolby International AB
    Inventor: Lars Villemoes
  • Patent number: 9852743
    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic emphasis of spoken words. In one embodiment, a process may begin by identifying, within an audio recording, a word that is to be emphasized. Once identified, contextual and lexical information relating to the emphasized word can be extracted from the audio recording. This contextual and lexical information can be utilized in conjunction with a predictive model to determine a set of emphasis parameters for the identified word. These emphasis parameters can then be applied to the identified word to cause the word to be emphasized. Other embodiments may be described and/or claimed.
    Type: Grant
    Filed: November 20, 2015
    Date of Patent: December 26, 2017
    Assignee: Adobe Systems Incorporated
    Inventors: Yang Zhang, Gautham J. Mysore, Floraine Berthouzoz
  • Patent number: 9842588
    Abstract: A method and a device of voice recognition are provided. The method involves receiving a voice signal, identifying a first voice recognition model in which context information associated with a situation at reception of the voice signal is not reflected and a second voice recognition model in which the context information is reflected, determining a weighted value of the first voice recognition model and a weighted value of the second voice recognition model, and recognizing a word in the voice signal by applying the determined weighted values to the first voice recognition model and the second voice recognition model.
    Type: Grant
    Filed: February 6, 2015
    Date of Patent: December 12, 2017
    Assignee: Samsung Electronics Co., Ltd.
    Inventors: Hyun-Jun Kim, Young Sang Choi
  • Patent number: 9830315
    Abstract: A system and method are provided which employ a neural network model which has been trained to predict a sequentialized form for an input text sequence. The sequentialized form includes a sequence of symbols. The neural network model includes an encoder which generates a representation of the input text sequence based on a representation of n-grams in the text sequence and a decoder which sequentially predicts a next symbol of the sequentialized form based on the representation and a predicted prefix of the sequentialized form. Given an input text sequence, a sequentialized form is predicted with the trained neural network model. The sequentialized form is converted to a structured form and information based on the structured form is output.
    Type: Grant
    Filed: July 13, 2016
    Date of Patent: November 28, 2017
    Assignees: XEROX CORPORATION, Centre National de la Recherche Scientifique
    Inventors: Chunyang Xiao, Marc Dymetman, Claire Gardent
  • Patent number: 9830920
    Abstract: A method, device, and apparatus provide the ability to predict a portion of a polyphonic audio signal for compression and networking applications. The solution involves a framework of a cascade of long term prediction filters, which by design is tailored to account for all periodic components present in a polyphonic signal. This framework is complemented with a design method to optimize the system parameters. Specialization may include specific techniques for coding and networking scenarios, where the potential of each enhanced prediction is realized to considerably improve the overall system performance for that application. One specific technique provides enhanced inter-frame prediction for the compression of polyphonic audio signals, particularly at low delay. Another specific technique provides improved frame loss concealment capabilities to combat packet loss in audio communications.
    Type: Grant
    Filed: June 29, 2016
    Date of Patent: November 28, 2017
    Assignee: The Regents of the University of California
    Inventors: Kenneth Rose, Tejaswi Nanjundaswamy
  • Patent number: 9817818
    Abstract: A method and computer system for translating sentences between languages from an intermediate language-independent semantic representation is provided. On the basis of comprehensive understanding about languages and semantics, exhaustive linguistic descriptions are used to analyze sentences, to build syntactic structures and language independent semantic structures and representations, and to synthesize one or more sentences in a natural or artificial language. A computer system is also provided to analyze and synthesize various linguistic structures and to perform translation of a wide spectrum of various sentence types. As result, a generalized data structure, such as a semantic structure, is generated from a sentence of an input language and can be transformed into a natural sentence expressing its meaning correctly in an output language.
    Type: Grant
    Filed: May 21, 2012
    Date of Patent: November 14, 2017
    Inventors: Konstantin Anisimovich, Vladimir Selegey, Konstantin Zuev
  • Patent number: 9807217
    Abstract: A computer-implemented method of determining when an audio notification should be generated includes detecting receipt of a triggering event that occurs on a user device; generating, based on detecting, the audio notification for the triggering event; receiving, from the user device, a user voice command responding to the audio notification; and generating a response to the user voice command based on one or more of (i) information associated with the audio notification, and (ii) information associated with the user voice command.
    Type: Grant
    Filed: April 21, 2016
    Date of Patent: October 31, 2017
    Assignee: Google Inc.
    Inventors: Michael J. LeBeau, John Nicholas Jitkoff
  • Patent number: 9807473
    Abstract: Video description generation using neural network training based on relevance and coherence is described. In some examples, long short-term memory with visual-semantic embedding (LSTM-E) can maximize the probability of generating the next word given previous words and visual content and can create a visual-semantic embedding space for enforcing the relationship between the semantics of an entire sentence and visual content. LSTM-E can include a 2-D and/or 3-D deep convolutional neural networks for learning powerful video representation, a deep recurrent neural network for generating sentences, and a joint embedding model for exploring the relationships between visual content and sentence semantics.
    Type: Grant
    Filed: November 20, 2015
    Date of Patent: October 31, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Tao Mei, Ting Yao, Yong Rui
  • Patent number: 9805732
    Abstract: Embodiments of the present application proposes a frequency envelope vector quantization method and apparatus, where the method includes: dividing N frequency envelopes in one frame into N1 vectors; quantizing a first vector in the N1 vectors by using a first codebook, to obtain a code word corresponding to the quantized first vector, where the first codebook is divided into 2B1 portions; determining, according to the code word corresponding to the quantized first vector; determining a second codebook according to the codebook of the ith portion; and quantizing a second vector in the N1 vectors based on the second codebook. In the embodiments of the present application, vector quantization can be performed on frequency envelope vectors by using a codebook with a smaller quantity of bits. Therefore, complexity of vector quantization can be reduced, and an effect of vector quantization can also be ensured.
    Type: Grant
    Filed: December 29, 2015
    Date of Patent: October 31, 2017
    Inventors: Chen Hu, Lei Miao, Zexin Liu