Neural Network Patents (Class 704/232)
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Patent number: 12266373Abstract: A method and apparatus for audio processing, an electronic device and a storage medium are provided. The method includes: obtaining an audio encoding result, wherein each element in the audio encoding result has a coordinate in an audio frame number dimension and a coordinate in a text label sequence dimension; in response to an output result of an ith frame in a decoding path being a non-null character, respectively increasing the coordinate in the audio frame number dimension and the coordinate in the text label sequence dimension corresponding to an output position of the ith frame by 1 to obtain an output position of a (i+1)th frame in the decoding path; and determining an output result corresponding to the output position of the (i+1)th frame according to the output result of the ith frame in the decoding path and an element of the (i+1)th frame in the audio encoding result.Type: GrantFiled: December 9, 2022Date of Patent: April 1, 2025Assignee: BEIJING XIAOMI MOBILE SOFTWARE CO., LTD.Inventors: Mingshuang Luo, Fangjun Kuang, Liyong Guo, Long Lin, Wei Kang, Zengwei Yao, Povey Daniel
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Patent number: 12266342Abstract: A method for generating speech through multi-speaker neural text-to-speech (TTS) synthesis is provided. A text input may be received (1410). Speaker latent space information of a target speaker may be provided through at least one speaker model (1420). At least one acoustic feature may be predicted through an acoustic feature predictor based on the text input and the speaker latent space information (1430). A speech waveform corresponding to the text input may be generated through a neural vocoder based on the at least one acoustic feature and the speaker latent space information (1440).Type: GrantFiled: December 11, 2018Date of Patent: April 1, 2025Assignee: Microsoft Technology Licensing, LLCInventors: Yan Deng, Lei He
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Patent number: 12260863Abstract: In an embodiment, the disclosure relates to a device for assisting a respondent in a conversation. The device includes a microphone configured to detect a voice input, and a transmitter communicatively coupled to a server and configured to transmit the voice input to the server. The server is to generate vectors associated with the voice input, feed the vectors associated with the voice input to an Artificial Intelligence utilizing a trained Machine Learning (ML) model, and obtain, from the trained ML model, an output corresponding to the vectors. The device further includes a receiver communicatively coupled to the server, and configured to receive from the server, the output generated by the ML model. A speaker is communicatively coupled with the receiver and is configured to generate a voice-based response based on the output, for assisting the respondent in responding to the conversation.Type: GrantFiled: May 6, 2024Date of Patent: March 25, 2025Inventor: Leigh M. Rothschild
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Patent number: 12261827Abstract: Systems, methods, and apparatus, including computer programs encoded on a computer storage medium for managing network traffic to and from a server configured to: (i) receive, from a client device, a query in a natural language, and (ii) generate a response to the query in the natural language. In one aspect, a method includes: receiving, from the client device via a network connection, a network message including a new query for the server; processing the new query, using a text encoder, to generate an embedding vector of the new query; identifying, from amongst multiple entries of a vector database, a particular entry based on a similarity metric between: (i) the embedding vector of the new query, and (ii) an embedding vector of a particular query stored in the particular entry; and determining whether the similarity metric is greater than a threshold similarity value.Type: GrantFiled: January 19, 2024Date of Patent: March 25, 2025Assignee: Auradine, Inc.Inventors: Tao Xu, Barun Kar
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Patent number: 12254885Abstract: Techniques are described herein for detecting and handling failures in other automated assistants. A method includes: executing a first automated assistant in an inactive state at least in part on a computing device operated by a user; while in the inactive state, determining, by the first automated assistant, that a second automated assistant failed to fulfill a request of the user; in response to determining that the second automated assistant failed to fulfill the request of the user, the first automated assistant processing cached audio data that captures a spoken utterance of the user comprising the request that the second automated assistant failed to fulfill, or features of the cached audio data, to determine a response that fulfills the request of the user; and providing, by the first automated assistant to the user, the response that fulfills the request of the user.Type: GrantFiled: January 13, 2023Date of Patent: March 18, 2025Assignee: GOOGLE LLCInventors: Victor Carbune, Matthew Sharifi
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Patent number: 12243545Abstract: A method and system of neural network dynamic noise suppression is provided for audio processing.Type: GrantFiled: December 24, 2021Date of Patent: March 4, 2025Assignee: Intel CorporationInventors: Adam Kupryjanow, Lukasz Pindor
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Patent number: 12244792Abstract: A method of processing, prior to encoding using an external encoder, image data using an artificial neural network is provided. The external encoder is operable in a plurality of encoding modes. At the neural network, image data representing one or more images is received. The image data is processed using the neural network to generate output data indicative of an encoding mode selected from the plurality of encoding modes of the external encoder. The neural network trained to select using image data an encoding mode of the plurality of encoding modes of the external encoder using one or more differentiable functions configured to emulate an encoding process. The generated output data is outputted from the neural network to the external encoder to enable the external encoder to encode the image data using the selected encoding mode.Type: GrantFiled: June 16, 2021Date of Patent: March 4, 2025Assignee: Sony Interactive Entertainment Europe LimitedInventors: Aaron Chadha, Ioannis Andreopoulos
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Patent number: 12228476Abstract: Provided is a fault signal locating and identifying method of industrial equipment based on a microphone array. The method includes the steps of: acquiring sound signals and dividing the acquired signals into a training set, a verifying set and a test set; performing feature extraction on the sound signals in the training set, and extracting a phase spectrogram and an amplitude spectrogram of a spectrogram; sending an output of a feature extraction module, as an input, to a CNN, and in each layer of the CNN, learning a translation invariance in the spectrogram by using a 2D CNN; in between the layers of the CNN, normalizing the output by using a batch normalization, and reducing a dimension by using a maximum pooling layer along a frequency axis; sending an output from the layers of the CNN to layers of RNN; using a linear activation function; and inputting an output of a full connection layer to two parallel full connection layer branches for fault identification and fault location, respectively.Type: GrantFiled: July 29, 2021Date of Patent: February 18, 2025Assignee: NORTHEASTERN UNIVERSITYInventors: Feng Luan, Xu Li, Ziming Zhang, Yan Wu, Yuejiao Han, Dianhua Zhang
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Patent number: 12223953Abstract: A contextual end-to-end automatic speech recognition (ASR) system includes: an audio encoder configured to process input audio signal to produce as output encoded audio signal; a bias encoder configured to produce as output at least one bias entry corresponding to a word to bias for recognition by the ASR system; a transcription token probability prediction network configured to produce as output a probability of a selected transcription token, based at least in part on the output of the bias encoder and the output of the audio encoder; a first attention mechanism configured to receive the at least one bias entry and determine whether the at least one bias entry is suitable to be transcribed at a specific moment of an ongoing transcription; and a second attention mechanism configured to produce prefix penalties for restricting the first attention mechanism to only entries fitting a current transcription context.Type: GrantFiled: May 5, 2022Date of Patent: February 11, 2025Assignee: Microsoft Technology Licensing, LLCInventors: Alejandro Coucheiro Limeres, Junho Park
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Patent number: 12225317Abstract: According to one embodiment, a method, computer system, and computer program product for front-end clipping reduction is provided. The embodiment may include capturing input, including at least one visual input and at least one audio input. The embodiment may also include modeling data regarding visual cues based on a visual input from the at least one visual input. The embodiment may further include marking one or more timestamps which, in light of the modeled data, correspond to speech in the at least one audio input. The embodiment may also include transmitting an audio input from within the at least one audio input corresponding to the one or more marked timestamps.Type: GrantFiled: March 3, 2022Date of Patent: February 11, 2025Assignee: International Business Machines CorporationInventors: Joseph Sayer, Andrew David Lyell, Benjamin David Cox
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Patent number: 12217012Abstract: A method classifies feedback from transcripts. The method includes receiving an utterance from a transcript from a communication session and processing the utterance with a classifier model to identify a topic label for the utterance. The classifier model is trained to identify topic labels for training utterances. The topic labels correspond to topics of clusters of the training utterances. The training utterances are selected using attention values for the training utterances and clustered using encoder values for the utterances. The method further includes routing the communication session using the topic label for the utterance.Type: GrantFiled: July 31, 2023Date of Patent: February 4, 2025Assignee: Intuit Inc.Inventors: Nitzan Gado, Adi Shalev, Talia Tron, Noa Haas, Oren Dar, Rami Cohen
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Patent number: 12217159Abstract: Systems, devices, and methods related to a Deep Learning Accelerator and memory are described. For example, an integrated circuit device may be configured to execute instructions with matrix operands and configured with random access memory (RAM) to store parameters of an artificial neural network (ANN). The device can generate random bit errors to simulate compromised or corrupted memory cells in a portion of the RAM accessed during computations of a first ANN output. A second ANN output is generated with the random bit errors applied to the data retrieved from the portion of the RAM. Based on a difference between the first and second ANN outputs, the device may adjust the ANN computation to reduce sensitivity to compromised or corrupted memory cells in the portion of the RAM. For example, the sensitivity reduction may be performed through ANN training using machine learning.Type: GrantFiled: August 6, 2020Date of Patent: February 4, 2025Assignee: Micron Technology, Inc.Inventor: Poorna Kale
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Patent number: 12205576Abstract: An electronic apparatus includes a memory storing a speech recognition model and first recognition information corresponding to a first user voice obtained through the speech recognition model, the speech recognition model including a first network, a second network, and a third network; and a processor configured to: obtain a first vector by inputting voice data corresponding to a second user voice to the first network, obtain a second vector by inputting the first recognition information to the second network which generates a vector based on first weight information, and obtain second recognition information corresponding to the second user voice by inputting the first vector and the second vector to the third network which generates recognition information based on second weight information, wherein at least a part of the second weight information is the same as the first weight information.Type: GrantFiled: October 18, 2022Date of Patent: January 21, 2025Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Jinhwan Park, Sungsoo Kim, Sichen Jin, Junmo Park, Dhairya Sandhyana, Changwoo Han
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Patent number: 12190877Abstract: Devices and techniques are generally described for nearest device arbitration. In various examples, a first device may receive first audio data representing a wakeword spoken by a first speaker at a first time. In some examples, a second device may receive second audio data representing the wakeword spoken by the first speaker at the first time. In some cases, the first device may generate first feature data representing the first audio data and the second device may generate second feature data representing the second audio data. In various examples, a machine learning model may use the first feature data and the second feature data to generate first prediction data representing a prediction that the first device is closer to the first speaker than the second device.Type: GrantFiled: March 2, 2022Date of Patent: January 7, 2025Assignee: AMAZON TECHNOLOGIES, INC.Inventors: Jarred Barber, Tao Zhang, Yifeng Fan
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Patent number: 12190062Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing natural language processing operations using a hybrid reason code prediction machine learning framework. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform natural language processing using a hybrid reason code prediction machine learning framework that comprises one or more of the following: (i) a hierarchical transformer machine learning model, (ii) an utterance prediction machine learning model, (iii) an attention distribution generation machine learning model, (iv) an utterance-code pair prediction machine learning model, and (v) a hybrid prediction machine learning model.Type: GrantFiled: April 28, 2022Date of Patent: January 7, 2025Assignee: Optum, Inc.Inventors: Suman Roy, Thomas G. Sullivan, Vijay Varma Malladi, Matthew J. Stewart, Abraham Gebru Tesfay, Gaurav Ranjan
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Patent number: 12190896Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing an input audio waveform using a generator neural network to generate an output audio waveform. In one aspect, a method comprises: receiving an input audio waveform; processing the input audio waveform using an encoder neural network to generate a set of feature vectors representing the input audio waveform; and processing the set of feature vectors representing the input audio waveform using a decoder neural network to generate an output audio waveform that comprises a respective output audio sample for each of a plurality of output time steps.Type: GrantFiled: July 1, 2022Date of Patent: January 7, 2025Assignee: Google LLCInventors: Yunpeng Li, Marco Tagliasacchi, Dominik Roblek, Félix de Chaumont Quitry, Beat Gfeller, Hannah Raphaelle Muckenhirn, Victor Ungureanu, Oleg Rybakov, Karolis Misiunas, Zalán Borsos
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Patent number: 12190869Abstract: A computer-implemented method includes receiving a sequence of acoustic frames as input to an automatic speech recognition (ASR) model. Here, the ASR model includes a causal encoder and a decoder. The method also includes generating, by the causal encoder, a first higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The method also includes generating, by the decoder, a first probability distribution over possible speech recognition hypotheses. Here, the causal encoder includes a stack of causal encoder layers each including a Recurrent Neural Network (RNN) Attention-Performer module that applies linear attention.Type: GrantFiled: September 29, 2022Date of Patent: January 7, 2025Assignee: Google LLCInventors: Tara N. Sainath, Rami Botros, Anmol Gulati, Krzysztof Choromanski, Ruoming Pang, Trevor Strohman, Weiran Wang, Jiahui Yu
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Patent number: 12183204Abstract: Techniques are discussed for determining prediction probabilities of an object based on a top-down representation of an environment. Data representing objects in an environment can be captured. Aspects of the environment can be represented as map data. A multi-channel image representing a top-down view of object(s) in the environment can be generated based on the data representing the objects and map data. The multi-channel image can be used to train a machine learned model by minimizing an error between predictions from the machine learned model and a captured trajectory associated with the object. Once trained, the machine learned model can be used to generate prediction probabilities of objects in an environment, and the vehicle can be controlled based on such prediction probabilities.Type: GrantFiled: December 6, 2021Date of Patent: December 31, 2024Assignee: Zoox, Inc.Inventors: Xi Joey Hong, Benjamin John Sapp, James William Vaisey Philbin, Kai Zhenyu Wang
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Patent number: 12175202Abstract: A method includes receiving a sequence of audio features characterizing an utterance and processing, using an encoder neural network, the sequence of audio features to generate a sequence of encodings. At each of a plurality of output steps, the method also includes determining a corresponding hard monotonic attention output to select an encoding from the sequence of encodings, identifying a proper subset of the sequence of encodings based on a position of the selected encoding in the sequence of encodings, and performing soft attention over the proper subset of the sequence of encodings to generate a context vector at the corresponding output step. The method also includes processing, using a decoder neural network, the context vector generated at the corresponding output step to predict a probability distribution over possible output labels at the corresponding output step.Type: GrantFiled: November 30, 2021Date of Patent: December 24, 2024Assignee: Google LLCInventors: Chung-Cheng Chiu, Colin Abraham Raffel
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Patent number: 12169779Abstract: The present disclosure provides systems and methods that enable parameter-efficient transfer learning, multi-task learning, and/or other forms of model re-purposing such as model personalization or domain adaptation. In particular, as one example, a computing system can obtain a machine-learned model that has been previously trained on a first training dataset to perform a first task. The machine-learned model can include a first set of learnable parameters. The computing system can modify the machine-learned model to include a model patch, where the model patch includes a second set of learnable parameters. The computing system can train the machine-learned model on a second training dataset to perform a second task that is different from the first task, which may include learning new values for the second set of learnable parameters included in the model patch while keeping at least some (e.g., all) of the first set of parameters fixed.Type: GrantFiled: May 2, 2023Date of Patent: December 17, 2024Assignee: GOOGLE LLCInventors: Mark Sandler, Andrew Gerald Howard, Andrey Zhmoginov, Pramod Kaushik Mudrakarta
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Patent number: 12165633Abstract: The present disclosure relates to Communicational and Conversational Artificial Intelligence, Machine Perception, Perceptual-User-Interface, and a professional training method. A chatbot may comprise at least one skills module. The chatbot engages with trainee(s) on communicational training on a subject matter provided by the skills module. A trainer may create, remove, or update a skills module with interaction skills and training materials through an onboarding module. A trainee can upload recorded interactions to a skills module for evaluation or for role playing an interaction without a trainer or partner. An administrator may monitor a trainee's performance, and correlate with the organization's metrics. Based on the evaluation, the trainer or chatbot may provide the trainee with feedback and recommended improvement plans. The chatbot may be implemented in an Internet-of-Things or any device. The subject matters may extend to cover different industries/markets.Type: GrantFiled: May 10, 2022Date of Patent: December 10, 2024Assignee: AskWisy, Inc.Inventors: Patrick Pak Tak Leong, Kwok-Cheung Ellis Hung
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Patent number: 12159111Abstract: A system and method for providing a voice assistant service for text including an anaphor are provided. A method, performed by an electronic device, of providing a voice assistant service includes: obtaining first text generated from a first input, detecting a target word within the first text and generating common information related to the detected target word, using a first natural language understanding (NLU) model, obtaining second text generated from a second input, inputting the common information and the second text to a second NLU model, detecting an anaphor included in the second text and outputting an intent and a parameter, based on common information corresponding to the detected anaphor, using the second NLU model, and generating response information related to the intent and the parameter.Type: GrantFiled: November 29, 2021Date of Patent: December 3, 2024Assignee: Samsung Electronics Co., Ltd.Inventors: Yeonho Lee, Munjo Kim, Sangwook Park, Youngbin Shin, Kookjin Yeo
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Patent number: 12159619Abstract: According to an embodiment, an electronic device comprises: a memory and at least one processor operatively connected with the memory. The at least one processor is configured to: in response to a voice assistant application being executed, identify a pronunciation variant for which an amount of sound source data stored in the memory is less than a specified value among a plurality of pronunciation variants, identify a subject based on the identified pronunciation variant, obtain a question text corresponding to a word including the identified pronunciation variant among a plurality of words included in the subject, output a question speech corresponding to the question text, and receive an utterance after outputting the question speech.Type: GrantFiled: March 15, 2022Date of Patent: December 3, 2024Assignee: Samsung Electronics Co., Ltd.Inventors: Cheol Ryu, Kwanghoon Kim, Junesig Sung
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Patent number: 12153423Abstract: A system for transportation includes a vehicle interface for gathering hormonal state data of a rider in the vehicle. The system further includes an artificial intelligence-based circuit that is trained on a set of outcomes related to rider in-vehicle experience and that induces, responsive to the sensed rider hormonal state data, variation in one or more of the user experience parameters to achieve at least one desired outcome in the set of outcomes. The set of outcomes includes at least one outcome that promotes rider safety. The inducing variation includes control of timing and extent of the variation.Type: GrantFiled: October 31, 2022Date of Patent: November 26, 2024Assignee: Strong Force TP Portfolio 2022, LLCInventor: Charles Howard Cella
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Patent number: 12154546Abstract: A method and system for acoustic model conditioning on non-phoneme information features for optimized automatic speech recognition is provided. The method includes using an encoder model to encode sound embedding from a known key phrase of speech and conditioning an acoustic model with the sound embedding to optimize its performance in inferring the probabilities of phonemes in the speech. The sound embedding can comprise non-phoneme information related to the key phrase and the following utterance. Further, the encoder model and the acoustic model can be neural networks that are jointly trained with audio data.Type: GrantFiled: July 6, 2023Date of Patent: November 26, 2024Assignee: SoundHound AI IP, LLC.Inventors: Zizu Gowayyed, Keyvan Mohajer
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Patent number: 12142258Abstract: Without dividing speech into a unit such as a word or a character, text corresponding to the speech is labeled. A speech distributed representation sequence converting unit 11 converts an acoustic feature sequence into a speech distributed representation. A symbol distributed representation converting unit 12 converts each symbol included in the symbol sequence corresponding to the acoustic feature sequence into a symbol distributed representation. A label estimation unit 13 estimates a label corresponding to the symbol from the fixed-length vector of the symbol generated using the speech distributed representation, the symbol distributed representation, and fixed-length vectors of previous and next symbols.Type: GrantFiled: January 10, 2020Date of Patent: November 12, 2024Assignee: NIPPON TELEGRAPH AND TELEPHONE CORPORATIONInventors: Tomohiro Tanaka, Ryo Masumura, Takanobu Oba
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Patent number: 12125472Abstract: Methods, apparatus, and systems are disclosed to segment audio and determine audio segment similarities. An example apparatus includes at least one memory storing instructions and processor circuitry to execute instructions to at least select an anchor index beat of digital audio, identify a first segment of the digital audio based on the anchor index beat to analyze, the first segment having at least two beats and a respective center beat, concatenate time-frequency data of the at least two beats and the respective center beat to form a matrix of the first segment, generate a first deep feature based on the first segment, the first deep feature indicative of a descriptor of the digital audio, and train internal coefficients to classify the first deep feature as similar to a second deep feature based on the descriptor of the first deep feature and a descriptor of a second deep feature.Type: GrantFiled: April 10, 2023Date of Patent: October 22, 2024Assignee: Gracenote, Inc.Inventor: Matthew McCallum
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Patent number: 12106749Abstract: A method for performing speech recognition using sequence-to-sequence models includes receiving audio data for an utterance and providing features indicative of acoustic characteristics of the utterance as input to an encoder. The method also includes processing an output of the encoder using an attender to generate a context vector, generating speech recognition scores using the context vector and a decoder trained using a training process, and generating a transcription for the utterance using word elements selected based on the speech recognition scores. The transcription is provided as an output of the ASR system.Type: GrantFiled: September 20, 2021Date of Patent: October 1, 2024Assignee: Google LLCInventors: Rohit Prakash Prabhavalkar, Zhifeng Chen, Bo Li, Chung-cheng Chiu, Kanury Kanishka Rao, Yonghui Wu, Ron J. Weiss, Navdeep Jaitly, Michiel A. u. Bacchiani, Tara N. Sainath, Jan Kazimierz Chorowski, Anjuli Patricia Kannan, Ekaterina Gonina, Patrick An Phu Nguyen
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Patent number: 12087307Abstract: An apparatus for processing speech data may include a processor configured to: separate an input speech into speech signals; identify a bandwidth of each of the speech signals; extract speaker embeddings from the speech signals based on the bandwidth of each of the speech signals, using at least one neural network configured to receive the speech signals and output the speaker embeddings; and cluster the speaker embeddings into one or more speaker clusters, each speaker cluster corresponding to a speaker identity.Type: GrantFiled: November 30, 2021Date of Patent: September 10, 2024Assignee: SAMSUNG ELECTRONICS CO., LTD.Inventors: Myungjong Kim, Vijendra Raj Apsingekar, Aviral Anshu, Taeyeon Ki
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Patent number: 12086704Abstract: Representative embodiments disclose machine learning classifiers used in scenarios such as speech recognition, image captioning, machine translation, or other sequence-to-sequence embodiments. The machine learning classifiers have a plurality of time layers, each layer having a time processing block and a depth processing block. The time processing block is a recurrent neural network such as a Long Short Term Memory (LSTM) network. The depth processing blocks can be an LSTM network, a gated Deep Neural Network (DNN) or a maxout DNN. The depth processing blocks account for the hidden states of each time layer and uses summarized layer information for final input signal feature classification. An attention layer can also be used between the top depth processing block and the output layer.Type: GrantFiled: November 3, 2021Date of Patent: September 10, 2024Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Jinyu Li, Liang Lu, Changliang Liu, Yifan Gong
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Patent number: 12087306Abstract: In one embodiment, a method includes receiving a user's utterance comprising a word in a custom vocabulary list of the user, generating a previous token to represent a previous audio portion of the utterance, and generating a current token to represent a current audio portion of the utterance by generating a bias embedding by using the previous token to query a trie of wordpieces representing the custom vocabulary list, generating first probabilities of respective first candidate tokens likely uttered in the current audio portion based on the bias embedding and the current audio portion, generating second probabilities of respective second candidate tokens likely uttered after the previous token based on the previous token and the bias embedding, and generating the current token to represent the current audio portion of the utterance based on the first probabilities of the first candidate tokens and the second probabilities of the second candidate tokens.Type: GrantFiled: November 24, 2021Date of Patent: September 10, 2024Assignee: Meta Platforms, Inc.Inventors: Duc Hoang Le, FNU Mahaveer, Gil Keren, Christian Fuegen, Yatharth Saraf
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Patent number: 12079913Abstract: This specification relates to the generation of animation data using recurrent neural networks. According to a first aspect of this specification, there is described a computer implemented method comprising: sampling an initial hidden state of a recurrent neural network (RNN) from a distribution; generating, using the RNN, a sequence of frames of animation from the initial state of the RNN and an initial set of animation data comprising a known initial frame of animation, the generating comprising, for each generated frame of animation in the sequence of frames of animation: inputting, into the RNN, a respective set of animation data comprising the previous frame of animation data in the sequence of frames of animation; generating, using the RNN and based on a current hidden state of the RNN, the frame of animation data; and updating the hidden state of the RNN based on the input respective set of animation data.Type: GrantFiled: March 31, 2022Date of Patent: September 3, 2024Assignee: ELECTRONIC ARTS INC.Inventor: Elaheh Akhoundi
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Patent number: 12073843Abstract: The present disclosure relates to a speech enhancement apparatus, and specifically, to a method and apparatus for a target exaggeration for deep learning-based speech enhancement. According to an embodiment of the present disclosure, the apparatus for a target exaggeration for deep learning-based speech enhancement can preserve a speech signal from a noisy speech signal and can perform speech enhancement for removing a noise signal.Type: GrantFiled: October 26, 2021Date of Patent: August 27, 2024Assignee: Gwangju Institute of Science and TechnologyInventors: Jong Won Shin, Han Sol Kim
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Patent number: 12067975Abstract: Methods, systems, and apparatuses for predicting an end of a command in a voice recognition input are described herein. The system may receive data comprising a voice input. The system may receive a signal comprising a voice input. The system may detect, in the voice input, data that is associated with a first portion of a command. The system may predict, based on the first portion and while the voice input is being received, a second portion of the command. The prediction may be generated by a machine learning algorithm that is trained based at least in part on historical data comprising user input data. The system may cause execution of the command, based on the first portion and the predicted second portion, prior to an end of the voice input.Type: GrantFiled: April 18, 2023Date of Patent: August 20, 2024Assignee: Comcast Cable Communications, LLCInventors: Rui Min, Hongcheng Wang
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Patent number: 12062363Abstract: A recurrent neural network-transducer (RNN-T) model improves speech recognition by processing sequential non-blank symbols at each time step after an initial one. The model's prediction network receives a sequence of symbols from a final Softmax layer and employs a shared embedding matrix to create and map embeddings to each symbol, associating them with unique position vectors. These embeddings are weighted according to their similarity to their matching position vector. Subsequently, a joint network of the RNN-T model uses these weighted embeddings to output a probability distribution for potential speech recognition hypotheses at each time step, enabling more accurate transcriptions of spoken language.Type: GrantFiled: July 6, 2023Date of Patent: August 13, 2024Assignee: Google LLCInventors: Rami Botros, Tara Sainath
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Patent number: 12057128Abstract: A system and method for publishing encoded identity data that uses at least biometric information as well as non-biometric identity and/or authentication data is disclosed. The system and method can be used for verifying a user's identity against the published encoded identity data on a distributed system, such as a distributed ledger or blockchain. Using this system, a user's identity can be verified efficiently by multiple parties, in sequence, or in parallel, as a user need only enroll in the verification process a single time. The system further includes a biometric enrollment sub-system that allows for a highly secure method of verifying a user based on unique biometric signals, such as features extracted from an audio voice signal.Type: GrantFiled: August 27, 2021Date of Patent: August 6, 2024Assignee: United Services Automobile Association (USAA)Inventors: Vijay Jayapalan, Jeffrey David Calusinski
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Patent number: 12033649Abstract: Embodiments are disclosed for noise floor estimation and noise reduction, In an embodiment, a method comprises: obtaining an audio signal; dividing the audio signal into a plurality of buffers; determining time-frequency samples for each buffer of the audio signal; for each buffer and for each frequency, determining a median (or mean) and a measure of an amount of variation of energy based on the samples in the buffer and samples in neighboring buffers that together span a specified time range of the audio signal; combining the median (or mean) and the measure of the amount of variation of energy into a cost function; for each frequency: determining a signal energy of a particular buffer of the audio signal that corresponds to a minimum value of the cost function; selecting the signal energy as the estimated noise floor of the audio signal; and reducing, using the estimated noise floor, noise in the audio signal.Type: GrantFiled: January 18, 2021Date of Patent: July 9, 2024Assignee: DOLBY INTERNATIONAL ABInventors: Giulio Cengarle, Antonio Mateos Sole, Davide Scaini
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Patent number: 12034555Abstract: Systems and methods for facilitating a watch party are provided. In one example, a method includes: initiating a watch party session for a host user using, presenting content selected by the host user on a first user device during the watch party session, initiating a chat session concurrent with the watch party session, receiving a participation request by a guest user sent from a second user device for participating in the chat session; in response to the participation request, authenticating the guest user; presenting the content selected by the host user on the second user device; synchronizing the presentation of the content on the first user device with the presentation of the second user device; and facilitating communication between the host user and the guest user during the chat session.Type: GrantFiled: May 10, 2023Date of Patent: July 9, 2024Assignee: DISH Network Technologies India Private LimitedInventors: Melvin P. Perinchery, Preetham Kumar
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Patent number: 12020697Abstract: An audio keyword searcher arranged to identify a voice segment of a received audio signal; identify, by an automatic speech recognition engine, one or more phonemes included in the voice segment; output, from the automatic speech recognition engine, the one or more phonemes to a keyword filter to detect whether the voice segment includes any of the one or more first keywords of the first keyword list and, if detected, output the one or more phonemes included in the voice segment to a decoder but, if not detected, not output the one or more phonemes included in the voice segment to the decoder. If the one or more phonemes are output to the decoder: generate a word lattice associated with the voice segment; search the word lattice for one or more second keywords, and determine whether the voice segment includes the one or more second keywords.Type: GrantFiled: July 15, 2020Date of Patent: June 25, 2024Assignee: Raytheon Applied Signal Technology, Inc.Inventor: Jonathan C. Wintrode
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Patent number: 12020135Abstract: A library of machine learning primitives is provided to optimize a machine learning model to improve the efficiency of inference operations. In one embodiment a trained convolutional neural network (CNN) model is processed into a trained CNN model via pruning, convolution window optimization, and quantization.Type: GrantFiled: August 26, 2021Date of Patent: June 25, 2024Assignee: Intel CorporationInventors: Liwei Ma, Elmoustapha Ould-Ahmed-Vall, Barath Lakshmanan, Ben J. Ashbaugh, Jingyi Jin, Jeremy Bottleson, Mike B. Macpherson, Kevin Nealis, Dhawal Srivastava, Joydeep Ray, Ping T. Tang, Michael S. Strickland, Xiaoming Chen, Anbang Yao, Tatiana Shpeisman, Altug Koker, Abhishek R. Appu
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Patent number: 12019639Abstract: This application relates to apparatus and methods for generating preference profiles that may be used to rank search results. In some examples, a computing device obtains browsing session data and determines items that were engaged, such as items that were viewed or clicked. The computing device obtains item property data, such as product descriptions, for the items, and applies a dependency parser to the item property data to identify portions that include certain words, such as nouns or adjectives, which are then identified as attributes. The computing device generates attribute data identifying portions of the item property data as item attributes. In some examples, the computing device applies one or more machine learning algorithms to the session data and/or search query to identify item attributes. The computing device may generate a profile that includes the item attributes, and may rank search results based on the attribute data, among other uses.Type: GrantFiled: January 25, 2023Date of Patent: June 25, 2024Assignee: Walmart Apollo, LLCInventors: Rahul Iyer, Soumya Wadhwa, Stephen Dean Guo, Kannan Achan
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Patent number: 12019641Abstract: Systems and techniques are provided for processing one or more data samples. For example, a neural network classifier can be trained to perform few-shot open-set recognition (FSOSR) based on a task-agnostic open-set prototype. A process can include determining one or more prototype representations for each class included in a plurality of support samples. A task-agnostic open-set prototype representation can be determined, in a same learned metric space as the one or more prototype representations. One or more distance metrics can be determined for each query sample of one or more query samples, based on the one or more prototype representations and the task-agnostic open-set prototype representation. Based on the one or more distance metrics, each query sample can be classified into one of classes associated with the one or more prototype representations or an open-set class associated with the task-agnostic open-set prototype representation.Type: GrantFiled: January 12, 2023Date of Patent: June 25, 2024Assignee: QUALCOMM IncorporatedInventors: Byeonggeun Kim, Juntae Lee, Simyung Chang
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Patent number: 12008459Abstract: This document relates to architectures and training procedures for multi-task machine learning models, such as neural networks. One example method involves providing a multi-task machine learning model having one or more shared layers and two or more task-specific layers. The method can also involve performing a pretraining stage on the one or more shared layers using one or more unsupervised prediction tasks. The method can also involve performing a tuning stage on the one or more shared layers and the two or more task-specific layers using respective task-specific objectives.Type: GrantFiled: June 17, 2019Date of Patent: June 11, 2024Assignee: Microsoft Technology Licensing, LLCInventors: Weizhu Chen, Pengcheng He, Xiaodong Liu, Jianfeng Gao
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Patent number: 11996099Abstract: An embodiment dialogue system includes a speech recognizer configured to convert an utterance of a user into an utterance text, a natural language understanding module configured to identify an intention of the user based on the utterance text, and a controller configured to generate a first control signal for performing control corresponding to the intention of the user, identify whether an additional control item related to the control corresponding to the intention of the user exists, and in response to the additional control item existing, generate a second control signal for displaying information about the additional control item on a display.Type: GrantFiled: November 18, 2021Date of Patent: May 28, 2024Assignees: Hyundai Motor Company, Kia CorporationInventors: Sungwang Kim, Donghyeon Lee, Minjae Park
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Patent number: 11989941Abstract: Embodiments described a method of video-text pre-learning to effectively learn cross-modal representations from sparse video frames and text. Specifically, an align and prompt framework provides a video and language pre-training framework that encodes the frames and text independently using a transformer-based video encoder and a text encoder. A multi-modal encoder is then employed to capture cross-modal interaction between a plurality of video frames and a plurality of texts. The pre-training includes a prompting entity modeling that enables the model to capture fine-grained region-entity alignment.Type: GrantFiled: December 30, 2021Date of Patent: May 21, 2024Assignee: Salesforce, Inc.Inventors: Dongxu Li, Junnan Li, Chu Hong Hoi
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Patent number: 11990151Abstract: The present technology relates to a particular-sound detector and method, and a program that make it possible to improve the performance of detecting particular sounds. The particular-sound detector includes a particular-sound detecting section that detects a particular sound on a basis of a plurality of audio signals obtained by collecting sounds by a plurality of microphones provided to a wearable device. In addition, the plurality of the microphones includes two microphones that are equidistant at least from a sound source of the particular sound, and one microphone arranged at a predetermined position. The present technology can be applied to headphones.Type: GrantFiled: December 12, 2019Date of Patent: May 21, 2024Assignee: Sony Group CorporationInventors: Yuki Yamamoto, Yuji Tokozume, Toru Chinen
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Patent number: 11970059Abstract: The invention relates to a system for interacting with an occupant of a motor vehicle comprising: a. a measuring device comprising at least one sensor arranged to acquire at least one parameter associated with the occupant of said vehicle; b. an on-board processing unit arranged to receive said parameter and to define a data item representing the emotional state of said occupant by means of said model, said representative data item being a comfort index score (CISn) of said occupant; c. the representative data item corresponding to a point in a two-dimensional space (anvn) for characterising the emotional state of the occupant; d. characterised in that an emotional comfort index is computed on the basis of the representative data item; e. and in that at least one actuator is configured to activate at least one multi-sensory stimulus for interacting with the occupant, said stimulus allowing the emotional state of said occupant to be changed.Type: GrantFiled: January 6, 2020Date of Patent: April 30, 2024Assignee: VALEO SYSTEMES THERMIQUESInventors: Georges De Pelsemaeker, Antoine Boilevin, Hamid Bessaa
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Patent number: 11967340Abstract: Disclosed is a method for detecting a voice from audio data, performed by a computing device according to an exemplary embodiment of the present disclosure. The method includes obtaining audio data; generating image data based on a spectrum of the obtained audio data; analyzing the generated image data by utilizing a pre-trained neural network model; and determining whether an automated response system (ARS) voice is included in the audio data, based on the analysis of the image data.Type: GrantFiled: June 23, 2023Date of Patent: April 23, 2024Assignee: ActionPower Corp.Inventors: Subong Choi, Dongchan Shin, Jihwa Lee
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Patent number: 11961515Abstract: A method includes receiving a plurality of unlabeled audio samples corresponding to spoken utterances not paired with corresponding transcriptions. At a target branch of a contrastive Siamese network, the method also includes generating a sequence of encoder outputs for the plurality of unlabeled audio samples and modifying time characteristics of the encoder outputs to generate a sequence of target branch outputs. At an augmentation branch of a contrastive Siamese network, the method also includes performing augmentation on the unlabeled audio samples, generating a sequence of augmented encoder outputs for the augmented unlabeled audio samples, and generating predictions of the sequence of target branch outputs generated at the target branch. The method also includes determining an unsupervised loss term based on target branch outputs and predictions of the sequence of target branch outputs. The method also includes updating parameters of the audio encoder based on the unsupervised loss term.Type: GrantFiled: December 14, 2021Date of Patent: April 16, 2024Assignee: Google LLCInventors: Jaeyoung Kim, Soheil Khorram, Hasim Sak, Anshuman Tripathi, Han Lu, Qian Zhang
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Patent number: 11941787Abstract: Examples are provided relating to recovering depth data from noisy phase data of low-signal pixels. One example provides a computing system, comprising a logic machine, and a storage machine holding instructions executable by the logic machine to process depth data by obtaining depth image data and active brightness image data for a plurality of pixels, the depth image data comprising phase data for a plurality of frequencies, and identifying low-signal pixels based at least on the active brightness image data. The instructions are further executable to apply a denoising filter to phase data of the low-signal pixels to obtain denoised phase data and not applying the denoising filter to phase data of other pixels. The instructions are further executable to, after applying the denoising filter, perform phase unwrapping on the phase data for the plurality of frequencies to obtain a depth image, and output the depth image.Type: GrantFiled: August 23, 2021Date of Patent: March 26, 2024Assignee: Microsoft Technology Licensing, LLCInventors: Sergio Ortiz Egea, Augustine Cha