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Patent Agency Ranking
公开(公告)号：US20240233713A1
公开(公告)日：2024-07-11
申请号：US18412394
申请日：2024-01-12
Applicant: Google LLC
Inventor： Andrea Agostinelli , Timo Immanuel Denk , Antoine Caillon , Neil Zeghidour , Jesse Engel , Mauro Verzetti , Christian Frank , Zalán Borsos , Matthew Sharifi , Adam Joseph Roberts , Marco Tagliasacchi
IPC: G10L15/16 , G06N3/0455 , G06N3/0475 , G10H1/00 , G10L15/06 , G10L15/18
CPC classification number: G10L15/16 , G06N3/0455 , G06N3/0475 , G10H1/0008 , G10L15/063 , G10L15/1815 , G10H2210/056 , G10H2250/311
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction of an audio signal. One of the methods includes receiving a request to generate an audio signal conditioned on an input; processing the input using an embedding neural network to map the input to one or more embedding tokens; generating a semantic representation of the audio signal; generating, using one or more generative neural networks and conditioned on at least the semantic representation and the embedding tokens, an acoustic representation of the audio signal; and processing at least the acoustic representation using a decoder neural network to generate the prediction of the audio signal.
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公开(公告)号：US20240079001A1
公开(公告)日：2024-03-07
申请号：US18463196
申请日：2023-09-07
Applicant: Google LLC
Inventor： Andrea Agostinelli , Timo Immanuel Denk , Antoine Caillon , Neil Zeghidour , Jesse Engel , Mauro Verzetti , Christian Frank , Zalán Borsos , Matthew Sharifi , Adam Joseph Roberts
CPC classification number: G10L15/16 , G10H1/0008 , G10L15/063 , G10L15/1815 , G10H2210/056 , G10H2250/311
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction of an audio signal. One of the methods includes receiving a request to generate an audio signal conditioned on an input; processing the input using an embedding neural network to map the input to one or more embedding tokens; generating a semantic representation of the audio signal; generating, using one or more generative neural networks and conditioned on at least the semantic representation and the embedding tokens, an acoustic representation of the audio signal; and processing at least the acoustic representation using a decoder neural network to generate the prediction of the audio signal.
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公开(公告)号：US11756530B2
公开(公告)日：2023-09-12
申请号：US17640579
申请日：2020-09-25
Applicant: GOOGLE LLC
Inventor： Marco Tagliasacchi , Mihajlo Velimirovic , Matthew Sharifi , Dominik Roblek , Christian Frank , Beat Gfeller
IPC: G10L15/06 , G10L21/013 , G10L25/30 , G10L25/90
CPC classification number: G10L15/063 , G10L21/013 , G10L25/30 , G10L25/90
Abstract: Example embodiments relate to techniques for training artificial neural networks or oilier machine-learning encoders to accurately predict the pitch of input audio samples in a semitone or otherwise logarithmically-scaled pitch space. An example method may include generating, from a sample of audio data, two training samples by applying two different pitch shifts to the sample of audio training data. This can be done by converting the sample of audio data into the frequency domain and then shifting the transformed data. These known shifts are then compared to the predicted pitches generated by applying the two training samples to the encoder. The encoder is then updated based on the comparison, such that the relative pitch output by the encoder is improved with respect to accuracy. One or more audio samples, labeled with absolute pitch values, can then be used to calibrate the relative pitch values generated by the trained encoder.
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公开(公告)号：US20240428056A1
公开(公告)日：2024-12-26
申请号：US18750973
申请日：2024-06-21
Applicant: Google LLC
Inventor： Paul Kishan Rubenstein , Matthew Sharifi , Alexandru Tudor , Chulayuth Asawaroengchai , Duc Dung Nguyen , Marco Tagliasacchi , Neil Zeghidour , Zalán Borsos , Christian Frank , Dalia Salem Hassan Fahmy Elbadawy , Hannah Raphaelle Muckenhirn , Dirk Ryan Padfield , Damien Vincent , Evgeny Kharitonov , Michelle Dana Tadmor , Mihajlo Velimirovic , Feifan Chen , Victoria Zayats
IPC: G06N3/0475 , G10L25/30
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing tasks. One of the methods includes obtaining a sequence of input tokens, where each token is selected from a vocabulary of tokens that includes text tokens and audio tokens, and wherein the sequence of input tokens includes tokens that describe a task to be performed and data for performing the task; generating a sequence of embeddings by embedding each token in the sequence of input tokens in an embedding space; and processing the sequence of embeddings using a language model neural network to generate a sequence of output tokens for the task, where each token is selected from the vocabulary.
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公开(公告)号：US11915689B1
公开(公告)日：2024-02-27
申请号：US18463196
申请日：2023-09-07
Applicant: Google LLC
Inventor： Andrea Agostinelli , Timo Immanuel Denk , Antoine Caillon , Neil Zeghidour , Jesse Engel , Mauro Verzetti , Christian Frank , Zalán Borsos , Matthew Sharifi , Adam Joseph Roberts , Marco Tagliasacchi
CPC classification number: G10L15/16 , G10H1/0008 , G10L15/063 , G10L15/1815 , G10H2210/056 , G10H2250/311
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a prediction of an audio signal. One of the methods includes receiving a request to generate an audio signal conditioned on an input; processing the input using an embedding neural network to map the input to one or more embedding tokens; generating a semantic representation of the audio signal; generating, using one or more generative neural networks and conditioned on at least the semantic representation and the embedding tokens, an acoustic representation of the audio signal; and processing at least the acoustic representation using a decoder neural network to generate the prediction of the audio signal.
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