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公开(公告)号：US20190303442A1
公开(公告)日：2019-10-03
申请号：US16024475
申请日：2018-06-29
Applicant: Apple Inc.
Inventor： Stephan PEITZ , Udhyakumar NALLASAMY , Matthias PAULIK , Yun TANG
Abstract: Systems and processes for operating an electronic device to train a machine-learning translation system are described. In one process, a first set of training data is obtained. The first set of training data includes at least one payload in a first language and a translation of the at least one payload in a second language. The process further includes obtaining one or more templates for adapting the at least one payload; adapting the at least one payload using the one or more templates to generate at least one adapted payload formulated as a translation request; generating a second set of training data based on the at least one adapted payload; and training the machine-learning translation system using the second set of training data.
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公开(公告)号：US20160358598A1
公开(公告)日：2016-12-08
申请号：US14846667
申请日：2015-09-04
Applicant: Apple Inc.
Inventor： Shaun E. WILLIAMS , Henry G. MASON , Mahesh KRISHNAMOORTHY , Matthias PAULIK , Neha AGRAWAL , Sachin S. KAJAREKAR , Selen UGUROGLU , Ali S. MOHAMED
CPC classification number: G10L15/04 , G10L17/02 , G10L25/87 , G10L2025/783
Abstract: The present disclosure generally relates to context-based endpoint detection in user speech input. A method for identifying an endpoint of a spoken request by a user may include receiving user input of natural language speech including one or more words; identifying at least one context associated with the user input; generating a probability, based on the at least one context associated with the user input, that a location in the user input is an endpoint; determining whether the probability is greater than a threshold; and in accordance with a determination that the probability is greater than the threshold, identifying the location in the user input as the endpoint.
Abstract translation: 本公开通常涉及用户语音输入中的基于上下文的端点检测。 用于识别用户的口头请求的端点的方法可以包括接收包括一个或多个单词的自然语言语言的用户输入; 识别与所述用户输入相关联的至少一个上下文; 基于与所述用户输入相关联的所述至少一个上下文，生成所述用户输入中的位置是端点的概率; 确定概率是否大于阈值; 并且根据概率大于阈值的确定，将用户输入中的位置识别为端点。
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公开(公告)号：US20160063998A1
公开(公告)日：2016-03-03
申请号：US14591754
申请日：2015-01-07
Applicant: Apple Inc.
Inventor： Mahesh KRISHNAMOORTHY , Matthias PAULIK
CPC classification number: G10L15/22 , G10L15/01 , G10L15/02 , G10L15/32 , G10L2015/025
Abstract: Systems and processes for processing speech in a digital assistant are provided. In one example process, a first speech input can be received from a user. The first speech input can be processed using a first automatic speech recognition system to produce a first recognition result. An input indicative of a potential error in the first recognition result can be received. The input can be used to improve the first recognition result. For example, the input can include a second speech input that is a repetition of the first speech input. The second speech input can be processed using a second automatic speech recognition system to produce a second recognition result.
Abstract translation: 提供了一种用于在数字助理中处理语音的系统和过程。 在一个示例过程中，可以从用户接收第一语音输入。 可以使用第一自动语音识别系统来处理第一语音输入以产生第一识别结果。 可以接收表示第一识别结果中的潜在错误的输入。 该输入可用于改善第一识别结果。 例如，输入可以包括作为第一语音输入的重复的第二语音输入。 可以使用第二自动语音识别系统来处理第二语音输入以产生第二识别结果。
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公开(公告)号：US20180330737A1
公开(公告)日：2018-11-15
申请号：US15713276
申请日：2017-09-22
Applicant: Apple Inc.
Inventor： Matthias PAULIK , Henry G. MASON , Jason A. SKINDER
CPC classification number: G10L17/04 , G10L15/02 , G10L15/063 , G10L15/07 , G10L15/187 , G10L15/30 , G10L2015/0635 , G10L2015/0636
Abstract: Systems and processes for providing user-specific acoustic models are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a plurality of speech inputs, each of the speech inputs associated with a same user of the electronic device; providing each of the plurality of speech inputs to a user-independent acoustic model, the user-independent acoustic model providing a plurality of speech results based on the plurality of speech inputs; initiating a user-specific acoustic model on the electronic device; and adjusting the user-specific acoustic model based on the plurality of speech inputs and the plurality of speech results.
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公开(公告)号：US20180330731A1
公开(公告)日：2018-11-15
申请号：US15713503
申请日：2017-09-22
Applicant: Apple Inc.
Inventor： Nicolas ZEITLIN , Matthias PAULIK , Henry G. MASON , Karric KWONG , Sinan AKAY , Saravana Kumar RATHINAM , Anumita BISWAS
Abstract: Systems and processes for performing a task with a digital assistant are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a natural-language input; determining, based on the natural-language input, a first task and first usefulness score associated with the first task; receiving, from another electronic device, a second task and second usefulness score associated with the second task; determining whether the first usefulness score is higher than the second usefulness score; in accordance with a determination that the first usefulness score is higher than the second usefulness score: performing the first task determined by the electronic device; and providing an output indicating whether the first task has been performed; and in accordance with a determination that the second usefulness score is higher than the first usefulness score: performing the second task received from the another electronic device; and providing an output indicating whether the second task has been performed.
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Patent Agency Ranking
公开(公告)号：US20190341056A1
公开(公告)日：2019-11-07
申请号：US16516986
申请日：2019-07-19
Applicant: Apple Inc.
Inventor： Matthias PAULIK , Henry G. MASON , Jason A. SKINDER
Abstract: Systems and processes for providing user-specific acoustic models are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a plurality of speech inputs, each of the speech inputs associated with a same user of the electronic device; providing each of the plurality of speech inputs to a user-independent acoustic model, the user-independent acoustic model providing a plurality of speech results based on the plurality of speech inputs; initiating a user-specific acoustic model on the electronic device; and adjusting the user-specific acoustic model based on the plurality of speech inputs and the plurality of speech results.
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公开(公告)号：US20190318739A1
公开(公告)日：2019-10-17
申请号：US16412137
申请日：2019-05-14
Applicant: Apple Inc.
Inventor： Ashish GARG , Harry J. SADDLER , Shweta GRAMPUROHIT , Robert A. WALKER , Rushin N. SHAH , Matthew S. SEIGEL , Matthias PAULIK
Abstract: Speech recognition is performed on a received utterance to determine a plurality of candidate text representations of the utterance, including a primary text representation and one or more alternative text representations. Natural language processing is performed on the primary text representation to determine a plurality of candidate actionable intents, including a primary actionable intent and one or more alternative actionable intents. A result is determined based on the primary actionable intent. The result is provided to the user. A recognition correction trigger is detected. In response to detecting the recognition correction trigger, a set of alternative intent affordances and a set of alternative text affordances are concurrently displayed.
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公开(公告)号：US20180330714A1
公开(公告)日：2018-11-15
申请号：US15917230
申请日：2018-03-09
Applicant: Apple Inc.
Inventor： Matthias PAULIK , Matthew S. SEIGEL , Rogier C. VAN DALEN
Abstract: Systems and processes for improved machine-learned systems are provided. In accordance with one example, a method includes receiving a first speech recognition result and a first accuracy score corresponding to the first speech recognition result; receiving, from another electronic device, a second speech recognition result and a second accuracy score corresponding to the second recognition result; determining whether the second accuracy score is greater than the first accuracy score; in accordance with a determination that the second accuracy score is greater than the first accuracy score, providing a speech recognition system of the electronic device based on the second speech recognition result; and in accordance with a determination that the second accuracy score is not greater than the first accuracy score, forgoing providing a speech recognition system of the electronic device based on the second speech recognition result.
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公开(公告)号：US20180108346A1
公开(公告)日：2018-04-19
申请号：US15803584
申请日：2017-11-03
Applicant: Apple Inc.
Inventor： Matthias PAULIK , Gunnar EVERMANN , Laurence S. GILLICK
IPC: G10L15/06 , G10L15/197 , G10L25/33 , G06F17/30 , G10L15/02
CPC classification number: G10L15/063 , G06F16/9535 , G10L15/02 , G10L15/1815 , G10L15/183 , G10L15/197 , G10L25/33
Abstract: Systems and processes are disclosed for discovering trending terms in automatic speech recognition. Candidate terms (e.g., words, phrases, etc.) not yet found in a speech recognizer vocabulary or having low language model probability can be identified based on trending usage in a variety of electronic data sources (e.g., social network feeds, news sources, search queries, etc.). When candidate terms are identified, archives of live or recent speech traffic can be searched to determine whether users are uttering the candidate terms in dictation or speech requests. Such searching can be done using open vocabulary spoken term detection to find phonetic matches in the audio archives. As the candidate terms are found in the speech traffic, notifications can be generated that identify the candidate terms, provide relevant usage statistics, identify the context in which the terms are used, and the like.
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公开(公告)号：US20230186921A1
公开(公告)日：2023-06-15
申请号：US18107289
申请日：2023-02-08
Applicant: Apple Inc.
Inventor： Matthias PAULIK , Henry G. MASON , Jason A. SKINDER
CPC classification number: G10L17/04 , G10L15/07 , G10L15/30 , G10L15/063 , G10L15/02
Abstract: Systems and processes for providing user-specific acoustic models are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a plurality of speech inputs, each of the speech inputs associated with a same user of the electronic device; providing each of the plurality of speech inputs to a user-independent acoustic model, the user-independent acoustic model providing a plurality of speech results based on the plurality of speech inputs; initiating a user-specific acoustic model on the electronic device; and adjusting the user-specific acoustic model based on the plurality of speech inputs and the plurality of speech results.
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