公开(公告)号：US10403268B2

公开(公告)日：2019-09-03

申请号：US15260021

申请日：2016-09-08

Applicant: Intel IP Corporation

Inventor： David J. Trawick ,  Joachim Hofer ,  Josef G. Bauer ,  Georg Stemmer ,  Da-Ming Chiang

IPC: G10L15/16 ,  G10L15/14 ,  G10L15/08 ,  G10L15/187 ,  G10L15/02 ,  G10L25/84 ,  G10L15/22

Abstract: A system, article, and method include techniques of automatic speech recognition using posterior confidence scores.

公开(公告)号：US10255909B2

公开(公告)日：2019-04-09

申请号：US15637559

申请日：2017-06-29

Applicant: INTEL IP CORPORATION

Inventor： Joachim Hofer ,  Josef G. Bauer ,  Piotr Rozen ,  Georg Stemmer

IPC: G10L15/16 ,  G10L15/14 ,  G10L25/30 ,  G10L15/26

Abstract: Techniques are provided for calculating reset parameters for recurrent neural networks (RNN). A methodology implementing the techniques according to an embodiment includes generating a sequence of statistics. The calculation of each statistic is based on outputs of an RNN that is periodically re-initialized at a selected RNN reset time such that each of the calculated statistics is associated with a unique RNN reset time selected from a pre-determined range of reset times. The method further includes analyzing the sequence to identify a maximum interval during which the sequence remains relatively constant. The method further includes selecting a reset time parameter and reset context duration parameter, for re-initialization of the RNN during operation. The reset time parameter is based on the duration of the identified maximum interval and the reset context duration parameter is based on a time associated with the starting point of the identified maximum interval.

公开(公告)号：US10657952B2

公开(公告)日：2020-05-19

申请号：US15892510

申请日：2018-02-09

Applicant: Intel IP Corporation

Inventor： Joachim Hofer ,  Georg Stemmer ,  Josef G. Bauer ,  Munir Nikolai Alexander Georges

IPC: G10L15/01 ,  G10L15/22 ,  G10L15/05 ,  G10L15/16 ,  G10L25/87 ,  G10L15/14

Abstract: Techniques are provided for reducing the latency of automatic speech recognition using hypothesis score trend analysis. A methodology implementing the techniques according to an embodiment includes generating complete-phrase hypotheses and partial-phrase hypotheses, along with associated likelihood scores, based on a segment of speech. The method also includes selecting the complete-phrase hypothesis associated with the highest of the complete-phrase hypotheses likelihood scores, and selecting the partial-phrase hypothesis associated with the highest of the partial-phrase hypotheses likelihood scores. The method further includes calculating a relative likelihood score based on a ratio of the likelihood score associated with the selected complete-phrase hypothesis to the likelihood score associated with the selected partial-phrase hypothesis. The method further includes calculating a trend of the relative likelihood score as a function of time and identifying an endpoint of the speech based on a determination that the trend does not decrease over a selected time period.

公开(公告)号：US10147423B2

公开(公告)日：2018-12-04

申请号：US15280809

申请日：2016-09-29

Applicant: Intel IP Corporation

Inventor： Munir Nikolai Alexander Georges ,  Georg Stemmer ,  Joachim Hofer

IPC: G10L15/22 ,  G10L15/02 ,  G10L15/14

Abstract: A method for context-aware query recognition in an electronic device includes receiving user speech from an input device. A speech signal is generated from the user speech. It is determined if the speech signal includes an action to be performed and if the electronic device is the intended recipient of the user speech. If the recognized speech signal include the action and the intended recipient of the user speech is the electronic device, a command is generated for the electronic device to perform the action.

公开(公告)号：US20180293974A1

公开(公告)日：2018-10-11

申请号：US15483421

申请日：2017-04-10

Applicant: INTEL IP CORPORATION

Inventor： Munir Nikolai Alexander Georges ,  Tobias Bocklet ,  Georg Stemmer ,  Joachim Hofer ,  Josef G. Bauer

IPC: G10L15/04 ,  G10L15/28 ,  G10L15/18

Abstract: Techniques are provided for spoken language understanding based on keyword spotting and speech recognition. A methodology implementing the techniques according to an embodiment includes detecting a user spoken keyword or key-phrase embedded in an initial segment of a received audio signal, which is stored in a buffer. The method further includes triggering an automatic speech recognition (ASR) processor in response to the key-phrase detection. The method further includes performing automatic speech recognition, by the ASR processor, on a combination of the buffered initial segment and one or more additional received segments of the audio signal which include further speech from the user. The method still further includes performing natural language understanding on the recognized speech to determine a user request. The key-phrase is user selectable and serves to wake the ASR processor from a sleeping or idle lower power consumption state, into an active higher power consumption recognition state.

公开(公告)号：US20190043481A1

公开(公告)日：2019-02-07

申请号：US15855379

申请日：2017-12-27

Applicant: INTEL IP CORPORATION

Inventor： Munir Nikolai Alexander Georges ,  Tobias Bocklet ,  Georg Stemmer ,  Joachim Hofer ,  Josef G. Bauer

IPC: G10L15/06 ,  G10L15/187 ,  G10L15/02 ,  G10L15/22

Abstract: Techniques are provided for wake-on-voice (WOV) key-phrase enrollment. A methodology implementing the techniques according to an embodiment includes generating a WOV key-phrase model based on identification of the sequence of sub-phonetic units of a user-provided key-phrase. The WOV key-phrase model is employed by a WOV processor for detection of the user spoken key-phrase and triggering operation of an automatic speech recognition (ASR) processor in response to the detection. The method further includes updating an ASR language model based on the user-provided key-phrase. The update includes one of embedding the WOV key-phrase model into the ASR language model, converting sub-phonetic units of the WOV key-phrase model and embedding the converted WOV key-phrase model into the ASR language model, or generating an ASR key-phrase model by applying a phoneme-syllable based statistical language model to the user-provided key-phrase and embedding the generated ASR key-phrase model into the ASR language model.

公开(公告)号：US20190005945A1

公开(公告)日：2019-01-03

申请号：US15637559

申请日：2017-06-29

Applicant: INTEL IP CORPORATION

Inventor： Joachim Hofer ,  Josef G. Bauer ,  Piotr Rozen ,  Georg Stemmer

IPC: G10L15/16 ,  G10L15/14 ,  G10L25/30 ,  G10L15/26

Abstract: Techniques are provided for calculating reset parameters for recurrent neural networks (RNN). A methodology implementing the techniques according to an embodiment includes generating a sequence of statistics. The calculation of each statistic is based on outputs of an RNN that is periodically re-initialized at a selected RNN reset time such that each of the calculated statistics is associated with a unique RNN reset time selected from a pre-determined range of reset times. The method further includes analyzing the sequence to identify a maximum interval during which the sequence remains relatively constant. The method further includes selecting a reset time parameter and reset context duration parameter, for re-initialization of the RNN during operation. The reset time parameter is based on the duration of the identified maximum interval and the reset context duration parameter is based on a time associated with the starting point of the identified maximum interval.

公开(公告)号：US09899034B2

公开(公告)日：2018-02-20

申请号：US14979108

申请日：2015-12-22

Applicant: Intel IP Corporation

Inventor： Joachim Hofer ,  Tobias Bocklet ,  Georg Stemmer ,  David Pearce ,  Sebastian Czyryba ,  Josef G. Bauer

IPC: G10L25/51 ,  G10L25/24 ,  G10L25/72 ,  G10L25/27

CPC classification number: G10L25/51 ,  G10L15/16 ,  G10L25/24 ,  G10L25/27 ,  G10L25/72

Abstract: Technologies for identifying sounds are disclosed. A sound identification device may capture sound data, and split the sound data into frames. The sound identification device may then determine an acoustic feature vector for each frame, and determine parameters based on how each acoustic feature varies over the duration of time corresponding to the frames. The sound identification device may then determine if the sound matches a pre-defined sound based on the parameters. In one embodiment, the sound identification device may be a baby monitor, and the pre-defined sound may be a baby crying.

公开(公告)号：US10672380B2

公开(公告)日：2020-06-02

申请号：US15855379

申请日：2017-12-27

Applicant: INTEL IP CORPORATION

Inventor： Munir Nikolai Alexander Georges ,  Tobias Bocklet ,  Georg Stemmer ,  Joachim Hofer ,  Josef G. Bauer

IPC: G10L15/00 ,  G10L15/06 ,  G10L15/187 ,  G10L15/02 ,  G10L15/22 ,  G10L15/08

Abstract: Techniques are provided for wake-on-voice (WOV) key-phrase enrollment. A methodology implementing the techniques according to an embodiment includes generating a WOV key-phrase model based on identification of the sequence of sub-phonetic units of a user-provided key-phrase. The WOV key-phrase model is employed by a WOV processor for detection of the user spoken key-phrase and triggering operation of an automatic speech recognition (ASR) processor in response to the detection. The method further includes updating an ASR language model based on the user-provided key-phrase. The update includes one of embedding the WOV key-phrase model into the ASR language model, converting sub-phonetic units of the WOV key-phrase model and embedding the converted WOV key-phrase model into the ASR language model, or generating an ASR key-phrase model by applying a phoneme-syllable based statistical language model to the user-provided key-phrase and embedding the generated ASR key-phrase model into the ASR language model.

公开(公告)号：US20180349794A1

公开(公告)日：2018-12-06

申请号：US15611104

申请日：2017-06-01

Applicant: INTEL IP CORPORATION

Inventor： Munir Nikolai Alexander Georges ,  Szymon Jessa ,  Georg Stemmer

IPC: G06N99/00 ,  G06F17/27 ,  G10L15/183 ,  G10L15/22 ,  G06N7/00

Abstract: Techniques are provided for rejecting out-of-domain (OD) queries in a language understanding system. A methodology implementing the techniques according to an embodiment includes generating a plurality of in-domain (ID) utterances based on variations of provided ID sentences, and generating a plurality of OD utterances based on variations of provided OD sentences. The method may further include training an ID language model based on the generated ID utterances and training an OD language model based on the generated OD utterances. The ID language model is configured to generate an ID dataset based on calculated probabilities associated with the generated ID utterances. The OD language model is configured to generate an OD dataset based on calculated probabilities associated with the generated OD utterances. The method further includes training a classifier to detect OD queries from a plurality of received queries, the training based on the ID dataset and the OD dataset.