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1. 发明申请

US20220269862A1 WEAKLY SUPERVISED AND EXPLAINABLE TRAINING OF A MACHINE-LEARNING-BASED NAMED-ENTITY RECOGNITION (NER) MECHANISM 有权
公开(公告)号：US20220269862A1
公开(公告)日：2022-08-25
申请号：US17185633
申请日：2021-02-25
申请人： Robert Bosch GmbH
发明人： Jiacheng Li , Haibo Ding , Zhe Feng
IPC分类号： G06F40/295 , G06N3/08 , G06N3/04
摘要： Systems and methods for weakly-supervised training a machine-learning model to perform named-entity recognition. All possible entity candidates and all possible rule candidates are automatically identified in an input data set of unlabeled text. An initial training of the machine-learning model is performed using labels assigned to entity candidates by a set of seeding rules as a first set of training data. The trained machine-learning model is then applied to the unlabeled text and a subset of rules from the rule candidates is identified that produces labels that most accurately match the labels assigned by the trained machine-learning model. The machine-learning model is then retrained using the labels assigned by the identified subset of rules as the second set of training data. This process is iteratively repeated to further refine and improve the performance of the machine-learning model for named-entity recognition.

2. 发明申请

US20210005067A1 System and Method for Audio Event Detection in Surveillance Systems 有权
公开(公告)号：US20210005067A1
公开(公告)日：2021-01-07
申请号：US16976462
申请日：2019-02-20
申请人： Robert Bosch GmbH
发明人： Asif Salekin , Zhe Feng , Shabnam Ghaffarzadegan
IPC分类号： G08B13/16 , G06N3/04 , G10L15/26 , G10L25/30 , G06F16/683
摘要： A method and system for detecting and localizing a target audio event in an audio clip is disclosed. The method and system use utilizes a hierarchical approach in which a dilated convolutional neural network to detect the presence of the target audio event anywhere in an audio clip based on high level audio features. If the target audio event is detected somewhere in the audio clip, the method and system further utilizes a robust audio vector representation that encodes the inherent state of the audio as well as a learned relationship between state of the audio and the particular target audio event that was detected in the audio clip. A bi-directional long short term memory classifier is used to model long term dependencies and determine the boundaries in time of the target audio event within the audio clip based on the audio vector representations.

3. 发明申请

US20190371307A1 Slot Filling in Spoken Language Understanding with Joint Pointer and Attention 审中-公开
公开(公告)号：US20190371307A1
公开(公告)日：2019-12-05
申请号：US16057521
申请日：2018-08-07
申请人： Robert Bosch GmbH
发明人： Lin Zhao , Zhe Feng
IPC分类号： G10L15/197 , G10L15/16 , G10L15/22
摘要： A method for slot-filling in an automated spoken language understanding (SLU) system includes receiving words in a text phrase, generating an encoded output and attention weights using a recurrent neural network (RNN) encoder with an attention mechanism, generating a first and second probability distributions of slot words in an extended slot vocabulary database using an RNN decoder and a pointer network, respectively, for a time step, generating a combined probability distribution based on the first and second probability distributions, and identifying a slot word corresponding to one word in the extended slot vocabulary database having a highest probability value in the combined probability distribution for the time step.

4. 发明申请

US20160313868A1 System and Method for Dialog-Enabled Context-Dependent and User-Centric Content Presentation 审中-公开
标题翻译：具有对话框的上下文相关性和以用户为中心的内容呈现的系统和方法
公开(公告)号：US20160313868A1
公开(公告)日：2016-10-27
申请号：US15104695
申请日：2014-12-11
申请人： Fuliang Weng , Kui Xu , Fel Liu , Lin Zhao , Zhe Feng , Zhongnan Shen , ROBERT BOSCH GMBH
发明人： Fuliang Weng , Kui Xu , Fel Liu , Lin Zhao , Zhe Feng , Zhongnan Shen
IPC分类号： G06F3/0481 , B60K35/00 , H04L29/06 , H04L29/08 , G10L15/22 , G06F3/01
CPC分类号： G06F3/0481 , B60K35/00 , B60K2350/1028 , B60K2350/1044 , B60K2350/1052 , B60K2350/2052 , B60K2350/901 , B60K2350/962 , G06F3/017 , G06F3/04883 , G06F9/451 , G06F2203/0381 , G06Q30/02 , G10L15/22 , H04L65/4069 , H04L67/12
摘要： An in-vehicle infotainment system, smart home information access and device control unit, or mobile system presents summarized information to a user based on a user preference model that is associated with the user. The system modifies the presentation of information to the user based on environmental context data about the vehicle and user context data about the activity of the user. During presentation of the information, the system modifies the content and presentation of the summarized information in response to multi-modal input requests from the user.
摘要翻译：车载信息娱乐系统，智能家居信息访问和设备控制单元或移动系统基于与用户相关联的用户偏好模型向用户呈现总结信息。系统基于关于车辆的环境上下文数据和关于用户的活动的用户上下文数据来向用户修改信息呈现。在呈现信息期间，系统响应于来自用户的多模式输入请求来修改总结信息的内容和呈现。

5. 发明申请

US20150348543A1 Speech Recognition of Partial Proper Names by Natural Language Processing 有权
标题翻译：通过自然语言处理语言识别部分正确名称
公开(公告)号：US20150348543A1
公开(公告)日：2015-12-03
申请号：US14728118
申请日：2015-06-02
申请人： Robert Bosch GmbH
发明人： Lin Zhao , Zhe Feng , Kui Xu , Fuliang Weng
IPC分类号： G10L15/18
CPC分类号： G10L15/19
摘要： A method for speech recognition of partial proper names is described which includes natural language processing (NLP), partial name candidate generation, speech recognition and post processing. Natural language processing techniques including shallow and deep parsing are applied to long proper names to identify syntactic units (for example, noun phrases). The syntactic units form a basis for generating a candidate list of partial names for each original full name. A partial name is part of the original name, with some words omitted, or word order changed, or even word substitution. After candidate partial names are generated, their phonetic transcriptions are incorporated into a model for a speech recognizer to recognize the partial names in a speech recognition system.
摘要翻译：描述了一种用于部分专有名称的语音识别的方法，其包括自然语言处理（NLP），部分名称候选生成，语音识别和后处理。自然语言处理技术，包括浅层和深层解析，适用于长名称，以识别句法单位（例如名词短语）。语法单元构成了为每个原始全名生成候选名单的基础。部分名称是原始名称的一部分，省略一些单词，或更改字词顺序，甚至单词替换。在生成候选部分名称之后，其语音转录被并入用于语音识别器的模型中以识别语音识别系统中的部分名称。

6. 发明授权

US09153229B2 Methods and systems for adapting grammars in hybrid speech recognition engines for enhancing local SR performance 有权
标题翻译：在混合语音识别引擎中调整语法的方法和系统，用于增强本地SR性能
公开(公告)号：US09153229B2
公开(公告)日：2015-10-06
申请号：US13683312
申请日：2012-11-21
申请人： Robert Bosch GmbH
发明人： Kui Xu , Fuliang Weng , Zhe Feng
IPC分类号： G10L15/00 , G10L15/01 , G10L15/065 , G10L15/30
CPC分类号： G10L15/01 , G10L15/005 , G10L15/065 , G10L15/30
摘要： A speech recognition method includes providing a processor communicatively coupled to each of a local speech recognition engine and a server-based speech recognition engine. A first speech input is inputted into the server-based speech recognition engine. A first recognition result from the server-based speech recognition engine is received at the processor. The first recognition result is based on the first speech input. The first recognition result is stored in a memory device in association with the first speech input. A second speech input is inputted into the local speech recognition engine. The first recognition result is retrieved from the memory device. A second recognition result is produced by the local speech recognition engine. The second recognition result is based on the second speech input and is dependent upon the retrieved first recognition result.
摘要翻译：语音识别方法包括提供通信地耦合到本地语音识别引擎和基于服务器的语音识别引擎中的每一个的处理器。第一语音输入被输入到基于服务器的语音识别引擎中。在处理器处接收来自基于服务器的语音识别引擎的第一识别结果。第一个识别结果是基于第一个语音输入。第一识别结果与第一语音输入相关联地存储在存储设备中。第二语音输入被输入到本地语音识别引擎中。从存储器件检索第一识别结果。第二识别结果由本地语音识别引擎产生。第二识别结果基于第二语音输入，并且取决于检索到的第一识别结果。

7. 发明授权

US11036774B2 Knowledge-based question answering system for the DIY domain 有权
公开(公告)号：US11036774B2
公开(公告)日：2021-06-15
申请号：US16151835
申请日：2018-10-04
申请人： Robert Bosch GmbH
发明人： Lin Zhao , Zhe Feng , Doo Soon Kim
IPC分类号： G06F16/00 , G06N5/00 , G06F16/332 , G06F16/33 , G06F16/9535 , G06N5/02 , G06F16/242 , G06F16/36 , G06F16/9032 , G06F40/56
摘要： DIY (Do-It-Yourself) is challenging for many novices, requiring extensive knowledge such as the usage of particular tools and the properties of the required materials. Many DIYers use web searches to find relevant information and instructions, but web search is time-consuming and the results often do not fit the DIYers' specific needs. To address these problems, we present a Question Answering (QA) system that can assist DIYers through the whole cycle of a DIY project. Given a natural language question about a DIY project, the QA system described herein provides an answer along with the explanations that are tailored to the DIYers' specific needs.

8. 发明申请

US20190272845A1 System and Method for Monitoring Dietary Activity 审中-公开
公开(公告)号：US20190272845A1
公开(公告)日：2019-09-05
申请号：US16284309
申请日：2019-02-25
申请人： Robert Bosch GmbH
发明人： Taufiq Hasan , Shabnam Ghaffarzadegan , Zhe Feng
IPC分类号： G10L25/51 , G16H20/60 , H04R29/00 , H04R1/08 , G10L25/21
摘要： A system for monitoring dietary activity of a user includes a wearable device having at least one audio input unit configured to record an audio sample corresponding to audio from a user's neck. The system further includes a processor configured to execute programmed instructions stored in a memory to obtain an audio sample from the audio input unit of a wearable device, determine segmental feature values of a set of selected features from the audio sample by extracting short-term features in the set of selected features from the audio sample and determining the segmental feature values of the set of selected features from the extracted short-term features. The processor is further configured to, using a classifier, classify a dietary activity based on the determined segmental feature values of the audio sample and generate an output corresponding to the classified dietary activity.

9. 发明申请

US20190005027A1 System and Method For Domain-Independent Aspect Level Sentiment Detection 审中-公开
公开(公告)号：US20190005027A1
公开(公告)日：2019-01-03
申请号：US16016106
申请日：2018-06-22
申请人： Robert Bosch GmbH
发明人： Yifan He , Lin Zhao , Kui Xu , Zhe Feng
IPC分类号： G06F17/27 , G06N99/00 , G06Q50/00 , G06Q30/02 , G06F17/28
摘要： A method for automated aspect-based sentiment analysis includes parsing reviews from a first domain to generate rhetorical structure trees and extracting rhetorical rules from the rhetorical structure trees, each rhetorical rule including a path extracted from at least one span in at least one of the rhetorical structure trees associated with a probability that the path corresponds to a positive or negative sentiment based on annotation data. The method further includes parsing reviews from a second domain to generate a second plurality of rhetorical structure trees, generating training data that associates at least one aspect in the review from the second domain with a sentiment associated with a rhetorical rule in the plurality of rhetorical rules, and training a classifier to identify sentiments in reviews from the second domain using the second plurality of reviews and the training data.

10. 发明申请

US20180096678A1 System And Method For Speech Recognition 有权
公开(公告)号：US20180096678A1
公开(公告)日：2018-04-05
申请号：US15281973
申请日：2016-09-30
申请人： Robert Bosch GmbH
发明人： Zhengyu Zhou , Zhe Feng
IPC分类号： G10L15/01 , G10L15/08 , G10L15/22
CPC分类号： G10L15/01 , G10L15/08 , G10L15/10 , G10L15/22 , G10L15/32 , G10L2015/088 , G10L2015/223 , G10L2015/228
摘要： A method for automated speech recognition includes generating first and second pluralities of candidate speech recognition results corresponding to audio input data using a first general-purpose speech recognition engine and a second domain-specific speech recognition engine, respectively. The method further includes generating a third plurality of candidate speech recognition result including a plurality of words included in one of the first plurality of speech recognition results and at least one word included in another one of the second plurality of speech recognition results, ranking the third plurality of candidate speech recognition results using a pairwise ranker to identify a highest ranked candidate speech recognition result, and operating the automated system using the highest ranked speech recognition result as an input from the user.

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