CN116312526A - 自然助理交互 - Google Patents
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Abstract
本公开设计自然助理交互。本发明提供了用于操作虚拟助理以提供自然助理交互的系统和过程。根据一个或多个示例，一种方法包括在具有存储器和一个或多个处理器的电子设备处：接收第一音频流，所述第一音频流包括一个或多个话语；确定所述第一音频流是否包括词汇触发；生成所述一个或多个话语的一个或多个候选文本表示；确定所述虚拟助理是否要忽略所述一个或多个候选文本表示的至少一个候选文本表示。如果要忽略至少一个候选文本表示，则基于除了要被忽略的所述至少一个候选文本表示之外的所述一个或多个候选文本表示的候选文本表示，生成一个或多个候选意图。
Description
相关申请的交叉引用
本申请是中国国家申请号为201910147749.1、申请日为2019年2月27日、发明名称为“自然助理交互”的发明专利申请的分案申请。
本专利申请要求于2018年3月26日提交的标题为“NATURAL ASSISTANTINTERACTION(自然助理交互)”的美国临时申请序列号62/648,084和于2018年6月26日提交的标题为“NATURAL ASSISTANT INTERACTION(自然助理交互)”的美国非临时申请序列号16/019,331的优先权。这两个专利申请的内容全文以引用方式并入本文以用于所有目的。
技术领域
这整体涉及虚拟助理，并且更具体地讲，涉及通过虚拟助理提供自然语言交互。
背景技术
虚拟助理(或数字助理或智能自动化助理)可提供有益的人机界面。此类助理可允许用户使用自然语言以语音形式和/或文本形式与设备或系统进行交互。例如，用户可向正在电子设备上运行的数字助理提供包含用户请求的语音输入。虚拟助理可从该语音输入解译用户意图并且将用户意图操作化成任务。随后可通过执行电子设备的一项或多项服务来执行这些任务，并且可将响应于用户请求的相关输出返回给用户。
在接收到触发短语诸如“嘿，Siri”时，虚拟助理可被启用。启用后，虚拟助理可接收和处理用户的语音输入。例如，用户的语音输入可包括前导触发短语，以启用虚拟助理，随后是信息请求(例如，“嘿，Siri，今天的天气如何？”)。然而，用触发短语(例如，“嘿，Siri”)引导每个语音输入可能不方便并且很快会变得麻烦。它也不代表自然的交流方式。例如，当第一用户与第二用户交谈时，第一用户通常不应当用第二用户的名字来引导每个句子。因此，要求用户用触发短语引导每个语音输入并不代表自然的交流方式并且效率较低。
发明内容
本发明提供了用于通过虚拟助理提供自然语言交互的系统和过程。
根据一个或多个示例，方法包括在具有一个或多个处理器、存储器和麦克风的电子设备处：经由麦克风接收第一音频流，第一音频流包括一个或多个话语，以及确定第一音频流是否包括词汇触发。根据确定的第一音频流包括词汇触发，该方法还包括生成一个或多个话语的一个或多个候选文本表示，以及确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示。根据确定的虚拟助理要忽略至少一个候选文本表示，该方法还包括基于除了要被忽略的至少一个候选文本表示之外的一个或多个候选文本表示的候选文本表示生成一个或多个候选意图。该方法还包括确定一个或多个候选意图是否包括至少一个可执行意图。根据确定的一个或多个候选意图包括至少一个可执行意图，该方法还包括执行至少一个可执行意图并输出执行至少一个可执行意图的结果。
本文公开了示例非暂态计算机可读介质。一种示例非暂态计算机可读存储介质存储一个或多个程序。一个或多个程序包括指令，该指令在由电子设备的一个或多个处理器执行时，使得电子设备经由麦克风接收第一音频流，第一音频流包括一个或多个话语；确定第一音频流是否包括词汇触发；根据确定的第一音频流包括词汇触发，生成一个或多个话语的一个或多个候选文本表示；确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示；根据确定的虚拟助理要忽略至少一个候选文本表示，基于除了要被忽略的至少一个候选文本表示之外的一个或多个候选文本表示的候选文本表示生成一个或多个候选意图；确定一个或多个候选意图是否包括至少一个可执行意图；根据确定的一个或多个候选意图包括至少一个可执行意图，执行至少一个可执行意图；以及输出执行至少一个可执行意图的结果。
本文公开了示例电子设备。一种示例电子设备包括：一个或多个处理器；存储器；和一个或多个程序，其中该一个或多个程序存储在存储器中并且被配置为由一个或多个处理器执行，该一个或多个程序包括用于执行以下操作的指令：经由麦克风接收第一音频流，第一音频流包括一个或多个话语；确定第一音频流是否包括词汇触发；根据确定的第一音频流包括词汇触发，生成一个或多个话语的一个或多个候选文本表示；确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示；根据确定的虚拟助理要忽略至少一个候选文本表示，基于除了要被忽略的至少一个候选文本表示之外的一个或多个候选文本表示的候选文本表示生成一个或多个候选意图；确定一个或多个候选意图是否包括至少一个可执行意图；根据确定的一个或多个候选意图包括至少一个可执行意图，执行至少一个可执行意图；输出执行至少一个可执行意图的结果。
示例性电子设备包括：用于经由麦克风接收第一音频流的装置，第一音频流包括一个或多个话语；用于确定第一音频流是否包括词汇触发的装置；根据确定的第一音频流包括词汇触发，用于生成一个或多个话语的一个或多个候选文本表示的装置；用于确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示的装置；根据确定的虚拟助理要忽略至少一个候选文本表示，用于基于除了要被忽略的至少一个候选文本表示之外的一个或多个候选文本表示的候选文本表示生成一个或多个候选意图的装置；用于确定一个或多个候选意图是否包括至少一个可执行意图的装置；根据确定的一个或多个候选意图包括至少一个可执行意图，用于执行至少一个可执行意图的装置；和用于输出执行至少一个可执行意图的结果的装置。
促进基于语音的人机交互的当前技术通常需要在来自用户的话语的开始部分使用触发短语。如上所述，这个要求可使得人机交互变得麻烦并且使得人机用户界面不太自然和高效。在本申请中描述的用于提供自然语言交互的各种技术消除或减少了这种用触发短语引导每个用户话语的要求的需要。相反，触发字词或短语可放置在可包括一个或多个用户话语的音频流的任何部分中。此外，本申请中所述的技术不需要使用包括多个字词的触发短语(例如，“嘿，Siri”)。单个字词(例如，“Siri”)可用于指示包括用户话语的音频流指向虚拟助理。这使得交流方式更加自然。
此外，本申请中描述的用于促进基于语音的人机交互的各种技术提高了设备的可操作性，并且使得用户设备界面更有效(例如，不需要用触发短语引导每个用户话语)，另外，通过使用户能够更快速和有效地使用设备，这还可以降低电力使用并延长设备的电池寿命。
附图说明
图1为示出了根据各种示例的用于实现数字助理的系统和环境的框图。
图2A是示出根据各种示例的实现数字助理的客户端侧部分的便携式多功能设备的框图。
图2B为示出了根据各种示例的用于事件处理的示例性部件的框图。
图3示出了根据各种示例的实现数字助理的客户端侧部分的便携式多功能设备。
图4为根据各种示例的具有显示器和触敏表面的示例性多功能设备的框图。
图5A示出了根据各种示例的便携式多功能设备上的应用程序的菜单的示例性用户界面。
图5B示出了根据各种示例的具有与显示器分开的触敏表面的多功能设备的示例性用户界面。
图6A示出了根据各种示例的个人电子设备。
图6B是示出根据各种示例的个人电子设备的框图。
图7A为示出了根据各种示例的数字助理系统或其服务器部分的框图。
图7B示出了根据各种示例的在图7A中所示的数字助理的功能。
图7C示出了根据各种示例的知识本体的一部分。
图8示出了示例性虚拟助理的框图，以用于提供自然语言交互。
图9示出了示例性用户界面，以用于由虚拟助理提供自然语言交互。
图10示出了示例性虚拟助理的框图，以用于使用上下文信息提供自然语言交互。
图11A示出了示例性用户界面，以用于使用与使用模式相关联的上下文信息、由虚拟助理提供自然语言交互。
图11B示出了示例性用户界面，以用于使用与感官数据相关联的上下文信息、由虚拟助理提供自然语言交互。
图12A至图12D示出了示例性用户界面，以用于使用与执行先前确定的可执行意图相关联的上下文信息、由虚拟助理提供自然语言交互。
图13A至图13B示出了示例性用户界面，以用于使用与用户话语或音频流的关系相关联的上下文信息、由虚拟助理提供自然语言交互。
图14A至图14D示出了示例性用户界面，以用于使用上下文信息从多个任务中选择任务。
图15A至图15G示出了根据各种实施方案的过程，以用于由虚拟助理提供自然语言交互。
具体实施方式
在以下对实施方案的描述中引用附图，在附图中以例示的方式示出了可被实施的特定示例。应当理解，在不脱离各个示例的范围的情况下，可使用其他示例并且可作出结构性变更。
描述了用于促进更自然的人机交互的各种技术。这些技术包括减少或消除使用触发短语引导用户话语的需要，并使用误触发缓解器来提高与确定用户话语是否针对虚拟助理相关联的准确性。这些技术还包括在没有实际执行的情况下执行候选意图评估(例如，进行干运行)，从而确定候选意图是否可操作。这种确定避免了浪费处理能力、用户混淆，从而提高了设备的操作效率。
尽管以下描述使用术语“第一”、“第二”等来描述各种元件，但这些元件不应当受术语的限制。这些术语只是用于将一个元件与另一元件区分开。例如，在不脱离各种所述示例的范围的情况下，第一输入可被称为第二输入，并且类似地，第二输入可被称为第一输入。第一输入和第二输入均为输入，并且在一些情况下为独立且不同的输入。
在本文中对各种所述示例的描述中所使用的术语只是为了描述特定示例的目的，而并非旨在进行限制。如在对各种所述示例的描述和所附权利要求书中所使用的那样，单数形式“一个”和“该”旨在也包括复数形式，除非上下文另外明确地指示。还将理解的是，本文中所使用的术语“和/或”是指并且涵盖相关联的所列出的项目中的一个或多个项目的任何和全部可能的组合。还将理解的是，术语“包括”在本说明书中使用时是指定存在所陈述的特征、整数、步骤、操作、元件和/或部件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、部件和/或其分组。
根据上下文，术语“如果”可被解释为意指“当...时”或“响应于确定”或“响应于检测到”。类似地，根据上下文，短语“如果确定...”或“如果检测到[所陈述的条件或事件]”可被解释为意指“在确定...时”或“响应于确定...”或“在检测到[所陈述的条件或事件]时”或“响应于检测到[所陈述的条件或事件]”。
1.系统和环境
图1示出了根据各种示例的系统100的框图。在一些示例中，系统100实现数字助理。术语“数字助理”、“虚拟助理”、“智能自动化助理”或“自动数字助理”是指解译口头形式和/或文本形式的自然语言输入来推断用户意图，并且基于推断出的用户意图来执行动作的任何信息处理系统。例如，为了作用于推断出的用户意图，系统执行下述步骤中的一个或多个：识别具有设计用于实现推断出的用户意图的步骤和参数的任务流，根据推断出的用户意图将特定要求输入到任务流中；通过调用程序、方法、服务、API等执行任务流；以及以可听(例如，语音)和/或可视形式来生成对用户的输出响应。
具体地讲，数字助理能够接受至少部分地为自然语言命令、请求、声明、讲述和/或询问的形式的用户请求。通常，用户请求要么寻求数字助理作出信息性回答，要么寻求数字助理执行任务。对用户请求的令人满意的响应包括提供所请求的信息性回答、执行所请求的任务或这两者的组合。例如，用户向数字助理提出问题，诸如“我现在在哪里？”。基于用户的当前位置，数字助理回答“你在中央公园西门附近。”用户还请求执行任务，例如“请邀请我的朋友们下周来参加我女朋友的生日聚会。”作为响应，数字助理可通过讲出“好的，马上”来确认请求，然后代表用户将合适的日历邀请发送到用户电子通讯录中列出的用户朋友中的每位朋友。在执行所请求的任务期间，数字助理有时在很长时间段内在涉及多次信息交换的持续对话中与用户进行交互。存在与数字助理进行交互以请求信息或执行各种任务的许多其他方法。除提供言语响应并采取经编程的动作之外，数字助理还提供其他视频或音频形式的响应，例如作为文本、警报、音乐、视频、动画等。
如图1所示，在一些示例中，数字助理根据客户端-服务器模型来实现。数字助理包括在用户设备104上执行的客户端侧部分102(后文称作“DA客户端102”)以及在服务器系统108上执行的服务器侧部分106(后文称作“DA服务器106”)。DA客户端102通过一个或多个网络110与DA服务器106通信。DA客户端102提供客户端侧功能，诸如面向用户的输入和输出处理，以及与DA服务器106通信。DA服务器106为各自位于相应用户设备104上的任意数量的DA客户端102提供服务器侧功能。
在一些示例中，DA服务器106包括面向客户端的I/O接口112、一个或多个处理模块114、数据与模型116，以及到外部服务的I/O接口118。面向客户端的I/O接口112有利于DA服务器106的面向客户端的输入和输出处理。一个或多个处理模块114利用数据与模型116来处理语音输入，并基于自然语言输入来确定用户意图。此外，一个或多个处理模块114基于推断出的用户意图来执行任务执行。在一些示例中，DA服务器106通过一个或多个网络110与外部服务120通信以完成任务或采集信息。到外部服务的I/O接口118促成此类通信。
用户设备104可以是任何合适的电子设备。在一些示例中，用户设备是便携式多功能设备(例如，下面参考图2A描述的设备200)、多功能设备(例如，下面参考图4描述的设备400)或个人电子设备(例如，下面参考图6A至图6B描述的设备600)。便携式多功能设备是例如还包含诸如PDA和/或音乐播放器功能的其他功能的移动电话。便携式多功能设备的特定示例包括来自Apple Inc.(Cupertino,California)的
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设备。便携式多功能设备的其他示例包括但不限于膝上型电脑或平板电脑。此外，在一些示例中，用户设备104是非便携式多功能设备。具体地讲，用户设备104是台式计算机、游戏机、电视或电视机顶盒。在一些示例中，用户设备104包括触敏表面(例如，触摸屏显示器和/或触控板)。此外，用户设备104任选地包括一个或多个其他物理用户接口设备，诸如物理键盘、鼠标和/或操纵杆。下文更详细地描述了电子设备诸如多功能设备的各种示例。
一个或多个通信网络110的示例包括局域网(LAN)和广域网(WAN)，例如互联网。一个或多个通信网络110使用任何已知的网络协议来实现，包括各种有线或无线协议，诸如以太网、通用串行总线(USB)、火线(FIREWIRE)、全球移动通信系统(GSM)、增强型数据GSM环境(EDGE)、码分多址(CDMA)、时分多址(TDMA)、蓝牙、Wi-Fi、互联网协议语音(VoIP)、Wi-MAX或任何其他合适的通信协议。
服务器系统108在一个或多个独立式数据处理设备或分布式计算机网络上实现。在一些示例中，服务器系统108还采用第三方服务提供方(例如，第三方云服务提供方)的各种虚拟设备和/或服务来提供服务器系统108的潜在计算资源和/或基础结构资源。
在一些示例中，用户设备104经由第二用户设备122与DA服务器106通信。第二用户设备122与用户设备104相似或相同。例如，第二用户设备122类似于下文参考图2A、图4和图6A至图6B描述的设备200、设备400或设备600。用户设备104被配置为经由直接通信连接诸如蓝牙、NFC、BTLE等或者经由有线或无线网络诸如局域Wi-Fi网络而通信耦接到第二用户设备122。在一些示例中，第二用户设备122被配置为充当用户设备104与DA服务器106之间的代理。例如，用户设备104的DA客户端102被配置为经由第二用户设备122向DA服务器106传输信息(例如，在用户设备104处接收的用户请求)。DA服务器106处理该信息，并经由第二用户设备122将相关数据(例如，响应于用户请求的数据内容)返回到用户设备104。
在一些示例中，用户设备104被配置为将针对数据的缩略请求发送到第二用户设备122，以减少从用户设备104传输的信息量。第二用户设备122被配置为确定添加到缩略请求的补充信息，以生成完整的请求来传输到DA服务器106。该系统架构可有利地通过使用具有较强通信能力和/或电池电力的第二用户设备122(例如，移动电话、膝上型计算机、平板电脑等)作为到DA服务器106的代理，允许具有有限通信能力和/或有限电池电力的用户设备104(例如，手表或类似的紧凑型电子设备)访问DA服务器106提供的服务。虽然图1中仅示出两个用户设备104和122，但应当理解，在一些示例中，系统100可包括在此代理配置中被配置为与DA服务器系统106通信的任意数量和类型的用户设备。
虽然图1中所示的数字助理包括客户端侧部分(例如，DA客户端102)和服务器侧部分(例如，DA服务器106)两者，但在一些示例中，数字助理的功能被实现为被安装在用户设备上的独立式应用程序。此外，数字助理的客户端部分与服务器部分之间的功能划分在不同的具体实施中可变化。例如，在一些示例中，DA客户端为仅提供面向用户的输入和输出处理功能，并将数字助理的所有其他功能委派给后端服务器的瘦客户端。
2.电子设备
现在将注意力转至用于实现数字助理的客户端侧部分的电子设备的实施方案。图2A是示出根据一些实施方案的具有触敏显示器系统212的便携式多功能设备200的框图。触敏显示器212有时为了方便被叫做“触摸屏”，并且有时被称为或被叫做“触敏显示器系统”。设备200包括存储器202(其任选地包括一个或多个计算机可读存储介质)、存储器控制器222、一个或多个处理单元(CPU)220、外围设备接口218、RF电路208、音频电路210、扬声器211、麦克风213、输入/输出(I/O)子系统206、其他输入控制设备216和外部端口224。设备200任选地包括一个或多个光学传感器264。设备200任选地包括一个或多个接触强度传感器265，以用于检测设备200(例如，设备200的触敏表面诸如触敏显示器系统212)上的接触的强度。设备200任选地包括一个或多个触觉输出发生器267，以用于在设备200上生成触觉输出(例如，在触敏表面诸如设备200的触敏显示器系统212或设备400的触控板455上生成触觉输出)。这些部件可选地通过一个或多个通信总线或信号线203进行通信。
如在本说明书和权利要求书中所使用的，术语触敏表面上的接触的“强度”是指触敏表面上的接触(例如，手指接触)的力或压力(每单位面积的力)，或是指触敏表面上的接触的力或压力的替代物(代用物)。接触的强度具有值范围，该值范围包括至少四个不同的值并且更典型地包括上百个不同的值(例如，至少256个)。接触的强度任选地使用各种方法和各种传感器或传感器的组合来确定(或测量)。例如，在触敏表面下方或相邻于触敏表面的一个或多个力传感器任选地用于测量触敏表面上的不同点处的力。在一些具体实施中，来自多个力传感器的力测量值被组合(例如，加权平均)以确定所估计的接触力。类似地，触笔的压敏顶端任选地用于确定触笔在触敏表面上的压力。另选地，在触敏表面上检测到的接触区域的大小和/或其变化、接触附近的触敏表面的电容和/或其变化以及/或者接触附近的触敏表面的电阻和/或其变化任选地被用作触敏表面上的接触的力或压力的替代物。在一些具体实施中，接触力或压力的替代物测量直接用于确定是否已经超过强度阈值(例如，强度阈值以对应于替代物测量的单位来描述)。在一些具体实施中，接触力或压力的替代物测量被转换成估计的力或压力，并且估计的力或压力用于确定是否已超过强度阈值(例如，强度阈值是以压力的单位进行测量的压力阈值)。使用接触的强度作为用户输入的属性，从而允许用户访问用户在实地面积有限的尺寸更小的设备上本来不可访问的附加设备功能，该尺寸更小的设备用于(例如，在触敏显示器上)显示示能表示和/或接收用户输入(例如，经由触敏显示器、触敏表面或物理控件/机械控件，诸如旋钮或按钮)。
如本说明书和权利要求书中所使用的，术语“触觉输出”是指将由用户利用用户的触感检测到的设备相对于设备的先前位置的物理位移、设备的部件(例如，触敏表面)相对于设备的另一个部件(例如，外壳)的物理位移、或部件相对于设备的质心的位移。例如，在设备或设备的部件与用户对触摸敏感的表面(例如，手指、手掌或用户手部的其他部分)接触的情况下，通过物理位移生成的触觉输出将由用户解释为触感，该触感对应于设备或设备的部件的物理特征的所感知的变化。例如，触敏表面(例如，触敏显示器或触控板)的移动任选地由用户解释为对物理致动按钮的“按下点击”或“松开点击”。在一些情况下，用户将感觉到触感，诸如“按下点击”或“松开点击”，即使在通过用户的移动而物理地被按压(例如，被移位)的与触敏表面相关联的物理致动按钮没有移动时。又如，即使在触敏表面的光滑度无变化时，触敏表面的移动也会任选地由用户解释或感测为触敏表面的“粗糙度”。虽然用户对触摸的此类解释将受到用户的个体化感官知觉的限制，但是对触摸的许多感官知觉是大多数用户共有的。因此，当触觉输出被描述为对应于用户的特定感官知觉(例如，“按下点击”、“松开点击”、“粗糙度”)时，除非另外陈述，否则所生成的触觉输出对应于设备或其部件的物理位移，该物理位移将会生成典型(或普通)用户的所述感官知觉。
应当理解，设备200仅是便携式多功能设备的一个示例，并且设备200任选地具有比所示出的更多或更少的部件，任选地组合两个或多个部件，或者任选地具有这些部件的不同配置或布置。图2A所示的各种部件以硬件、软件或硬件与软件两者的组合来实现，包括一个或多个信号处理和/或专用集成电路。
存储器202包括一个或多个计算机可读存储介质。这些计算机可读存储介质例如为有形的和非暂态的。存储器202包括高速随机存取存储器，并且还包括非易失性存储器，诸如一个或多个磁盘存储设备、闪存存储器设备或其他非易失性固态存储器设备。存储器控制器222控制设备200的其他部件访问存储器202。
在一些示例中，存储器202的非暂态计算机可读存储介质用于存储指令(例如，用于执行下文描述的过程的各方面)以供指令执行系统、装置或设备诸如基于计算机的系统、包含处理器的系统或可从指令执行系统、装置或设备取出指令并执行指令的其他系统使用或与其结合使用。在其他示例中，指令(例如，用于执行下文描述的过程的各方面)存储在服务器系统108的非暂态计算机可读存储介质(未示出)上，或在存储器202的非暂态计算机可读存储介质与服务器系统108的非暂态计算机可读存储介质之间划分。
外围设备接口218用于将设备的输入和输出外围设备耦接到CPU 220和存储器202。所述一个或多个处理器220运行或执行存储器202中所存储的各种软件程序和/或指令集以执行设备200的各种功能并处理数据。在一些实施方案中，外围设备接口218、CPU 220和存储器控制器222在单个芯片诸如芯片204上实现。在一些其他实施方案中，它们在独立的芯片上实现。
RF(射频)电路208接收和发送也被称作电磁信号的RF信号。RF电路208将电信号转换为电磁信号/将电磁信号转换为电信号，并且经由电磁信号与通信网络和其他通信设备进行通信。RF电路208可选地包括熟知的电路，以用于执行这些功能，包括但不限于天线系统、RF收发器、一个或多个放大器、调谐器、一个或多个振荡器、数字信号处理器、编解码芯片组、用户身份模块(SIM)卡、存储器等等。RF电路208可选地通过无线通信来与网络和其他设备进行通信，这些网络为诸如互联网(也被称为万维网(WWW))、内联网和/或无线网络(诸如，蜂窝电话网络、无线局域网(LAN)和/或城域网(MAN))。RF电路208任选地包括熟知的电路，以用于诸如通过近程通信无线电部件来检测近场通信(NFC)场。无线通信任选地使用多种通信标准、协议和技术中的任一种，包括但不限于全球移动通信系统(GSM)、增强型数据GSM环境(EDGE)、高速下行链路分组接入(HSDPA)、高速上行链路分组接入(HSUPA)、演进、纯数据(EV-DO)、HSPA、HSPA+、双小区HSPA(DC-HSPDA)、长期演进(LTE)、近场通信(NFC)、宽带码分多址(W-CDMA)、码分多址(CDMA)、时分多址(TDMA)、蓝牙、蓝牙低功耗(BTLE)、无线保真(Wi-Fi)(例如，IEEE 802.11a、IEEE 802.11b、IEEE 802.11g、IEEE 802.11n和/或IEEE802.11ac)、互联网协议语音(VoIP)、Wi-MAX、电子邮件协议(例如，互联网消息访问协议(IMAP)和/或邮局协议(POP))、即时消息(例如，可扩展消息处理和存在协议(XMPP)、用于即时消息和存在利用扩展的会话发起协议(SIMPLE)、即时消息和存在服务(IMPS))和/或短消息服务(SMS)，或者任何其他适当的通信协议，包括在本文档提交日期时尚未开发出的通信协议。
音频电路210、扬声器211和麦克风213提供用户与设备200之间的音频接口。音频电路210从外围设备接口218接收音频数据，将音频数据转换为电信号，并将电信号传输到扬声器211。扬声器211将电信号转换为人类可听到的声波。音频电路210还接收由麦克风213从声波转换的电信号。音频电路210将电信号转换为音频数据，并且将音频数据传输到外围设备接口218以用于处理。音频数据通过外围设备接口218检索自和/或传输至存储器202和/或RF电路208。在一些实施方案中，音频电路210还包括耳麦插孔(例如，图3中的312)。该耳麦插孔提供音频电路210与可移除的音频输入/输出外围设备之间的接口，该可移除的音频输入/输出外围设备诸如仅输出的耳机或者具有输出(例如，单耳耳机或双耳耳机)和输入(例如，麦克风)两者的耳麦。
I/O子系统206将设备200上的输入/输出外围设备诸如触摸屏212和其他输入控制设备216耦接到外围设备接口218。I/O子系统206任选地包括显示控制器256、光学传感器控制器258、强度传感器控制器259、触觉反馈控制器261，以及用于其他输入或控制设备的一个或多个输入控制器260。该一个或多个输入控制器260从其他输入控制设备216接收电信号/将电信号发送到所述其他输入控制设备。其他输入控制设备216任选地包括物理按钮(例如，下压按钮、摇臂按钮等)、拨号盘、滑动开关、操纵杆、点击轮等。在一些另选实施方案中，输入控制器260任选地耦接至以下各项中的任一者(或不耦接至以下各项中的任一者)：键盘、红外线端口、USB端口和指向设备诸如鼠标。所述一个或多个按钮(例如，图3中的308)任选地包括增大/减小按钮，以用于扬声器211和/或麦克风213的音量控制。所述一个或多个按钮任选地包括下压按钮(例如，图3中的306)。
快速按下下压按钮会脱离触摸屏212的锁定或者开始使用触摸屏上的手势来对设备进行解锁的过程，如在2005年12月23日提交的名称为“Unlocking a Device byPerforming Gestures on an Unlock Image”(通过在解锁图像上执行手势解锁设备)的美国专利No.7,657,849的美国专利申请11/322,549中所述的，该美国专利申请据此全文以引用方式并入本文。较长地按下下压按钮(例如，306)使设备200开机或关机。用户能够自定义一个或多个按钮的功能。触摸屏212用于实现虚拟按钮或软按钮以及一个或多个软键盘。
触敏显示器212提供设备和用户之间的输入接口和输出接口。显示控制器256从触摸屏212接收电信号和/或将电信号发送至该触摸屏。触摸屏212向用户显示视觉输出。视觉输出包括图形、文本、图标、视频及其任何组合(统称为“图形”)。在一些实施方案中，一些视觉输出或全部视觉输出对应于用户界面对象。
触摸屏212具有基于触觉和/或触感接触来接受来自用户的输入的触敏表面、传感器或传感器组。触摸屏212和显示控制器256(与存储器202中的任何相关联的模块和/或指令集一起)检测触摸屏212上的接触(和该接触的任何移动或中断)，并且将所检测到的接触转换为与被显示在触摸屏212上的用户界面对象(例如，一个或多个软键、图标、网页或图像)的交互。在示例性实施方案中，触摸屏212与用户之间的接触点对应于用户的手指。
触摸屏212使用LCD(液晶显示器)技术、LPD(发光聚合物显示器)技术或LED(发光二极管)技术，但在其他实施方案中可使用其他显示技术。触摸屏212和显示控制器256使用目前已知或以后将开发的多种触摸感测技术中的任何技术，以及其他接近传感器阵列或用于确定与触摸屏212接触的一个或多个点的其他元件来检测接触及其任何移动或中断，所述多种触摸感测技术包括但不限于电容式、电阻式、红外和表面声波技术。在示例性实施方案中，使用投射式互电容感测技术，诸如在来自Apple Inc.(Cupertino,California)的
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中使用的技术。
在一些实施方案中，触摸屏212的触敏显示器类似于以下美国专利：6,323,846(Westerman等人)、6,570,557(Westerman等人)和/或6,677,932(Westerman)和/或美国专利公开2002/0015024A1中所述的多触敏触控板，这些专利申请均据此全文以引用方式并入本文。然而，触摸屏212显示来自设备200的视觉输出，而触敏触摸板不提供视觉输出。
在一些实施方案中，触摸屏212的触敏显示器如以下专利申请所述：(1)2006年5月2日提交的名称为“Multipoint Touch Surface Controller”(多点触摸表面控制器)的美国专利申请No.11/381,313；(2)2004年5月6日提交的名称为“Multipoint Touchscreen”的美国专利申请No.10/840,862；(3)2004年7月30日提交的名称为“Gestures For TouchSensitive Input Devices”的美国专利申请No.10/903,964；(4)2005年1月31日提交的名称为“Gestures For Touch Sensitive Input Devices”的美国专利申请11/048,264；(5)2005年1月18日提交的名称为“Mode-Based Graphical User Interfaces For TouchSensitive Input Devices”的美国专利申请No.11/038,590；(6)2005年9月16日提交的名称为“Virtual Input Device Placement On A Touch Screen User Interface”的美国专利申请No.11/228,758；(7)2005年9月16日提交的名称为“Operation Of A Computer WithA Touch Screen Interface”的美国专利申请No.11/228,700；(8)2005年9月16日提交的名称为“Activating Virtual Keys Of A Touch-Screen Virtual Keyboard”的美国专利申请No.11/228,737；以及(9)2006年3月3日提交的名称为“Multi-Functional Hand-HeldDevice”的美国专利申请No.11/367,749。所有这些申请全文以引用方式并入本文。
触摸屏212例如具有超过100dpi的视频分辨率。在一些实施方案中，触摸屏具有约160dpi的视频分辨率。用户使用任何合适的对象或附加物诸如触笔、手指等与触摸屏212进行接触。在一些实施方案中，将用户界面设计为主要通过基于手指的接触和手势来工作，由于手指在触摸屏上的接触区域较大，因此这可能不如基于触笔的输入精确。在一些实施方案中，设备将基于手指的粗略输入转化为精确的指针/光标位置或命令以用于执行用户所期望的动作。
在一些实施方案中，除了触摸屏之外，设备200还包括触控板(未示出)，以用于启用或停用特定功能。在一些实施方案中，触控板是设备的触敏区域，与触摸屏不同，该触敏区域不显示视觉输出。触控板是与触摸屏212分开的触敏表面，或者是由触摸屏形成的触敏表面的延伸。
设备200还包括电力系统262，以用于为各种部件供电。电力系统262包括电力管理系统、一个或多个电源(例如，电池、交流电(AC))、再充电系统、电力故障检测电路、功率转换器或逆变器、电力状态指示器(例如，发光二极管(LED))和与便携式设备中电力的生成、管理和分配相关联的任何其他部件。
设备200还包括一个或多个光学传感器264。图2A示出了耦接到I/O子系统206中的光学传感器控制器258的光学传感器。光学传感器264包括电荷耦合器件(CCD)或互补金属氧化物半导体(CMOS)光电晶体管。光学传感器264从环境接收通过一个或多个透镜而投射的光，并且将光转换为表示图像的数据。结合成像模块243(也叫做相机模块)，光学传感器264捕获静态图像或视频。在一些实施方案中，光学传感器位于设备200的后部，与设备前部的触摸屏显示器212相背对，使得触摸屏显示器被用作用于静态图像和/或视频图像采集的取景器。在一些实施方案中，光学传感器位于设备的前部，使得在用户在触摸屏显示器上查看其他视频会议参与者的同时获取该用户的图像以用于视频会议。在一些实施方案中，光学传感器264的位置可由用户改变(例如，通过旋转设备外壳中的透镜和传感器)，使得单个光学传感器264与触摸屏显示器一起使用以用于视频会议和静态图像和/或视频图像采集两者。
设备200任选地还包括一个或多个接触强度传感器265。图2A示出了耦接到I/O子系统206中的强度传感器控制器259的接触强度传感器。接触强度传感器265任选地包括一个或多个压阻应变仪、电容式力传感器、电气力传感器、压电力传感器、光学力传感器、电容式触敏表面或其他强度传感器(例如，用于测量触敏表面上的接触的力(或压力)的传感器)。接触强度传感器265从环境接收接触强度信息(例如，压力信息或压力信息的代用物)。在一些实施方案中，至少一个接触强度传感器与触敏表面(例如，触敏显示器系统212)并置排列或邻近。在一些实施方案中，至少一个接触强度传感器位于设备200的后部上，与位于设备200的前部上的触摸屏显示器212相背对。
设备200还包括一个或多个接近传感器266。图2A示出了耦接到外围设备接口218的接近传感器266。另选地，接近传感器266耦接到I/O子系统206中的输入控制器260。接近传感器266如以下美国专利申请中所述的那样执行：No.11/241,839，名称为“ProximityDetector In Handheld Device”；No.11/240,788，名称为“Proximity Detector InHandheld Device”；No.11/620,702，名称为“Using Ambient Light Sensor To AugmentProximity Sensor Output”；No.11/586,862，名称为“Automated Response To AndSensing Of User Activity In Portable Devices”；以及No.11/638,251，名称为“Methods And Systems For Automatic Configuration Of Peripherals”，这些美国专利申请据此全文以引用方式并入本文。在一些实施方案中，当多功能设备被置于用户的耳朵附近时(例如，当用户正在进行电话呼叫时)，接近传感器关闭并且禁用触摸屏212。
设备200可选地还包括一个或多个触觉输出发生器267。图2A示出了耦接到I/O子系统206中的触觉反馈控制器261的触觉输出发生器。触觉输出发生器267任选地包括一个或多个电声设备诸如扬声器或其他音频部件；和/或用于将能量转换成线性运动的机电设备诸如电机、螺线管、电活性聚合器、压电致动器、静电致动器或其他触觉输出生成部件(例如，用于将电信号转换成设备上的触觉输出的部件)。接触强度传感器265从触觉反馈模块233接收触觉反馈生成指令，并且在设备200上生成能够由设备200的用户感觉到的触觉输出。在一些实施方案中，至少一个触觉输出发生器与触敏表面(例如，触敏显示器系统212)并置排列或邻近，并且任选地通过竖直地(例如，向设备200的表面内/外)或侧向地(例如，在与设备200的表面相同的平面中向后和向前)移动触敏表面来生成触觉输出。在一些实施方案中，至少一个触觉输出发生器传感器位于设备200的后部上，与位于设备200的前部上的触摸屏显示器212相背对。
设备200还包括一个或多个加速度计268。图2A示出了耦接至外围设备接口218的加速度计268。另选地，加速度计268耦接至I/O子系统206中的输入控制器260。加速度计268如以下美国专利公开中所述那样执行：美国专利公开20050190059，“Acceleration-basedTheft Detection System for Portable Electronic Devices”和美国专利公开20060017692，“Methods And Apparatuses For Operating A Portable Device Based OnAn Accelerometer”，这两个美国专利公开全文以引用方式并入本文。在一些实施方案中，基于对从一个或多个加速度计接收的数据的分析来在触摸屏显示器上以纵向视图或横向视图显示信息。设备200任选地除了加速度计268之外还包括磁力仪(未示出)和GPS(或GLONASS或其他全球导航系统)接收器(未示出)，以用于获取关于设备200的位置和取向(例如，纵向或横向)的信息。
在一些实施方案中，存储于存储器202中的软件部件包括操作系统226、通信模块(或指令集)228、接触/运动模块(或指令集)230、图形模块(或指令集)232、文本输入模块(或指令集)234、全球定位系统(GPS)模块(或指令集)235、数字助理客户端模块229以及应用程序(或指令集)236。此外，存储器202存储数据与模型，诸如用户数据与模型231。此外，在一些实施方案中，存储器202(图2A)或470(图4)存储设备/全局内部状态257，如图2A和图4中所示。设备/全局内部状态257包括下述各项中的一者或多者：活动应用程序状态，其指示哪些应用程序(如果有的话)当前是活动的；显示状态，其指示什么应用程序、视图或其他信息占据触摸屏显示器212的各个区域；传感器状态，包括从设备的各个传感器和输入控制设备216获取的信息；以及关于设备的位置和/或姿态的位置信息。
操作系统226(例如，Darwin、RTXC、LINUX、UNIX、OS X、iOS、WINDOWS、或嵌入式操作系统诸如VxWorks)包括各种软件部件和/或驱动程序，以用于控制和管理一般系统任务(例如，存储器管理、存储设备控制、电源管理等)，并且促进各种硬件部件和软件部件之间的通信。
通信模块228促进通过一个或多个外部端口224来与其他设备进行通信，并且还包括各种软件部件，以用于处理由RF电路208和/或外部端口224所接收的数据。外部端口224(例如，通用串行总线(USB)、火线等)适于直接耦接到其他设备，或间接地通过网络(例如，互联网、无线LAN等)进行耦接。在一些实施方案中，外部端口是与
(Apple Inc.的商标)设备上所使用的30针连接器相同的或类似的和/或与其兼容的多针(例如，30针)连接器。
接触/运动模块230任选地检测与触摸屏212(结合显示控制器256)和其他触敏设备(例如，触摸板或物理点击式转盘)的接触。接触/运动模块230包括各种软件部件以用于执行与接触检测相关的各种操作，诸如确定是否已发生接触(例如，检测手指按下事件)、确定接触强度(例如，接触的力或压力，或者接触的力或压力的替代物)、确定是否存在接触的移动并跟踪在触敏表面上的移动(例如，检测一个或多个手指拖动事件)，以及确定接触是否已停止(例如，检测手指抬起事件或接触断开)。接触/运动模块230从触敏表面接收接触数据。确定接触点的移动任选地包括确定接触点的速率(量值)、速度(量值和方向)和/或加速度(量值和/或方向的改变)，所述接触点的移动由一系列接触数据表示。这些操作任选地被应用于单点接触(例如，单指接触)或者多点同时接触(例如，“多点触摸”/多个手指接触)。在一些实施方案中，接触/运动模块230和显示控制器256检测触摸板上的接触。
在一些实施方案中，接触/运动模块230使用一组一个或多个强度阈值来确定操作是否已由用户执行(例如，确定用户是否已“点击”图标)。在一些实施方案中，根据软件参数来确定强度阈值的至少一个子集(例如，强度阈值不是由具体物理致动器的启用阈值来确定的，并且可在不改变设备200的物理硬件的情况下被调节)。例如，在不改变触控板或触摸屏显示器硬件的情况下，触控板或触摸屏的鼠标“点击”阈值可被设定成预定义的阈值的大范围中的任一个阈值。另外，在一些具体实施中，向设备的用户提供用于调节一组强度阈值中的一个或多个强度阈值(例如，通过调节各个强度阈值和/或通过利用对“强度”参数的系统级点击来一次调节多个强度阈值)的软件设置。
接触/运动模块230任选地检测用户的手势输入。触敏表面上的不同手势具有不同的接触模式(例如，所检测到的接触的不同运动、计时和/或强度)。因此，任选地通过检测特定接触模式来检测手势。例如，检测手指轻击手势包括检测手指按下事件，然后在与手指按下事件相同的位置(或基本上相同的位置)处(例如，在图标的位置处)检测手指抬起(抬离)事件。作为另一个示例，在触敏表面上检测手指轻扫手势包括检测手指按下事件，然后检测一个或多个手指拖动事件，并且随后检测手指抬起(抬离)事件。
图形模块232包括各种已知的软件部件，以用于在触摸屏212或其他显示器上呈现和显示图形，包括用于改变所显示的图形的视觉冲击(例如，亮度、透明度、饱和度、对比度或其他视觉特征)的部件。如本文所用，术语“图形”包括可被显示给用户的任何对象，非限制性地包括文本、网页、图标(诸如，包括软键的用户界面对象)、数字图像、视频、动画等。
在一些实施方案中，图形模块232存储表示待使用的图形的数据。每个图形任选地被分配有对应的代码。图形模块232从应用程序等接收用于指定待显示的图形的一个或多个代码，在必要的情况下还一起接收坐标数据和其他图形属性数据，并且然后生成屏幕图像数据，以输出至显示控制器256。
触觉反馈模块233包括各种软件部件，以用于生成指令，该指令由触觉输出发生器267使用，以便响应于用户与设备200的交互而在设备200上的一个或多个位置处产生触觉输出。
在一些示例中作为图形模块232的部件的文本输入模块234提供用于在各种应用程序(例如，联系人237、电子邮件240、IM 241、浏览器247和需要文本输入的任何其他应用程序)中输入文本的软键盘。
GPS模块235确定设备的位置，并提供该信息以供在各种应用程序中使用(例如提供给电话238以供在基于位置的拨号中使用；提供给相机243作为图片/视频元数据；以及提供给提供基于位置的服务的应用，诸如天气桌面小程序、本地黄页桌面小程序和地图/导航桌面小程序)。
数字助理客户端模块229包括各种客户端侧数字助理指令，以提供数字助理的客户端侧功能。例如，数字助理客户端模块229能够通过便携式多功能设备200的各种用户接口(例如，麦克风213、加速度计268、触敏显示器系统212、光学传感器229、其他输入控制设备216等)接受声音输入(例如，语音输入)、文本输入、触摸输入和/或手势输入。数字助理客户端模块229还能够通过便携式多功能设备200的各种输出接口(例如，扬声器211、触敏显示器系统212、触觉输出生成器267等)提供音频形式的输出(例如，语音输出)、视觉形式的输出和/或触觉形式的输出。例如，将输出提供为语音、声音、警报、文本消息、菜单、图形、视频、动画、振动和/或以上两者或更多者的组合。在操作期间，数字助理客户端模块229使用RF电路208与DA服务器106通信。
用户数据与模型231包括与用户相关联的各种数据(例如，用户特定的词汇数据、用户偏好数据、用户指定的名称发音、来自用户电子通讯录的数据、待办事项、购物清单等)以提供数字助理的客户端侧功能。此外，用户数据与模型231包括各种模型(例如，语音识别模型、统计语言模型、自然语言处理模型、知识本体、任务流模型、服务模型等)，以用于处理用户输入并且确定用户意图。
在一些示例中，数字助理客户端模块229利用便携式多功能设备200的各种传感器、子系统和外围设备来从便携式多功能设备200的周围环境采集附加信息，以建立与用户、当前用户交互和/或当前用户输入相关联的上下文。在一些示例中，数字助理客户端模块229将上下文信息或其子集与用户输入一起提供至DA服务器106以帮助推断用户意图。在一些示例中，数字助理还使用上下文信息来确定如何准备输出并将其传送给用户。上下文信息被称为上下文数据。
在一些示例中，伴随用户输入的上下文信息包括传感器信息，例如照明、环境噪声、环境温度、周围环境的图像或视频等。在一些示例中，上下文信息还可包括设备的物理状态，例如设备取向、设备位置、设备温度、功率电平、速度、加速度、运动模式、蜂窝信号强度等。在一些示例中，将与DA服务器106的软件状态相关的信息，例如便携式多功能设备200的运行过程、已安装程序、过去和当前的网络活动、后台服务、错误日志、资源使用等，作为与用户输入相关联的上下文信息提供至DA服务器106。
在一些示例中，数字助理客户端模块229响应于来自DA服务器106的请求而选择性地提供存储在便携式多功能设备200上的信息(例如，用户数据231)。在一些示例中，数字助理客户端模块229还在DA服务器106请求时引出来自用户经由自然语言对话或其他用户接口的附加输入。数字助理客户端模块229将该附加输入传送至DA服务器106，以帮助DA服务器106进行意图推断和/或满足在用户请求中表达的用户意图。
下面参考图7A-图7C对数字助理进行更详细的描述。应当认识到，数字助理客户端模块229可包括下文所述的数字助理模块726的任意数量的子模块。
应用程序236包括以下模块(或指令集)或者其子集或超集：
·联系人模块237(有时称为通讯录或联系人列表)；
·电话模块238；
·视频会议模块239；
·电子邮件客户端模块240；
·即时消息(IM)模块241；
·健身支持模块242；
·用于静态图像和/或视频图像的相机模块243；
·图像管理模块244；
·视频播放器模块；
·音乐播放器模块；
·浏览器模块247；
·日历模块248；
·桌面小程序模块249，其在一些示例中包括以下各项中的一者或多者：天气桌面小程序249-1、股票桌面小程序249-2、计算器桌面小程序249-3、闹钟桌面小程序249-4、词典桌面小程序249-5和用户获取的其他桌面小程序以及用户创建的桌面小程序249-6；
·用于形成用户创建的桌面小程序249-6的桌面小程序创建器模块250；
·搜索模块251；
·视频和音乐播放器模块252，其合并视频播放器模块和音乐播放器模块；
·记事本模块253；
·地图模块254；和/或
·在线视频模块255。
存储在存储器202中的其他应用程序236的示例包括其他文字处理应用程序、其他图像编辑应用程序、绘图应用程序、呈现应用程序、支持JAVA的应用程序、加密、数字版权管理、声音识别和声音复制。
结合触摸屏212、显示控制器256、接触/运动模块230、图形模块232、和文本输入模块234，联系人模块237用于管理通讯录或联系人列表(例如，存储在存储器202或存储器470中的联系人模块237的应用程序内部状态292中)，包括：将一个或多个姓名添加到通讯录；从地址簿删除姓名；将电话号码、电子邮件地址、物理地址或其他信息与姓名关联；将图像与姓名关联；对姓名进行归类和分类；提供电话号码或电子邮件地址来发起和/或促进通过电话238、视频会议模块239、电子邮件240或IM 241的通信；等等。
结合RF电路208、音频电路210、扬声器211、麦克风213、触摸屏212、显示控制器256、接触/运动模块230、图形模块232和文本输入模块234，电话模块238用于输入对应于电话号码的字符序列、访问联系人模块237中的一个或多个电话号码、修改已经输入的电话号码、拨打相应的电话号码、进行会话以及当会话完成时断开或挂断。如上所述，无线通信使用多种通信标准、协议和技术中的任一种。
结合RF电路208、音频电路210、扬声器211、麦克风213、触摸屏212、显示控制器256、光学传感器264、光学传感器控制器258、接触/运动模块230、图形模块232、文本输入模块234、联系人模块237和电话模块238，视频会议模块239包括根据用户指令来发起、进行和终止用户与一个或多个其他参与方之间的视频会议的可执行指令。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232和文本输入模块234，电子邮件客户端模块240包括响应于用户指令来创建、发送、接收和管理电子邮件的可执行指令。结合图像管理模块244，电子邮件客户端模块240使得非常容易创建和发送具有由相机模块243拍摄的静态图像或视频图像的电子邮件。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232和文本输入模块234，即时消息模块241包括用于以下操作的可执行指令：输入与即时消息对应的字符序列、修改先前输入的字符、传输相应即时消息(例如，使用短消息服务(SMS)或多媒体消息服务(MMS)协议以用于基于电话的即时消息或者使用XMPP、SIMPLE、或IMPS以用于基于互联网的即时消息)、接收即时消息以及查看所接收的即时消息。在一些实施方案中，所传输和/或接收的即时消息包括图形、照片、音频文件、视频文件和/或如MMS和/或增强型消息服务(EMS)中支持的其他附件。如本文所用，“即时消息”是指基于电话的消息(例如，使用SMS或MMS发送的消息)和基于互联网的消息(例如，使用XMPP、SIMPLE或IMPS发送的消息)两者。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232、文本输入模块234、GPS模块235、地图模块254和音乐播放器模块，健身支持模块242包括用于以下各项的可执行指令：创建健身(例如，具有时间、距离和/或卡路里燃烧目标)；与健身传感器(运动设备)进行通信；接收健身传感器数据；校准用于监视健身的传感器；为健身选择和播放音乐；以及显示、存储和传输健身数据。
结合触摸屏212、显示控制器256、光学传感器264、光学传感器控制器258、接触/运动模块230、图形模块232和图像管理模块244，相机模块243包括用于以下操作的可执行指令：捕获静态图像或视频(包括视频流)并且将它们存储到存储器202中、修改静态图像或视频的特征，或从存储器202删除静态图像或视频。
结合触摸屏212、显示控制器256、接触/运动模块230、图形模块232、文本输入模块234、和相机模块243，图像管理模块244包括可执行指令，以排列、修改(例如，编辑)或以其他方式操控、加标签、删除、呈现(例如，在数字幻灯片或相册中)以及存储静态图像和/或视频图像。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232和文本输入模块234，浏览器模块247包括可执行指令，以根据用户指令来浏览互联网，包括搜索、链接至、接收和显示网页或其部分以及链接至网页的附件和其他文件。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232、文本输入模块234、电子邮件客户端模块240和浏览器模块247，日历模块248包括根据用户指令来创建、显示、修改和存储日历以及与日历相关联的数据(例如，日历条目、待办事项等)的可执行指令。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232、文本输入模块234和浏览器模块247，桌面小程序模块249是可由用户下载并使用的微型应用程序(例如，天气桌面小程序249-1、股市桌面小程序249-2、计算器桌面小程序249-3、闹钟桌面小程序249-4和词典桌面小程序249-5)或由用户创建的微型应用程序(例如，用户创建的桌面小程序249-6)。在一些实施方案中，桌面小程序包括HTML(超文本标记语言)文件、CSS(层叠样式表)文件和JavaScript文件。在一些实施方案中，桌面小程序包括XML(可扩展标记语言)文件和JavaScript文件(例如，Yahoo！桌面小程序)。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232、文本输入模块234和浏览器模块247，桌面小程序创建器模块250被用户用于创建桌面小程序(例如，使网页的用户指定部分变成桌面小程序)。
结合触摸屏212、显示控制器256、接触/运动模块230、图形模块232和文本输入模块234，搜索模块251包括可执行指令，以根据用户指令来搜索存储器202中与一个或多个搜索条件(例如，一个或多个用户指定的搜索词)匹配的文本、音乐、声音、图像、视频和/或其他文件。
结合触摸屏212、显示控制器256、接触/运动模块230、图形模块232、音频电路系统210、扬声器211、RF电路系统208和浏览器模块247，视频和音乐播放器模块252包括允许用户下载和回放以一种或多种文件格式(诸如MP3或AAC文件)存储的所记录的音乐和其他声音文件的可执行指令，以及用于显示、呈现或以其他方式回放视频(例如，在触摸屏212上或在经由外部端口224连接的外部显示器上)的可执行指令。在一些实施方案中，设备200任选地包括MP3播放器诸如iPod(Apple Inc.的商标)的功能。
结合触摸屏212、显示控制器256、接触/运动模块230、图形模块232和文本输入模块234，记事本模块253包括根据用户指令来创建和管理记事本、待办事项等的可执行指令。
结合RF电路208、触摸屏212、显示控制器256、接触/运动模块230、图形模块232、文本输入模块234、GPS模块235和浏览器模块247，地图模块254用于根据用户指令接收、显示、修改和存储地图以及与地图相关联的数据(例如，驾驶方向、与特定位置处或附近的商店及其他兴趣点有关的数据，以及其他基于位置的数据)。
结合触摸屏212、显示控制器256、接触/运动模块230、图形模块232、音频电路210、扬声器211、RF电路208、文本输入模块234、电子邮件客户端模块240和浏览器模块247，在线视频模块255包括允许用户访问、浏览、接收(例如，通过流式传输和/或下载)、回放(例如，在触摸屏上或经由外部端口224在所连接的外部显示器上)、发送具有至特定在线视频的链接的电子邮件，以及以其他方式管理一种或多种文件格式(诸如，H.264)的在线视频的指令。在一些实施方案中，使用即时消息模块241而不是电子邮件客户端模块240来发送特定在线视频的链接。在线视频应用程序的其他描述可见于2007年6月20日提交的名称为“Portable Multifunction Device,Method,and Graphical User Interface forPlaying Online Videos”的美国临时专利申请60/936,562和2007年12月31日提交的名称为“Portable Multifunction Device,Method,and Graphical User Interface forPlaying Online Videos”的美国专利申请11/968,067，这两个专利申请的内容据此全文以引用方式并入本文。
上述每个模块和应用程序对应于用于执行上述一种或多种功能以及在本专利申请中所述的方法(例如，本文所述的计算机实现的方法和其他信息处理方法)的可执行指令集。这些模块(例如，指令集)不必被实现为独立的软件程序、过程或模块，并因此在各种实施方案中可组合或以其他方式重新布置这些模块的各种子集。例如，视频播放器模块可与音乐播放器模块组合成单个模块(例如，图2A中的视频和音乐播放器模块252)。在一些实施方案中，存储器202存储上述模块和数据结构的子集。此外，存储器202存储上文未描述的另外的模块和数据结构。
在一些实施方案中，设备200是该设备上的预定义的一组功能的操作唯一地通过触摸屏和/或触摸板来执行的设备。通过使用触摸屏和/或触控板作为用于设备200的操作的主要输入控制设备，减少设备200上的物理输入控制设备(诸如下压按钮、拨盘等)的数量。
唯一地通过触摸屏和/或触控板来执行的预定义的一组功能任选地包括在用户界面之间的导航。在一些实施方案中，触摸板在被用户触摸时将设备200从设备200上显示的任何用户界面导航到主菜单、home菜单或根菜单。在此类实施方案中，使用触摸板来实现“菜单按钮”。在一些其他实施方案中，菜单按钮是物理下压按钮或者其他物理输入控制设备，而不是触摸板。
图2B是示出了根据一些实施方案的用于事件处理的示例性部件的框图。在一些实施方案中，存储器202(图2A)或存储器470(图4)包括事件分类器270(例如，在操作系统226中)以及相应的应用程序236-1(例如，前述应用程序237至251、255、480至490中的任一个应用程序)。
事件分类器270接收事件信息并确定要将事件信息递送到的应用程序236-1和应用程序236-1的应用程序视图291。事件分类器270包括事件监视器271和事件分配器模块274。在一些实施方案中，应用程序236-1包括应用程序内部状态292，该应用程序内部状态指示当应用程序是活动的或正在执行时被显示在触敏显示器212上的一个或多个当前应用程序视图。在一些实施方案中，设备/全局内部状态257被事件分类器270用来确定哪个(哪些)应用程序当前是活动的，并且应用程序内部状态292被事件分类器270用来确定要将事件信息递送到的应用程序视图291。
在一些实施方案中，应用程序内部状态292包括附加信息，诸如以下各项中的一者或多者：当应用程序236-1恢复执行时将被使用的恢复信息、指示信息正被显示或准备好用于被应用程序236-1显示的用户界面状态信息、用于使得用户能够返回到应用程序236-1的前一状态或视图的状态队列和用户采取的先前动作的重复/撤销队列。
事件监视器271从外围设备接口218接收事件信息。事件信息包括关于子事件(例如，作为多点触摸手势一部分的触敏显示器212上的用户触摸)的信息。外围设备接口218传输其从I/O子系统206或传感器诸如接近传感器266、加速度计268和/或麦克风213(通过音频电路210)接收的信息。外围设备接口218从I/O子系统206接收的信息包括来自触敏显示器212或触敏表面的信息。
在一些实施方案中，事件监视器271以预先确定的间隔将请求发送至外围设备接口218。作为响应，外围设备接口218传输事件信息。在其他实施方案中，外围设备接口218仅当存在显著事件(例如，接收到高于预先确定的噪声阈值的输入和/或接收到超过预先确定的持续时间的输入)时才传输事件信息。
在一些实施方案中，事件分类器270还包括命中视图确定模块272和/或活动事件识别器确定模块273。
当触敏显示器212显示多于一个视图时，命中视图确定模块272提供用于确定子事件已在一个或多个视图内的什么地方发生的软件过程。视图由用户能够在显示器上看到的控件和其他元素构成。
与应用程序相关联的用户界面的另一方面是一组视图，本文中有时也称为应用程序视图或用户界面窗口，在其中显示信息并且发生基于触摸的手势。在其中检测到触摸的(相应应用程序的)应用程序视图对应于应用程序的程序化分级结构或视图分级结构内的程序化水平。例如，在其中检测到触摸的最低水平视图被称为命中视图，并且被认为是正确输入的事件集至少部分地基于初始触摸的命中视图来确定，该初始触摸开始基于触摸的手势。
命中视图确定模块272接收与基于触摸的手势的子事件相关的信息。当应用程序具有以分级结构组织的多个视图时，命中视图确定模块272将命中视图识别为应当对子事件进行处理的分级结构中的最低视图。在大多数情况下，命中视图是发起子事件(例如，形成事件或潜在事件的子事件序列中的第一子事件)在其中发生的最低水平视图。一旦命中视图被命中视图确定模块272识别，命中视图便通常接收与其被识别为命中视图所针对的同一触摸或输入源相关的所有子事件。
活动事件识别器确定模块273确定视图分级结构内的哪个或哪些视图应当接收特定子事件序列。在一些实施方案中，活动事件识别器确定模块273确定仅命中视图应当接收特定子事件序列。在其他实施方案中，活动事件识别器确定模块273确定包括子事件的物理位置的所有视图是活跃参与的视图，并因此确定所有活跃参与的视图都应当接收特定子事件序列。在其他实施方案中，即使触摸子事件完全被局限到与一个特定视图相关联的区域，分级结构中的较高视图应当仍然保持为活跃参与的视图。
事件分配器模块274将事件信息分配到事件识别器(例如，事件识别器280)。在包括活动事件识别器确定模块273的实施方案中，事件分配器模块274将事件信息递送到由活动事件识别器确定模块273确定的事件识别器。在一些实施方案中，事件分配器模块274在事件队列中存储事件信息，该事件信息由相应事件接收器282进行检索。
在一些实施方案中，操作系统226包括事件分类器270。另选地，应用程序236-1包括事件分类器270。在又一个实施方案中，事件分类器270是独立模块，或者是存储在存储器202中的另一个模块(诸如，接触/运动模块230)的一部分。
在一些实施方案中，应用程序236-1包括多个事件处理程序290和一个或多个应用程序视图291，其中的每一个都包括指令，以用于处理发生在应用程序的用户界面的相应视图内的触摸事件。应用程序236-1的每个应用程序视图291包括一个或多个事件识别器280。通常，相应应用程序视图291包括多个事件识别器280。在其他实施方案中，事件识别器280中的一个或多个事件识别器是独立模块的一部分，该独立模块为诸如用户界面工具包(未示出)或应用程序236-1从中继承方法和其他属性的较高级别的对象。在一些实施方案中，相应事件处理程序290包括以下各项中的一者或多者：数据更新器276、对象更新器277、GUI更新器278和/或从事件分类器270接收的事件数据279。事件处理程序290利用或调用数据更新器276、对象更新器277或GUI更新器278来更新应用程序内部状态292。另选地，应用程序视图291中的一个或多个应用程序视图包括一个或多个相应事件处理程序290。另外，在一些实施方案中，数据更新器276、对象更新器277和GUI更新器278中的一者或多者包括在相应应用程序视图291中。
相应的事件识别器280从事件分类器270接收事件信息(例如，事件数据279)，并且从事件信息识别事件。事件识别器280包括事件接收器282和事件比较器284。在一些实施方案中，事件识别器280还包括元数据283和事件传递指令288(其包括子事件传递指令)的至少一个子集。
事件接收器282接收来自事件分类器270的事件信息。事件信息包括关于子事件例如触摸或触摸移动的信息。根据子事件，事件信息还包括附加信息，诸如子事件的位置。当子事件涉及触摸的运动时，事件信息还包括子事件的速率和方向。在一些实施方案中，事件包括设备从一个取向旋转到另一取向(例如，从纵向取向旋转到横向取向，或反之亦然)，并且事件信息包括关于设备的当前取向(也被称为设备姿态)的对应信息。
事件比较器284将事件信息与预定义的事件或子事件定义进行比较，并且基于该比较，确定事件或子事件，或者确定或更新事件或子事件的状态。在一些实施方案中，事件比较器284包括事件定义286。事件定义286包含事件的定义(例如，预定义的子事件序列)，例如事件1(287-1)、事件2(287-2)以及其他事件。在一些实施方案中，事件(287)中的子事件例如包括触摸开始、触摸结束、触摸移动、触摸取消和多点触摸。在一个示例中，事件1(287-1)的定义是在被显示对象上的双击。例如，双击包括被显示对象上的预先确定时长的第一触摸(触摸开始)、预先确定时长的第一抬离(触摸结束)、被显示对象上的预先确定时长的第二触摸(触摸开始)以及预先确定时长的第二抬离(触摸结束)。在另一个示例中，事件2(287-2)的定义是在被显示对象上的拖动。例如，拖动包括被显示对象上的预先确定时长的触摸(或接触)、触摸在触敏显示器212上的移动、以及触摸的抬离(触摸结束)。在一些实施方案中，事件还包括信息，以用于一个或多个相关联的事件处理程序290。
在一些实施方案中，事件定义287包括事件的定义，以用于相应用户界面对象。在一些实施方案中，事件比较器284执行命中测试以确定哪个用户界面对象与子事件相关联。例如，在触敏显示器212上显示三个用户界面对象的应用程序视图中，当在触敏显示器212上检测到触摸时，事件比较器284执行命中测试以确定这三个用户界面对象中的哪一个用户界面对象与该触摸(子事件)相关联。如果每个所显示对象与相应事件处理程序290相关联，则事件比较器使用该命中测试的结果来确定哪个事件处理程序290应当被启用。例如，事件比较器284选择与子事件和触发该命中测试的对象相关联的事件处理程序。
在一些实施方案中，相应事件(287)的定义还包括延迟动作，所述延迟动作延迟事件信息的递送，直到已确定子事件序列确实对应于或不对应于事件识别器的事件类型。
当相应事件识别器280确定子事件序列不与事件定义286中的任何事件匹配时，该相应事件识别器280进入事件不可能、事件失败或事件结束状态，在此之后忽略基于触摸的手势的后续子事件。在这种情况下，对于命中视图保持活动的其他事件识别器(如果有的话)继续跟踪并处理持续进行的基于触摸的手势的子事件。
在一些实施方案中，相应事件识别器280包括具有指示事件递送系统应当如何执行对活跃参与的事件识别器的子事件递送的可配置属性、标记和/或列表的元数据283。在一些实施方案中，元数据283包括指示事件识别器彼此如何交互或如何能够交互的可配置属性、标志和/或列表。在一些实施方案中，元数据283包括指示子事件是否递送到视图或程序化分级结构中的不同层级的可配置属性、标志和/或列表。
在一些实施方案中，当事件的一个或多个特定子事件被识别时，相应事件识别器280启用与事件相关联的事件处理程序290。在一些实施方案中，相应事件识别器280将与事件相关联的事件信息递送到事件处理程序290。启用事件处理程序290不同于将子事件发送(和延期发送)到相应命中视图。在一些实施方案中，事件识别器280抛出与所识别的事件相关联的标记，并且与该标记相关联的事件处理程序290获取该标记并执行预定义过程。
在一些实施方案中，事件递送指令288包括递送关于子事件的事件信息而不启用事件处理程序的子事件递送指令。相反，子事件递送指令将事件信息递送到与子事件序列相关联的事件处理程序或者递送到活跃参与的视图。与子事件序列或与活跃参与的视图相关联的事件处理程序接收事件信息并执行预先确定的过程。
在一些实施方案中，数据更新器276创建并更新在应用程序236-1中使用的数据。例如，数据更新器276更新联系人模块237中所使用的电话号码或者存储视频播放器模块中所使用的视频文件。在一些实施方案中，对象更新器277创建和更新在应用程序236-1中使用的对象。例如，对象更新器277创建新的用户界面对象或更新用户界面对象的位置。GUI更新器278更新GUI。例如，GUI更新器278准备显示信息，并且将显示信息发送到图形模块232以用于在触敏显示器上显示。
在一些实施方案中，事件处理程序290包括数据更新器276、对象更新器277和GUI更新器278或者具有对其访问权限。在一些实施方案中，数据更新器276、对象更新器277和GUI更新器278被包括在相应应用程序236-1或应用程序视图291的单个模块中。在其他实施方案中，它们被包括在两个或更多个软件模块中。
应当理解，关于触敏显示器上的用户触摸的事件处理的上述论述还适用于利用输入设备来操作多功能设备200的其他形式的用户输入，并不是所有用户输入都是在触摸屏上发起的。例如，任选地与单次或多次键盘按下或按住协作的鼠标移动和鼠标按钮按下；触控板上的接触移动，诸如轻击、拖动、滚动等；触笔输入；设备的移动；口头指令；检测到的眼睛移动；生物特征输入；和/或其任何组合任选地被用作对应于限定要识别的事件的子事件的输入。
图3示出了根据一些实施方案的具有触摸屏212的便携式多功能设备200。触摸屏可选地在用户界面(UI)300内显示一个或多个图形。在本实施方案以及下文所述的其他实施方案中，用户能够通过例如利用一根或多根手指302(在图中未按比例绘制)或一支或多支触笔303(在图中未按比例绘制)在图形上作出手势来选择这些图形中的一个或多个图形。在一些实施方案中，当用户中断与一个或多个图形的接触时，将发生对一个或多个图形的选择。在一些实施方案中，手势任选地包括一次或多次轻击、一次或多次轻扫(从左向右、从右向左、向上和/或向下)和/或已与设备200发生接触的手指的滚动(从右向左、从左向右、向上和/或向下)。在一些具体实施中或在一些情况下，不经意地与图形接触不选择图形。例如，当与选择对应的手势是轻击时，在应用程序图标上方扫动的轻扫手势任选地不选择对应的应用程序。
设备200还包括一个或多个物理按钮，诸如“home”或菜单按钮304。如前所述，菜单按钮304用于导航到在设备200上执行的一组应用程序中的任何应用程序236。另选地，在一些实施方案中，菜单按钮被实现为软键，软键被显示在触摸屏212上的GUI中。
在一些实施方案中，设备200包括触摸屏212、菜单按钮304、用于使设备通电/断电和用于锁定设备的下压按钮306、一个或多个音量调节按钮308、用户身份模块(SIM)卡槽310、耳麦插孔312和对接/充电外部端口224。下压按钮306任选地用于通过压下该按钮并且将该按钮保持在压下状态持续预定义的时间间隔来对设备进行开/关机；通过压下该按钮并在该预定义的时间间隔过去之前释放该按钮来锁定设备；和/或对设备进行解锁或发起解锁过程。在另选的实施方案中，设备200还通过麦克风213接受用于启用或停用某些功能的语音输入。设备200还任选地包括：一个或多个接触强度传感器265，以用于检测触摸屏212上的接触的强度；和/或一个或多个触觉输出发生器267，以用于为设备200的用户生成触觉输出。
图4是根据一些实施方案的具有显示器和触敏表面的示例性多功能设备的框图。设备400不必是便携式的。在一些实施方案中，设备400为膝上型计算机、台式计算机、平板电脑、多媒体播放器设备、导航设备、教育设备(诸如儿童学习玩具)、游戏系统或控制设备(例如，家用控制器或工业用控制器)。设备400通常包括一个或多个处理单元(CPU)410、一个或多个网络或其他通信接口460、存储器470和用于使这些部件互连的一个或多个通信总线420。通信总线420任选地包括电路(有时称作芯片组)，其使系统部件互连并且控制系统部件之间的通信。设备400包括具有显示器440的输入/输出(I/O)接口430，该显示器通常是触摸屏显示器。I/O接口430还任选地包括键盘和/或鼠标(或其他指向设备)450以及触控板455、用于在设备400上生成触觉输出的触觉输出发生器457(例如，类似于以上参考图2A所述的一个或多个触觉输出发生器267)、传感器459(例如，光学传感器、加速度传感器、接近传感器、触敏传感器和/或类似于以上参考图2A所述的一个或多个接触强度传感器265的接触强度传感器)。存储器470包括：高速随机存取存储器，诸如DRAM、SRAM、DDR RAM或其他随机存取固态存储器设备；并且任选地包括非易失性存储器，诸如一个或多个磁盘存储设备、光盘存储设备、闪存存储器设备或其他非易失性固态存储设备。存储器470任选地包括一个或多个存储设备，其远离CPU 410定位。在一些实施方案中，存储器470存储与便携式多功能设备200(图2A)的存储器202中存储的程序、模块和数据结构类似的程序、模块和数据结构或其子集。此外，存储器470任选地存储在便携式多功能设备200的存储器202中不存在的附加程序、模块和数据结构。例如，设备400的存储器470任选地存储绘图模块480、呈现模块482、文字处理模块484、网站创建模块486、盘编辑模块488和/或电子表格模块490，而便携式多功能设备200(图2A)的存储器202任选地不存储这些模块。
图4中的上述元件中的每一者在一些示例中存储在一个或多个先前提到的存储器设备中。上述模块中的每个模块对应于用于执行上述功能的指令集。上述模块或程序(例如，指令集)不必被实现为独立的软件程序、过程或模块，因此这些模块的各种子集在各种实施方案中组合或以其他方式重新布置。在一些实施方案中，存储器470存储上述模块和数据结构的子集。此外，存储器470存储上文未描述的另外的模块和数据结构。
现在将注意力转到可在例如便携式多功能设备200上实现的用户界面的实施方案。
图5A示出了根据一些实施方案的便携式多功能设备200上的应用程序菜单的示例性用户界面。类似的用户界面在设备400上实现。在一些实施方案中，用户界面500包括以下元件或者其子集或超集：
无线通信(诸如蜂窝信号和Wi-Fi信号)的信号强度指示器502；
·时间504；
·蓝牙指示符505；
·电池状态指示符506；
·托盘508，其具有常用应用程序的图标，该图标诸如：
○电话模块238的图标516，被标记为“电话”，该图标可选地包括未接来电或语音留言的数量的指示符514；
○电子邮件客户端模块240图标518,被标记为“邮件”，该图标可选地包括未读电子邮件的数量的指示符510；
○浏览器模块247的图标520，被标记为“浏览器”；以及
○视频和音乐播放器模块252(也称为iPod(Apple Inc.的商标)模块252)的图标522，被标记为“iPod”；和
·其他应用的图标，诸如：
○IM模块241的图标524，被标记为“消息”；
○日历模块248的图标526，被标记为“日历”；
○图像管理模块244的图标528，被标记为“照片”；
○相机模块243的图标530，被标记为“相机”；
○在线视频模块255的图标532，被标记为“在线视频”；
○股市桌面小程序249-2的图标534，被标记为“股市”；
○地图模块254的图标536，被标记为“地图”；
○天气桌面小程序249-1的图标538，被标记为“天气”；
○闹钟桌面小程序249-4的图标540，被标记为“时钟”；
○健身支持模块242的图标542，被标记为“健身支持”；
○记事本模块253的图标544，被标记为“记事本”；和
○用于设置应用程序或模块的图标546，被标记为“设置”，该图标提供对设备200及其各种应用程序236的设置的访问。
应当指出的是，图5A中示出的图标标签仅是示例性的。例如，视频和音乐播放器模块252的图标522任选地被标记为“音乐”或“音乐播放器”。对于各种应用程序图标任选地使用其他标签。在一些实施方案中，相应应用程序图标的标签包括与该相应应用程序图标对应的应用程序的名称。在一些实施方案中，特定应用程序图标的标签不同于与该特定应用程序图标对应的应用程序的名称。
图5B示出了具有与显示器550(例如，触摸屏显示器212)分开的触敏表面551(例如，图4的平板电脑或触控板455)的设备(例如，图4的设备400)上的示例性用户界面。设备400还可选地包括：一个或多个接触强度传感器(例如，传感器457中的一个或多个传感器)，以用于检测触敏表面551上的接触的强度；和/或一个或多个触觉输出发生器459，以用于为设备400的用户生成触觉输出。
尽管将参考触摸屏显示器212(其中组合了触敏表面和显示器)上的输入给出随后的示例中的一些示例，但是在一些实施方案中，设备检测与显示器分开的触敏表面上的输入，如图5B中所示。在一些实施方案中，触敏表面(例如，图5B中的551)具有与显示器(例如，550)上的主轴(例如，图5B中的553)对应的主轴(例如，图5B中的552)。根据这些实施方案，设备检测在与显示器上的相应位置对应的位置(例如，在图5B中，560对应于568并且562对应于570)处的与触敏表面551的接触(例如，图5B中的560和562)。这样，在触敏表面(例如，图5B中的551)与多功能设备的显示器(例如，图5B中的550)分开时，由设备在触敏表面上检测到的用户输入(例如，接触560和562以及其移动)被该设备用于操纵显示器上的用户界面。应当理解，类似的方法任选地用于本文所述的其他用户界面。
另外，虽然主要是参考手指输入(例如，手指接触、单指轻击手势、手指轻扫手势)来给出下面的示例，但是应当理解的是，在一些实施方案中，这些手指输入中的一个或多个手指输入由来自另一输入设备的输入(例如，基于鼠标的输入或触笔输入)替代。例如，轻扫手势任选地由鼠标点击(例如，而不是接触)，之后是光标沿着轻扫的路径的移动(例如，而不是接触的移动)替代。又如，轻击手势任选地由在光标位于轻击手势的位置上方时的鼠标点击(例如，代替对接触的检测，之后是停止检测接触)替代。类似地，当同时检测到多个用户输入时，应当理解的是，多个计算机鼠标任选地被同时使用，或鼠标和手指接触任选地被同时使用。
图6A示出了示例性个人电子设备600。设备600包括主体602。在一些实施方案中，设备600包括相对于设备200和400(例如，图2A-图4)所述的特征中的一些或全部特征。在一些实施方案中，设备600具有触敏显示屏604，以下简称触摸屏604。作为触摸屏604的替代或补充，设备600具有显示器和触敏表面。与设备200和400的情况一样，在一些实施方案中，触摸屏604(或触敏表面)具有一个或多个强度传感器，以用于检测正在施加的接触(例如，触摸)的强度。触摸屏604(或触敏表面)的一个或多个强度传感器提供表示触摸的强度的输出数据。设备600的用户界面基于触摸强度来对触摸作出响应，这意味着不同强度的触摸可调用设备600上的不同的用户界面操作。
用于检测和处理触摸强度的技术可例如在相关申请中找到：2013年5月8日提交的名称为“Device,Method,and Graphical User Interface for Displaying UserInterface Objects Corresponding to an Application”(用于显示对应于应用的用户界面对象的设备、方法和图形用户界面)的国际专利申请No.PCT/US2013/040061，以及2013年11月11日提交的名称为“Device,Method,and Graphical User Interface forTransitioning Between Touch Input to Display Output Relationships”(用于触摸输入到显示输出之间关系转换的设备、方法和图形用户界面)的国际专利申请No.PCT/US2013/069483，这两个专利申请中的每个专利申请据此全文以引用方式并入本文。
在一些实施方案中，设备600具有一个或多个输入机构606和608。输入机构606和608(如果包括的话)是物理形式的。物理输入机构的示例包括下压按钮和可旋转机构。在一些实施方案中，设备600具有一个或多个附接机构。此类附接机构(如果包括的话)可允许设备600与下述各项附接：例如帽子、眼镜、耳环、项链、衬衣、夹克、手镯、表带、手链、裤子、皮带、鞋子、钱包、背包等。这些附接机构允许用户穿戴设备600。
图6B示出了示例性个人电子设备600。在一些实施方案中，设备600包括相对于图2A、图2B和图4所述的部件中的一些或全部部件。设备600具有总线612，该总线将I/O部分614与一个或多个计算机处理器616和存储器618操作性地耦接。I/O部分614被连接到显示器604，该显示器可具有触敏部件622并且任选地还具有触摸强度敏感部件624。此外，I/O部分614与通信单元630连接，以用于使用Wi-Fi、蓝牙、近场通信(NFC)、蜂窝和/或其他无线通信技术来接收应用程序和操作系统数据。设备600包括输入机构606和/或608。例如，输入机构606是可旋转输入设备或者可按压输入设备以及可旋转输入设备。在一些示例中，输入机构608是按钮。
在一些示例中，输入机构608是麦克风。个人电子设备600包括例如各种传感器，诸如GPS传感器632、加速度计634、定向传感器640(例如，罗盘)、陀螺仪636、运动传感器638和/或其组合，所有这些设备均可操作性连接到I/O部分614。
个人电子设备600的存储器618是非暂态计算机可读存储介质，以用于存储计算机可执行指令，该指令当由一个或多个计算机处理器616执行时例如使得计算机处理器执行上述技术和过程。该计算机可执行指令也例如在任何非暂态计算机可读存储介质内进行存储和/或传送，以供指令执行系统、装置或设备诸如基于计算机的系统、包含处理器的系统或可从指令执行系统、装置或设备获取指令并执行指令的其他系统使用或与其结合。个人电子设备600不限于图6B的部件和配置，而是可包括多种配置中的其他部件或附加部件。
如本文所用，术语“示能表示”是指例如在设备200、400和/或600(图2A、图4和图6A-图6B)的显示屏上显示的用户交互式图形用户界面对象。例如，图像(例如，图标)、按钮和文本(例如，超链接)各自构成示能表示。
如本文所用，术语“焦点选择器”是指用于指示用户正与之进行交互的用户界面的当前部分的输入元件。在包括光标或其他位置标记的一些具体实施中，光标充当“焦点选择器”，使得当光标在特定用户界面元素(例如，按钮、窗口、滑块或其他用户界面元素)上方时在触敏表面(例如，图4中的触摸板455或图5B中的触敏表面551)上检测到输入(例如，按压输入)的情况下，该特定用户界面元素根据所检测到的输入而被调节。在包括能够实现与触摸屏显示器上的用户界面元素的直接交互的触摸屏显示器(例如，图2A中的触敏显示器系统212或图5A中的触摸屏212)的一些具体实施中，在触摸屏上所检测到的接触充当“焦点选择器”，以使得当在触摸屏显示器上在特定用户界面元素(例如，按钮、窗口、滑块或其他用户界面元素)的位置处检测到输入(例如，由接触进行的按压输入)时，该特定用户界面元素根据所检测到的输入而被调节。在一些具体实施中，焦点从用户界面的一个区域移动到用户界面的另一个区域，而无需光标的对应移动或触摸屏显示器上的接触的移动(例如，通过使用制表键或箭头键将焦点从一个按钮移动到另一个按钮)；在这些具体实施中，焦点选择器根据焦点在用户界面的不同区域之间的移动而移动。不考虑焦点选择器所采取的具体形式，焦点选择器通常是由用户控制的以便递送与用户界面的用户预期的交互(例如，通过向设备指示用户界面的用户期望与其进行交互的元素)的用户界面元素(或触摸屏显示器上的接触)。例如，在触敏表面(例如，触摸板或触摸屏)上检测到按压输入时，焦点选择器(例如，光标、接触或选择框)在相应按钮上方的位置将指示用户期望启用相应按钮(而不是设备显示器上示出的其他用户界面元素)。
如说明书和权利要求中所使用的，接触的“特征强度”这一术语是指基于接触的一个或多个强度的接触的特征。在一些实施方案中，特征强度基于多个强度样本。特征强度任选地基于相对于预定义事件(例如，在检测到接触之后，在检测到接触抬离之前，在检测到接触开始移动之前或之后，在检测到接触结束之前，在检测到接触的强度增大之前或之后和/或在检测到接触的强度减小之前或之后)而言在预先确定的时间段(例如，0.05秒、0.1秒、0.2秒、0.5秒、1秒、2秒、5秒、10秒)期间采集的预定义数量的强度样本或一组强度样本。接触的特征强度任选地基于以下各项中的一者或多者：接触强度的最大值、接触强度的均值、接触强度的平均值、接触强度的前10％处的值、接触强度的半最大值、接触强度的90％最大值等。在一些实施方案中，在确定特征强度时使用接触的持续时间(例如，在特征强度是接触的强度在时间上的平均值时)。在一些实施方案中，将特征强度与一组一个或多个强度阈值进行比较，以确定用户是否已执行操作。例如，该组一个或多个强度阈值包括第一强度阈值和第二强度阈值。在该示例中，特征强度未超过第一阈值的接触导致第一操作，特征强度超过第一强度阈值但未超过第二强度阈值的接触导致第二操作，而特征强度超过第二阈值的接触导致第三操作。在一些实施方案中，使用特征强度与一个或多个阈值之间的比较来确定是否要执行一个或多个操作(例如，是执行相应操作还是放弃执行相应操作)，而不是用于确定执行第一操作还是第二操作。
在一些实施方案中，识别手势的一部分以用于确定特征强度。例如，触敏表面接收连续的轻扫接触，该连续的轻扫接触从起始位置过渡并到达结束位置，在该结束位置处，接触的强度增加。在该示例中，接触在结束位置处的特征强度仅基于连续轻扫接触的一部分，而不是整个轻扫接触(例如，仅轻扫接触在结束位置处的部分)。在一些实施方案中，在确定接触的特征强度之前向轻扫手势的强度应用平滑化算法。例如，平滑化算法任选地包括以下各项中的一种或多种：不加权滑动平均平滑化算法、三角平滑化算法、中值滤波器平滑化算法和/或指数平滑化算法。在一些情况下，这些平滑化算法消除了轻扫接触的强度中的窄的尖峰或凹陷，以实现确定特征强度的目的。
相对于一个或多个强度阈值诸如接触检测强度阈值、轻按压强度阈值、深按压强度阈值和/或一个或多个其他强度阈值来表征触敏表面上的接触的强度。在一些实施方案中，轻按压强度阈值对应于这样的强度：在该强度下设备将执行通常与点击物理鼠标或触摸板的按钮相关联的操作。在一些实施方案中，深按压强度阈值对应于这样的强度：在该强度下设备将执行与通常与点击物理鼠标或触控板的按钮相关联的操作不同的操作。在一些实施方案中，当检测到特征强度低于轻按压强度阈值(例如，并且高于标称接触检测强度阈值，比标称接触检测强度阈值低的接触不再被检测到)的接触时，设备将根据接触在触敏表面上的移动来移动焦点选择器，而不执行与轻按压强度阈值或深按压强度阈值相关联的操作。一般来讲，除非另有陈述，否则这些强度阈值在不同组的用户界面附图之间是一致的。
接触特征强度从低于轻按压强度阈值的强度增大到介于轻按压强度阈值与深按压强度阈值之间的强度有时被称为“轻按压”输入。接触特征强度从低于深按压强度阈值的强度增大到高于深按压强度阈值的强度有时被称为“深按压”输入。接触特征强度从低于接触检测强度阈值的强度增大到介于接触检测强度阈值与轻按压强度阈值之间的强度有时被称为检测到触摸表面上的接触。接触特征强度从高于接触检测强度阈值的强度减小到低于接触检测强度阈值的强度有时被称为检测到接触从触摸表面抬离。在一些实施方案中，接触检测强度阈值为零。在一些实施方案中，接触检测强度阈值大于零。
在本文中所述的一些实施方案中，响应于检测到包括相应按压输入的手势或响应于检测到利用相应接触(或多个接触)执行的相应按压输入来执行一个或多个操作，其中至少部分地基于检测到该接触(或多个接触)的强度增大到高于按压输入强度阈值而检测到相应按压输入。在一些实施方案中，响应于检测到相应接触的强度增大到高于按压输入强度阈值(例如，相应按压输入的“向下冲程”)来执行相应操作。在一些实施方案中，按压输入包括相应接触的强度增大到高于按压输入强度阈值以及该接触的强度随后减小到低于按压输入强度阈值，并且响应于检测到相应接触的强度随后减小到低于按压输入阈值(例如，相应按压输入的“向上冲程”)来执行相应操作。
在一些实施方案中，设备采用强度滞后以避免有时被称为“抖动”的意外输入，其中设备限定或选择与按压输入强度阈值具有预定义关系的滞后强度阈值(例如，滞后强度阈值比按压输入强度阈值低X个强度单位，或者滞后强度阈值是按压输入强度阈值的75％、90％或某个合理比例)。因此，在一些实施方案中，按压输入包括相应接触的强度增大到高于按压输入强度阈值以及该接触的强度随后减小到低于对应于按压输入强度阈值的滞后强度阈值，并且响应于检测到相应接触的强度随后减小到低于滞后强度阈值(例如，相应按压输入的“向上冲程”)来执行相应操作。类似地，在一些实施方案中，仅在设备检测到接触强度从等于或低于滞后强度阈值的强度增大到等于或高于按压输入强度阈值的强度并且任选地接触强度随后减小到等于或低于滞后强度的强度时才检测到按压输入，并且响应于检测到按压输入(例如，根据环境，接触强度增大或接触强度减小)来执行相应操作。
为了容易解释，任选地，响应于检测到以下各种情况中的任一种情况而触发对响应于与按压输入强度阈值相关联的按压输入或响应于包括按压输入的手势而执行的操作的描述：接触强度增大到高于按压输入强度阈值、接触强度从低于滞后强度阈值的强度增大到高于按压输入强度阈值的强度、接触强度减小到低于按压输入强度阈值以及/或者接触强度减小到低于与按压输入强度阈值对应的滞后强度阈值。另外，在将操作描述为响应于检测到接触的强度减小到低于按压输入强度阈值而执行的示例中，任选地响应于检测到接触的强度减小到低于对应于并且小于按压输入强度阈值的滞后强度阈值来执行操作。
3.数字助理系统
图7A示出根据各种示例的数字助理系统700的框图。在一些示例中，数字助理系统700在独立式计算机系统上实现。在一些示例中，数字助理系统700跨多个计算机分布。在一些示例中，数字助理的模块和功能中的一些被划分成服务器部分和客户端部分，其中客户端部分位于一个或多个用户设备(例如，设备104、设备122、设备200、设备400或设备600)上并通过一个或多个网络与服务器部分(例如，服务器系统108)通信，例如，如图1中所示。在一些示例中，数字助理系统700是图1中所示的服务器系统108(和/或DA服务器106)的具体实施。应当指出，数字助理系统700仅为数字助理系统的一个示例，且该数字助理系统700具有比所示更多或更少的部件、组合两个或更多个部件，或者可具有部件的不同配置或布局。图7A中所示的各种部件在硬件、用于由一个或多个处理器执行的软件指令、固件(包括一个或多个信号处理集成电路和/或专用集成电路)或其组合中实现。
数字助理系统700包括存储器702、输入/输出(I/O)接口706、网络通信接口708和一个或多个处理器704。这些部件可通过一条或多条通信总线或信号线710彼此通信。
在一些示例中，存储器702包括非暂态计算机可读介质，诸如高速随机存取存储器和/或非易失性计算机可读存储介质(例如，一个或多个磁盘存储设备、闪存存储器设备或其他非易失性固态存储器设备)。
在一些示例中，I/O接口706将数字助理系统700的输入/输出设备716诸如显示器、键盘、触摸屏和麦克风耦接至用户界面模块722。I/O接口706，与用户界面模块722结合，接收用户输入(例如，语音输入、键盘输入、触摸输入等)并相应地对这些输入进行处理。在一些示例中，例如，当数字助理在独立式用户设备上实现时，数字助理系统700包括相对于图2A、图4、图6A至图6B中的设备200、设备400或设备600分别描述的部件和I/O通信接口中的任一者。在一些示例中，数字助理系统700代表数字助理具体实施的服务器部分，并且可通过位于用户设备(例如，设备104、设备200、设备400或设备600)上的客户端侧部分与用户进行交互。
在一些示例中，网络通信接口708包括一个或多个有线通信端口712和/或无线传输和接收电路714。一个或多个有线通信端口经由一个或多个有线接口例如以太网、通用串行总线(USB)、火线等接收和发送通信信号。无线电路714从通信网络及其他通信设备接收RF信号和/或光学信号以及将RF信号和/或光学信号发送至通信网络及其他通信设备。无线通信使用多种通信标准、协议和技术中的任一种，诸如GSM、EDGE、CDMA、TDMA、蓝牙、Wi-Fi、VoIP、Wi-MAX或任何其他合适的通信协议。网络通信接口708使数字助理系统700通过网络(诸如互联网、内联网和/或无线网络诸如蜂窝电话网络、无线局域网(LAN)和/或城域网(MAN))与其他设备之间的通信成为可能。
在一些示例中，存储器702或存储器702的计算机可读存储介质存储程序、模块、指令和数据结构，包括以下内容中的全部或其子集：操作系统718、通信模块720、用户界面模块722、一个或多个应用程序724和数字助理模块726。具体地讲，存储器702或存储器702的计算机可读存储介质存储用于执行上述过程的指令。一个或多个处理器704执行这些程序、模块和指令，并从数据结构读取数据或将数据写到数据结构。
操作系统718(例如，Darwin、RTXC、LINUX、UNIX、iOS、OS X、WINDOWS、或嵌入式操作系统诸如VxWorks)包括各种软件组件和/或驱动器，以用于控制和管理一般系统任务(例如，存储器管理、存储设备控制、电源管理等)，并且有利于各种硬件、固件和软件组件之间的通信。
通信模块720促成数字助理系统700与其他设备之间通过网络通信接口708进行的通信。例如，通信模块720与电子设备诸如分别在图2A、图4、图6A至图6B中所示的设备200、400和600的RF电路208通信。通信模块720还包括各种部件，用于处理由无线电路714和/或有线通信端口712所接收的数据。
用户界面模块722经由I/O接口706接收来自用户(例如，来自键盘、触摸屏、指向设备、控制器和/或麦克风)的命令和/或输入，并在显示器上生成用户界面对象。用户界面模块722还准备输出(例如，语音、声音、动画、文本、图标、振动、触觉反馈、光照等)并将其经由I/O接口706(例如，通过显示器、音频通道、扬声器、触控板等)传送给用户。
应用程序724包括程序和/或模块，其被配置为由一个或多个处理器704执行。例如，如果数字助理系统在独立式用户设备上实施，则应用程序724包括用户应用程序，诸如游戏、日历应用程序、导航应用程序或邮件应用程序。如果数字助理系统700在服务器上实现，则应用程序724包括例如资源管理应用程序、诊断应用程序或调度应用程序。
存储器702还存储数字助理模块726(或数字助理的服务器部分)。在一些示例中，数字助理模块726包括以下子模块或者其子集或超集：输入/输出处理模块728、语音转文本(STT)处理模块730、自然语言处理模块732、对话流处理模块734、任务流处理模块736、服务处理模块738和语音合成模块740。这些模块中的每一者均具有对以下数字助理模块726的系统或数据与模型中的一者或多者或者其子集或超集的访问权限：知识本体760、词汇索引744、用户数据748、任务流模型754、服务模型756和ASR系统758。
在一些示例中，使用在数字助理模块726中实现的处理模块、数据和模型，数字助理可执行下述各项中的至少一些：将语音输入转换成文本；识别在从用户接收的自然语言输入中表达的用户意图；主动引出并获得完全推断用户意图所需的信息(例如，通过消除字词、姓名、意图的歧义等)；确定用于满足推断出的意图的任务流；以及执行该任务流以满足推断出的意图。
在一些示例中，如图7B中所示，I/O处理模块728可通过图7A中的I/O设备716与用户交互或通过图7A中的网络通信接口708与用户设备(例如，设备104、设备200、设备400或设备600)交互，以获取用户输入(例如，语音输入)并提供对用户输入的响应(例如，作为语音输出)。I/O处理模块728随同接收到用户输入一起或在接收到用户输入之后不久任选地获得与来自用户设备的用户输入相关联的上下文信息。上下文信息包括特定于用户的数据、词汇和/或与用户输入相关的偏好。在一些示例中，该上下文信息还包括在接收到用户请求时的用户设备的软件状态和硬件状态和/或在接收到用户请求时与用户的周围环境相关的信息。在一些示例中，I/O处理模块728还向用户发送与用户请求有关的跟进问题并从用户接收回答。在用户请求被I/O处理模块728接收且用户请求包括语音输入时，I/O处理模块728将语音输入转发至STT处理模块730(或语音识别器)以用于语音文本转换。
STT处理模块730包括一个或多个ASR系统758。该一个或多个ASR系统758可处理通过I/O处理模块728接收到的言语输入，以产生识别结果。每个ASR系统758可包括前端言语预处理器。前端语音预处理器从语音输入中提取代表性特征。例如，前端语音预处理器对语音输入执行傅里叶变换，以提取表征语音输入的光谱特征作为代表性多维向量的序列。另外，每个ASR系统758包括一个或多个言语识别模型(例如，声学模型和/或语言模型)并且实现一个或多个言语识别引擎。语音识别模型的示例包括隐马尔可夫模型、高斯混合模型、深层神经网络模型、n元语言模型和其他统计模型。语音识别引擎的示例包括基于动态时间规整的引擎和基于加权有限状态变换器(WFST)的引擎。使用一个或多个语音识别模型和一个或多个语音识别引擎来处理前端语音预处理器的所提取的代表性特征，以产生中间识别结果(例如，音素、音素串和子字词)，并且最终产生文本识别结果(例如，字词、字词串或符号序列)。在一些示例中，语音输入至少部分地由第三方服务处理或在用户的设备(例如，设备104、设备200、设备400或设备600)上处理，以产生识别结果。一旦STT处理模块730产生包含文本串(例如，字词、或字词的序列或符号序列)的识别结果，识别结果就被传送至自然语言处理模块732以供意图推断。在一些示例中，STT处理模块730产生言语输入的多个候选文本表示。每个候选文本表示是与语音输入对应的字词或符号的序列。在一些示例中，每个候选文本表示与言语识别置信度得分相关联。基于语音识别置信度得分，STT处理模块730对候选文本表示进行排序并将n个最佳(例如，n个排名最高)候选文本表示提供给自然语言处理模块732以供意图推断，其中n为大于零的预先确定的整数。例如，在一个示例中，仅将排名最高的(n＝1)候选文本表示递送至自然语言处理模块732以供意图推断。又如，将5个排名最高的(n＝5)候选文本表示传递给自然语言处理模块732以供意图推断。
有关语音转文本处理的更多细节在提交于2011年9月20日的名为“ConsolidatingSpeech Recognition Results”的美国实用新型专利申请序列号13/236,942中有所描述，其全部公开内容以引用方式并入本文。
在一些示例中，STT处理模块730包括可识别字词的词汇和/或经由语音字母转换模块731访问该词汇。每个词汇字词与语音识别语音字母表中表示的字词的一个或多个候选发音相关联。具体地讲，可识别字词的词汇包括与多个候选发音相关联的字词。例如，该词汇包括与
和/>
的候选发音相关联的字词“tomato”。另外，词汇字词与基于来自用户的先前语音输入的自定义候选发音相关联。此类自定义候选发音存储在STT处理模块730中，并且经由设备上的用户配置文件与特定用户相关联。在一些示例中，字词的候选发音基于字词的拼写以及一个或多个语言学和/或语音学规则确定。在一些示例中，候选发音手动生成，例如，基于已知的标准发音而手动生成。
在一些示例中，基于候选发音的普遍性来对候选发音进行排名。例如，候选语音
的排序高于/>
因为前者是更常用的发音(例如，在所有用户中，对于特定地理区域的用户而言或对于任何其他合适的用户子集而言)。在一些示例中，基于候选发音是否为与用户相关联的自定义候选发音来对候选发音进行排序。例如，自定义候选发音的排名高于标准候选发音。这可用于识别具有偏离规范发音的独特发音的专有名词。在一些示例中，候选发音与一个或多个语音特征(诸如地理起源、国家或种族)相关联。例如，候选发音/>
与美国相关联，而候选发音/>
与英国相关联。此外，候选发音的排序基于存储在设备上的用户配置文件中的用户的一个或多个特征(例如，地理起源、国家、种族等)。例如，可从用户配置文件确定该用户与美国相关联。基于用户与美国相关联，候选发音/>
(与美国相关联)可比候选发音/>
(与英国相关联)排名更高。在一些示例中，经排序的候选发音中的一个可被选作预测发音(例如，最可能的发音)。
接收到语音输入时，STT处理模块730被用来(例如，使用声音模型)确定对应于该语音输入的音素，然后尝试(例如，使用语言模型)确定匹配该音素的字词。例如，如果STT处理模块730首先识别对应于该语音输入的一部分的音素序列
那么它随后可基于词汇索引744确定该序列对应于字词“tomato”。
在一些示例中，STT处理模块730使用模糊匹配技术来确定话语中的字词。因此，例如，STT处理模块730确定音素序列
对应于字词“tomato”，即使该特定音素序列不是该字词的候选音素序列。
数字助理的自然语言处理模块732(“自然语言处理器”)获取由STT处理模块730生成的n个最佳候选文字表示(“字词序列”或“符号序列”)，并尝试将每个候选文本表示与由数字助理所识别的一个或多个“可执行意图”相关联。在一些实施方案中，如下文更详细描述的，STT处理模块730尝试使用误触发缓解器(FTM)将每个候选文本表示与一个或多个“候选意图”相关联。FTM向候选意图评估器(CIE)提供候选意图，该候选意图评估器评估候选意图是否包括一个或多个“可执行意图”。“可执行意图”(或“用户意图”)表示可由数字助理执行并且可具有在任务流模型754中实现的相关联的任务流的任务。相关联任务流是数字助理为了执行任务而采取的一系列经编程的动作和步骤。数字助理的能力范围取决于已在任务流模型754中实现并存储的任务流的数量和种类，或换言之，取决于数字助理所识别的“可执行意图”的数量和种类。然而，数字助理的有效性还取决于助理从以自然语言表达的用户请求中推断出正确的“一个或多个可执行意图”的能力。
在一些示例中，除从STT处理模块730获取的字词或符号的序列之外，自然语言处理模块732还(例如，从I/O处理模块728)接收与用户请求相关联的上下文信息。自然语言处理模块732任选地使用上下文信息来明确、补充和/或进一步限定在从STT处理模块730接收的候选文本表示中包含的信息。上下文信息包括例如用户偏好，用户设备的硬件和/或软件状态，在用户请求之前、期间或之后不久收集的传感器信息，数字助理与用户之间的先前交互(例如，对话)，等等。如本文所述，在一些示例中，上下文信息是动态的，并且随对话的时间、位置、内容和其他因素而变化。
在一些示例中，自然语言处理基于例如知识本体760。知识本体760为包含许多节点的分级结构，每个节点表示“可执行意图”或与“可执行意图”或其他“属性”中的一者或多者相关的“属性”。如上所述，“可执行意图”表示数字助理能够执行的任务，即，该任务为“可执行的”或可被进行的。“属性”代表与可执行意图或另一属性的子方面相关联的参数。知识本体760中可执行意图节点与属性节点之间的连接定义由属性节点表示的参数如何从属于由可执行意图节点表示的任务。
在一些示例中，知识本体760由可执行意图节点和属性节点组成。在知识本体760内，每个可执行意图节点直接连接至或通过一个或多个中间属性节点连接至一个或多个属性节点。类似地，每个属性节点直接地或通过一个或多个中间属性节点连接至一个或多个可执行意图节点。例如，如图7C所示，知识本体760包括“餐厅预订”节点(即，可执行意图节点)。属性节点“餐厅”、“日期/时间”(针对预订)和“派对人数”均直接连接至可执行意图节点(即，“餐厅预订”节点)。
此外，属性节点“菜系”、“价格区间”、“电话号码”和“位置”是属性节点“餐厅”的子节点，并且均通过中间属性节点“餐厅”连接至“餐厅预订”节点(即，可执行意图节点)。又如，如图7C所示，知识本体760还包括“设定提醒”节点(即，另一个可执行意图节点)。属性节点“日期/时间”(针对设定提醒)和“主题”(针对提醒)均连接至“设定提醒”节点。由于属性“日期/时间”与进行餐厅预订的任务和设定提醒的任务二者相关，因此属性节点“日期/时间”连接至知识本体760中的“餐厅预订”节点和“设定提醒”节点二者。
可执行意图节点连同其连接的概念节点一起被描述为“域”。在本讨论中，每个域与相应的可执行意图相关联，并涉及与特定可执行意图相关联的一组节点(以及这些节点之间的关系)。例如，图7C中示出的知识本体760包括在知识本体760内的餐厅预订域762的示例以及提醒域764的示例。餐厅预订域包括可执行意图节点“餐厅预订”、属性节点“餐厅”、“日期/时间”和“派对人数”以及子属性节点“菜系”、“价格范围”、“电话号码”和“位置”。提醒域764包括可执行意图节点“设定提醒”和属性节点“主题”和“日期/时间”。在一些示例中，知识本体760由多个域组成。每个域与一个或多个其他域共享一个或多个属性节点。例如，除了餐厅预订域762和提醒域764之外，“日期/时间”属性节点还与许多不同域(例如，行程安排域、旅行预订域、电影票域等)相关联。
尽管图7C示出知识本体760内的两个示例性域，但其他域包括例如“查找电影”、“发起电话呼叫”、“查找方向”、“安排会议”、“发送消息”以及“提供问题的回答”、“阅读列表”、“提供导航指令”、“提供针对任务的指令”等。“发送消息”域与“发送消息”可执行意图节点相关联，并且还包括属性节点诸如“一个或多个接收人”、“消息类型”和“消息正文”。属性节点“接收人”进一步例如由子属性节点诸如“接收人姓名”和“消息地址”来限定。
在一些示例中，知识本体760包括数字助理能够理解并对其起作用的所有域(以及因而可执行意图)。在一些示例中，知识本体760诸如通过添加或移除整个域或节点或通过修改知识本体760内的节点之间的关系进行修改。
在一些示例中，将与多个相关可执行意图相关联的节点群集在知识本体760中的“超级域”下。例如，“旅行”超级域包括与旅行相关的属性节点和可执行意图节点的群集。与旅行相关的可执行意图节点包括“机票预订”、“酒店预订”、“汽车租赁”、“获取路线”、“寻找兴趣点”，等等。同一超级域(例如，“旅行”超级域)下的可执行意图节点具有多个共用的属性节点。例如，针对“机票预订”、“酒店预订”、“汽车租赁”、“路线规划”和“寻找感兴趣的点”的可执行意图节点共享属性节点“起始位置”、“目的地”、“出发日期/时间”、“到达日期/时间”和“派对人数”中的一者或多者。
在一些示例中，知识本体760中的每个节点与跟由节点代表的属性或可执行意图有关的一组字词和/或短语相关联。与每个节点相关联的相应组的字词和/或短语是所谓的与节点相关联的“词汇”。将与每个节点相关联的相应组的字词和/或短语存储在与由节点所代表的属性或可执行意图相关联的词汇索引744中。例如，返回图7B，与“餐厅”属性的节点相关联的词汇包括字词诸如“美食”、“酒水”、“菜系”、“饥饿”、“吃”、“披萨”、“快餐”、“膳食”等。又如，与“发起电话呼叫”可执行意图的节点相关联的词汇包括字词和短语诸如“呼叫”、“打电话”、“拨打”、“与……通电话”、“呼叫该号码”、“打电话给”等。词汇索引744任选地包括不同语言的字词和短语。
自然语言处理模块732接收来自STT处理模块730的候选文本表示(例如，一个或多个文本字符串或一个或多个符号序列)，并针对每个候选表示，确定候选文本表示中的字词涉及哪些节点。在一些示例中，如果发现候选文本表示中的字词或短语(经由词汇索引744)与知识本体760中的一个或多个节点相关联，则所述字词或短语“触发”或“启用”这些节点。基于已启用节点的数量和/或相对重要性，自然语言处理模块732选择可执行意图之一作为用户意图使数字助理执行的任务。在一些示例中，选择具有最多“已触发”节点的域。在一些示例中，选择具有最高置信度(例如，基于其各个已触发节点的相对重要性)的域。在一些示例中，基于已触发节点的数量和重要性的组合来选择域。在一些示例中，在选择节点的过程中还考虑附加因素，诸如数字助理先前是否已正确解译来自用户的类似请求。
用户数据748包括特定于用户的信息，诸如特定于用户的词汇、用户偏好、用户地址、用户的默认语言和第二语言、用户的联系人列表和每位用户的其他短期或长期信息。在一些示例中，自然语言处理模块732使用特定于用户的信息来补充用户输入中所包含的信息以进一步限定用户意图。例如，针对用户请求“邀请我的朋友参加我的生日派对”，自然语言处理模块732能够访问用户数据748以确定“朋友”是哪些人以及“生日派对”应当于何时何地举行，而不需要用户在其请求中明确地提供此类信息。
应当认识到，在一些示例中，利用一个或多个机器学习机构(例如，神经网络)来实现自然语言处理模块732。具体地，一个或多个机器学习机构被配置为接收候选文本表示和与候选文本表示相关联的上下文信息。基于候选文本表示和相关联的上下文信息，一个或多个机器学习机构被配置为基于一组候选可执行意图确定意图置信度得分。自然语言处理模块732可基于所确定的意图置信度得分从一组候选可执行意图中选择一个或多个候选可执行意图。在一些示例中，还利用知识本体(例如，知识本体760)从一组候选可执行意图中选择一个或多个候选可执行意图。
基于符号串搜索知识本体的其他细节在提交于2008年12月22日的名为“Methodand Apparatus for Searching Using An Active Ontology”的美国实用新型专利申请序列号12/341,743中有所描述，其全部公开内容以引用方式并入本文。
在一些示例中，一旦自然语言处理模块732基于用户请求识别出可执行意图(或域)，自然语言处理模块732便生成结构化查询以表示所识别的可执行意图。在一些示例中，结构化查询包括针对可执行意图的域内的一个或多个节点的参数，并且所述参数中的至少一些参数填充有用户请求中指定的特定信息和要求。例如，用户说“帮我在寿司店预订晚上7点的座位。”在这种情况下，自然语言处理模块732能够基于用户输入将可执行意图正确地识别为“餐厅预订”。根据知识本体，“餐厅预订”域的结构化查询包括参数诸如{菜系}、{时间}、{日期}、{派对人数}等。在一些示例中，基于语音输入和使用STT处理模块730从语音输入得出的文本，自然语言处理模块732针对餐厅预订域生成部分结构化查询，其中部分结构化查询包括参数{菜系＝“寿司类”}以及{时间＝“晚上7点”}。然而，在该示例中，用户话语包含不足以完成与域相关联的结构化查询的信息。因此，基于当前可用信息，在结构化查询中未指定其他必要参数，诸如{同行人数}和{日期}。在一些示例中，自然语言处理模块732用所接收的上下文信息来填充结构化查询的一些参数。例如，在一些示例中，如果请求“附近的”寿司店，自然语言处理模块732用来自用户设备的GPS坐标来填充结构化查询中的{位置}参数。
在一些示例中，自然语言处理模块732识别针对从STT处理模块730所接收的每个候选文本表示的多个候选可执行意图。另外，在一些示例中，针对每个所识别的候选可执行意图生成相应的结构化查询(部分地或全部地)。自然语言处理模块732确定针对每个候选可执行意图的意图置信度得分，并基于意图置信度得分对候选可执行意图进行排序。在一些示例中，自然语言处理模块732将所生成的一个或多个结构化查询(包括任何已完成的参数)传送至任务流处理模块736(“任务流处理器”)。在一些示例中，针对m个最佳(例如，m个排名最高的)候选可执行意图的一个或多个结构化查询被提供给任务流处理模块736，其中m为预先确定的大于零的整数。在一些示例中，将针对m个最佳候选可执行意图的一个或多个结构化查询连同对应的候选文本表示提供给任务流处理模块736。
基于根据语音输入的多个候选文本表示所确定的多个候选可执行意图推断用户意图的其他细节在2014年6月6日提交的名称为“System and Method for Inferring UserIntent From Speech Inputs”(用于从语音输入推断用户意图的系统和方法)的美国实用新型专利申请No.14/298,725中有所描述，其全部公开内容以引用方式并入本文。
任务流处理模块736被配置为接收来自自然语言处理模块732的一个或多个结构化查询，(必要时)完成结构化查询，以及执行“完成”用户最终请求所需的动作。在一些示例中，完成这些任务所必需的各种过程在任务流模型754中提供。在一些示例中，任务流模型754包括：过程，以用于获取来自用户的附加信息；和任务流，以用于执行与可执行意图相关联的动作。
如上所述，为了完成结构化查询，任务流处理模块736需要发起与用户的附加对话，以便获取附加信息和/或弄清可能有歧义的话语。当有必要进行此类交互时，任务流处理模块736调用对话流处理模块734来参与同用户的对话。在一些示例中，对话流处理器模块734确定如何(和/或何时)向用户请求附加信息，并且接收和处理用户响应。通过I/O处理模块728将问题提供给用户并从用户接收回答。在一些示例中，对话处理模块734经由音频和/或视频输出向用户呈现对话输出，并接收经由口头或物理(例如，点击)响应的来自用户的输入。继续上述示例，在任务流处理模块736调用对话流处理模块734来确定针对与域“餐厅预订”相关联的结构化查询的“派对人数”和“日期”信息时，对话流处理模块734生成诸如“一行几位？”和“预订哪天？”之类的问题传递给用户。一旦收到来自用户的回答，对话流处理模块734就用缺失信息填充结构化查询或将信息传递给任务流处理模块736，以根据结构化查询完成缺失信息。
一旦任务流处理模块736已针对可执行意图完成结构化查询，任务流处理模块736就开始执行与可执行意图相关联的最终任务。因此，任务流处理模块736根据结构化查询中包含的特定参数来执行任务流模型中的步骤和指令。例如，针对可执行意图“餐厅预订”的任务流模型包括步骤和指令，以用于联系餐厅并实际上请求在特定时间针对特定派对人数的预订。例如，使用结构化查询诸如：餐厅预订、{餐厅＝ABC咖啡馆、日期＝3/12/2012、时间＝7pm、派对人数＝5}，任务流处理模块736可执行以下步骤：(1)登录ABC咖啡馆的服务器或诸如
的餐厅预订系统；(2)以网站上的形式输入日期、时间和派对人数信息；(3)提交表单；以及(4)在用户的日历中形成针对预订的日历条目。
在一些示例中，任务流处理模块736在服务处理模块738(“服务处理模块”)的辅助下完成用户输入中所请求的任务或者提供用户输入中所请求的信息性回答。例如，服务处理模块738代表任务流处理模块736发起电话呼叫、设定日历条目、调用地图搜索、调用用户设备上安装的其他用户应用程序或与所述其他应用程序进行交互以及调用第三方服务(例如，餐厅预订门户网站、社交网站、银行门户网站等)或与第三方服务进行交互。在一些示例中，通过服务模型756中的相应服务模型指定每项服务所需的协议和应用程序编程接口(API)。服务处理模块738针对服务访问适当的服务模型，并依据服务模型根据该服务所需的协议和API生成针对该服务的请求。
例如，如果餐厅已启用在线预订服务，则餐厅提交服务模型，该服务模型指定进行预订的必要参数以及将必要参数的值传送至在线预订服务的API。在被任务流处理模块736请求时，服务处理模块738可使用存储在服务模型中的web地址来建立与在线预订服务的网络连接，并根据在线预订服务的API的格式将预订的必要参数(例如，时间、日期、同行人数)发送至在线预订接口。
在一些示例中，自然语言处理模块732、对话处理模块734和任务流处理模块736被共同且反复地使用，以推断并限定用户的意图、获取信息以进一步明确并细化用户意图、并最终生成响应(即，输出至用户或完成任务)，以满足用户的意图。所生成的响应是至少部分地满足用户意图的对语音输入的对话响应。另外，在一些示例中，所生成的响应被输出为语音输出。在这些示例中，所生成的响应被发送到语音合成模块740(例如，语音合成器)，在语音合成模块中，可处理所生成的响应以将对话响应以语音形式合成。在其他示例中，所生成的响应是与满足语音输入中的用户请求相关的数据内容。
在任务流处理模块736接收到来自自然语言处理模块732的多个结构化查询的示例中，任务流处理模块736首先处理所接收结构化查询的第一结构化查询以试图完成第一结构化查询并且/或者执行由第一结构化查询所表示的一个或多个任务或动作。在一些示例中，第一结构化查询对应于排名最高的可执行意图。在其他示例中，第一结构化查询选自基于对应的语音识别置信度得分和对应的意图置信度得分的结合所接收的结构化查询。在一些示例中，如果任务流处理模块736在第一结构化查询的处理期间(例如，由于无法确定必要的参数)遇到错误，则任务流处理模块736可继续选择和处理所接收结构化查询的与排名较低的可执行意图对应的第二结构化查询。例如，基于对应候选文本表示的语音识别置信度得分、对应候选可执行意图的意图置信度得分、第一结构化查询中的缺失必要参数或其任何组合来选择第二结构化查询。
语音合成模块740被配置为合成用于呈现给用户的语音输出。语音合成模块740基于数字助理提供的文本来合成语音输出。例如，所生成的对话响应是文本串的形式。语音合成模块740将文本串转换成可听语音输出。语音合成模块740使用任何适当语音合成技术，以便从文本生成语音输出，包括但不限于：拼接合成、单元选择合成、双音素合成、域特定合成、共振峰合成、发音合成、基于隐马尔可夫模型(HMM)的合成和正弦波合成。在一些示例中，语音合成模块740被配置为基于对应于这些字词的音素串来合成各个字词。例如，音素串与所生成的对话响应中的字词相关联。音素串存储在与字词相关联的元数据中。语音合成模型740被配置为直接处理元数据中的音素串，以合成语音形式的字词。
在一些示例中，替代使用语音合成模块740(或除此之外)，在远程设备(例如，服务器系统108)上执行语音合成，并且将合成的语音发送至用户设备以输出给用户。例如，这可发生在一些具体实施中，其中在服务器系统处生成数字助理的输出。而且由于服务器系统通常比用户设备具有更强的处理能力或更多的资源，有可能获得比客户端侧合成应当实现的质量更高的语音输出。
有关数字助理的另外细节可见于提交于2011年1月10日的名称为“IntelligentAutomated Assistant”的美国实用新型专利申请号12/987,982和提交于2011年9月30日的名称为“Generating and Processing Task Items That Represent Tasks to Perform”的美国实用新型专利申请号13/251,088中，其全部公开内容以引用方式并入本文。
4.虚拟助理的示例性架构和功能
图8示出了用于提供自然语言交互的虚拟助理800的框图。在一些示例中，数字助理800(例如，数字助理系统700)可由用户设备根据各种实施方案来实现。在一些实施方案中，用户设备、服务器(例如，服务器108)或其组合可实现虚拟助理800。用户设备可利用例如如图1、图2A至图2B、图4、图9、图11A至图11B、图12A至图12D、图13A至图13B和图14A至图14D所示的设备104、200、400、900、1120、1220、1320或1420来实现。在一些实施方案中，如图8所示，虚拟助理800包括以下子模块、其子集或超集：输入模块810、自然语言引擎820、误触发缓解器(FTM)840、候选意图评估器(CIE)860和任务执行模块880。在一些实施方案中，虚拟助理800可利用图7B中所示的数字助理系统700的数字助理模块726来实现。例如，虚拟助理800可以包括类似于数字助理模块726的一个或多个模块、模型、应用程序、词汇表和用户数据。参考图7B和图8，作为一个示例，输入模块810可以是例如输入/输出处理模块728的子模块或变型。自然语言引擎820可以包括例如下述各项中的一个或多个：STT处理模块730、语音字母表转换模块731、词汇744、用户数据748和/或自然语言处理模块760。虚拟助理800还可以包括模块、模型、应用程序、词汇和用户数据，其未包括在数字助理模块726中。例如，如图8所示的误触发缓解器840可能不包括在数字助理模块726中。
参考图8，在一些实施方案中，输入模块810接收一个或多个音频流802。音频流可包括一个或多个话语。在一些实施方案中，音频流中的话语可包括字词、包括多个字词的短语和/或一个或多个句子。作为图9所示的示例，音频流912可包括一个或多个用户话语，其作为句子(诸如“外面太黑了。把灯打开，Siri。”)。
再次参考图8，输入模块810可被启用或保持活动状态(例如，在预先配置的时间段内)以接收一个或多个音频流802。例如，输入模块810的语音活动检测器814可检测是否存在人类语音(例如，基于在语音活动检测器814处接收的输入信号的振幅和/或频谱)。在一些实施方案中，输入模块810可包括缓冲器812(例如，环形缓冲器)，其被配置为存储一个或多个接收的音频流(例如，存储10秒的音频流)。
在一些实施方案中，使用存储在缓冲器812中的接收的音频流，语音活动检测器814可确定音频流是否包括词汇触发。词汇触发可包括单个字词或多个字词。例如，词汇触发可以是“嘿，Siri”、“嘿，助理”、“Siri”、“助理”等。在一些实施方案中，在通过输入模块810(例如，语音活动检测器814)接收到词汇触发时，虚拟助理800(例如，NLE 820)的至少一部分被启用。在一些实施方案中，虚拟助理800(例如，输入模块810、NLE 820、FTM 840)的至少一部分可以保持活动状态或保持预先配置的时间段的活动状态。例如，输入模块810可保持30秒的活动状态以接收音频流802。在虚拟助理800的至少一部分保持至少每个配置的时间段的活动状态的实施方案中，词汇触发可能不使虚拟助理800的一部分被启用。相反，词汇触发可能指示音频流的至少一部分被指向虚拟助理。
使用图9所示的上述示例，话语“把灯打开，Siri”包括单个字词的词汇触发“Siri”，其指示话语指向在设备900上操作的虚拟助理。在一些实施方案中，词汇触发可定位在音频流中的话语的开始部分(例如，“Siri，股票价格是多少？”)。在一些实施方案中，词汇触发可定位在除话语的开始部分之外的任何部分处(例如，“把灯打开，Siri”)。允许将词汇触发定位在除话语的开始部分之外的任何部分处，能够在用户和虚拟助理之间实现更自然的人机交互，而不是要求用户利用词汇触发引导指向虚拟助理的每个话语。这增强用户体验、降低功耗并提高系统效率。
再次参考图8，如上所述，输入模块810接收一个或多个音频流802。虚拟助理800(例如，使用输入模块810的VAD 814)可以确定一个或多个音频流802的特定音频流的开始点/结束点和/或持续时间。基于这种确定，虚拟助理800可以确定词汇触发是否包括在特定音频流内。
作为一个示例，为了检测特定音频流的开始点，虚拟助理800经由麦克风(未在图8中示出)检测到在接收到特定音频流之前没有语音活动(例如，检测相邻话语之间的静音或暂停)。虚拟助理800还可确定在接收特定音频流之前没有语音活动的时间是否超过第一阈值时间段(例如，3秒)。如果没有语音活动的时间超过第一阈值时间段，则虚拟助理800确定特定音频流的开始点。例如，如果第一阈值时间段是3秒并且如果虚拟助理800确定在接收第一音频流之前存在5秒的静音，或者输入模块810在过去5秒内没有接收到任何音频输入，则虚拟助理800确定没有语音活动的时间超过第一阈值时间段。因此，可确定特定音频流的开始点。
在一些实施方案中，为了检测特定音频流的结束点，虚拟助理800可经由麦克风(未在图8中示出)检测到在接收到特定音频流的一个或多个话语之后没有语音活动(例如，检测相邻话语之间的静音或暂停)。虚拟助理800还可确定在接收特定音频流之后没有语音活动的时间是否超过第二阈值时间周期(例如，3秒)。如果没有语音活动的时间超过第二阈值时间段，则虚拟助理800确定第一音频流的结束点。例如，如果第二阈值时间段是3秒并且如果虚拟助理800确定在接收特定音频流之后存在5秒的静音，或者输入模块810在接下来的5秒内没有接收到任何其他音频输入，则虚拟助理800可确定没有语音活动的时间超过第二阈值时间段。因此，可确定特定音频流的结束点。
作为图9所示的示例，特定音频流912可包括第一话语(例如，“外面太黑了。”)和第二话语(例如，“把灯打开，Siri。”)。在设备900上操作的虚拟助理(例如，虚拟助理800)可确定：在接收音频流912的第一话语之前，至少3秒没有接收到音频输入；以及在接收到第二话语音频流912之后，至少3秒没有接收到音频输入。虚拟助理还可确定在第一话语和第二话语之间，仅存在短时间的语音活动缺失(例如，0.5秒的短暂停顿)。因此，虚拟助理可确定音频流912的开始点/结束点和/或持续时间。
在一些实施方案中，参考图8，可基于输入模块810被配置为接收音频流的预先配置的持续时间来确定音频流的结束点。例如，如果音频流中的一个或多个用户话语指向虚拟助理(例如，为了获取信息或指示虚拟助理执行任务)，则用户话语通常不能持续超过30秒。因此，预先配置的持续时间可被设置为例如30秒。因此，在检测到特定音频流的开始点之后30秒内接收的任何用户话语可被确定为同一音频流的话语。因此，为了确定特定音频流的结束点，在一些实施例中，虚拟助理800(例如，使用输入模块810)可以检测音频流的开始点，获取音频流的预先配置的持续时间(例如，30秒)，并基于预先配置的持续时间和开始点确定音频流的结束点(例如，结束点是开始点后30秒)。
参考图8，在一些实施方案中，音频流的结束点可基于缓冲器812的容量来确定。缓冲器812可将接收的一个或多个音频流存储为音频文件。音频文件缓冲器812的存储容量取决于缓冲器812的容量(例如，在兆字节的范围内)。作为基于缓冲器812的容量确定音频流的结束点的示例，虚拟助理800(例如，使用输入模块810)可以确定音频文件的大小，音频文件表示包括一个或多个话语的接收音频流，并将音频文件的大小与缓冲器812的容量进行比较。在一些实施方案中，如果音频文件的大小达到缓冲器812的容量(例如，基本上等于缓冲器812的容量)，则虚拟助理800可确定包括在音频文件中的话语表示整个音频流。基于该确定结果，虚拟助理800可确定音频流的结束点。
在一些实施方案中，虚拟助理800还可估计在接收特定音频流之前或之后的音频流的特定缺失分别对应于特定音频流的开始点或结束点的可能性。如上所述，虚拟助理800可以在接收语音输入之前或之后检测语音活动的缺失。在一些示例中，虚拟助理800的自动语音识别系统(例如，图7A中所示的系统758)处理语音输入并产生识别结果。基于该识别结果(例如，语音输入的文本)和一个或多个语言模型(例如，如上所述由ASR系统758使用的模型)，虚拟助理800估计语音活动的特定缺失对应于特定音频流的开始点或结束点的可能性。在音频流912的上述示例中(例如，“外面太黑了。把灯打开，Siri。”)，基于ASR系统的识别结果和一个或多个语言模型，虚拟助理800可估计在接收音频流912之后语音活动的缺失(例如，3秒的静音)对应于音频流912的结束点的可能性。基于该估计的可能性，虚拟助理800可以增加或改善的置信度(例如，基于该估计的可能性与阈值的比较)来检测音频流912的结束点。
在检测到特定音频流的结束点和开始点时，虚拟助理800可确定特定音频流的持续时间。在一些实施方案中，基于特定音频流的持续时间，虚拟助理800可以确定词汇触发是否包括在特定音频流中。在一些实施方案中，虚拟助理800不确定特定音频流的持续时间，但是可以使用特定音频流的检测到的结束点和检测到的开始点来确定词汇触发是否包括在特定音频流中。
如上所述，图9示出了包括一个或多个话语的音频流912(例如，“外面太黑了。把灯打开，Siri。”)并且虚拟助理800确定词汇触发(例如，“Siri”)包括在音频流912中。如图9所示，音频流912的一个或多个话语可包括不指向虚拟助理800的至少一个话语。例如，第一话语“外面太黑了”可以是评论，而不是指向在设备900上操作的虚拟助理(例如，虚拟助理800)的话语。因此，虚拟助理可不执行任务或不基于这样的话语采取行动。如下文详细描述的，通过使用各种技术，虚拟助理可以确定话语不是指向它的，因此这样的话语要被忽略。这样的话语可包括例如用户的评论、从一个用户指向另一个用户的话语等。虚拟助理确定话语是否指向它的能力提高了设备的操作效率，因为虚拟助理可以忽略任何不指向它的话语，同时消除或减少用触发词或短语引导指向虚拟助理的每个话语的要求。
参考图8，在一些实施方案中，根据确定的一个或多个音频流802的特定音频流包括词汇触发(例如，“Siri”)，输入模块810生成一个或多个语音结果816。语音结果816可以包括一个或多个话语的音频表示(例如，语音表示)，其包括在特定音频流中。输入模块810还向自然语言引擎820提供语音结果816，该自然语言引擎可包括一个或多个模块，诸如语音转文本(STT)处理模块730和/或自然语言处理模块732(图7B中所示)或其变型。基于语音结果816，自然语言引擎820可生成表示特定音频流中的一个或多个话语的候选文本表示822。如上所述，每个候选文本表示可以是与特定音频流中的话语相对应的字词或令牌。使用图9中所示的音频流912作为示例，在设备900上操作的虚拟助理的自然语言引擎可执行音频流912的每个话语的语音转文本转换，并生成包括第一候选文本表示(例如，“外面太黑了。”)和第二候选文本表示(例如，“把灯打开，Siri。”)的候选文本表示。
在一些实施方案中，自然语言引擎820还可确定与一个或多个候选文本表示822相对应的置信水平。例如，如上所述，每个候选文本表示可与语音识别置信度得分相关联。并且自然语言引擎820可对候选文本表示822进行排序(例如，使用STT处理模块730)，并为候选意图生成或推导提供n个最佳(例如，n个最高排序)的候选文本表示。
如上所述，自然语言引擎820可以包括例如下述各项中的一个或多个：STT处理模块730、语音字母表转换模块731、词汇744、用户数据748和/或自然语言处理模块760。在一些实施方案中，使用自然语言处理模块760，自然语言引擎820还可解释候选文本表示以推导预缓解意图和可选地与预缓解意图相关联的置信水平。例如，自然语言引擎820可以可选地对与预缓解意图相关联的置信水平进行排序，并为候选意图生成或推导提供n个最佳预缓解意图。
参考图8，虚拟助理800的误触发缓解器(FTM)840可以确定虚拟助理800是否要忽略一个或多个候选文本表示822(或排序的候选文本表示)的至少一个候选文本表示。FTM840可使用例如图7B中所示的数字助理模块726的子模块或变型来实现。例如，FTM 840可包括自然语言处理732或其变型，以推导一个或多个候选意图842。在一些实施方案中，FTM840可包括决策树，诸如简单决策树或提升决策树。如上所述，在一些实施方案中，特定音频流中的一个或多个话语的至少一个话语可能不指向虚拟助理800，因此可被虚拟助理800忽略。
图9示出了确定是否要忽略至少一个候选文本表示的一个示例。如图9所示并且如上所述，基于用户910的话语，在设备900上操作的虚拟助理的自然语言引擎(例如，NLE820)可生成例如两个候选文本表示，诸如“外面太黑了。”和“把灯打开，Siri。”在一些实施方案中，虚拟助理的FTM(例如，FTM 840)针对两个候选文本表示中的每一个确定候选文本表示是否包括词汇触发。例如，FTM确定第一候选文本表示(例如，“外面太黑了。”)不包括词汇触发，但是第二候选文本表示(例如，“把灯打开，Siri。”)包括词汇触发(例如，“Siri”)。
参考图8，在一些实施方案中，如果FTM 840确定候选文本表示包括词汇触发，则FTM 840确定相应的用户话语指向虚拟助理800，因此该特定候选文本表示不要被忽略。因此，该特定候选文本表示应当被进一步处理，如下文更详细描述的。作为图9中所示的示例，在设备900上操作的虚拟助理的FTM确定第二候选文本表示(例如，“把灯打开，Siri。”)不要被忽略，因为它包括单个字词的词汇触发器“Siri”。
参考图8，在一些实施方案中，如果FTM 840确定候选文本表示不包括词汇触发，则FTM 840可以估计对应于特定候选文本表示的话语不指向虚拟助理800的可能性。使用图9所示的示例，如上所述，在设备900上操作的虚拟助理的FTM确定第一候选文本表示(例如，“外面太黑了。”)不包括词汇触发。此外，使用决策树，虚拟助理的FTM可以估计对应于第一候选文本表示的话语不指向虚拟助理的可能性。例如，FTM可以确定对应于第一候选文本表示(例如，“外面太黑了。”)的预缓解意图不或可能不与虚拟助理识别的域或候选意图相关联。因此，FTM可以估计与第一候选文本表示(例如，“外面太黑了。”)相对应的话语不指向虚拟助理的可能性，并且确定该估计的可能性是否满足阈值条件。如果满足，则FTM确定话语不指向虚拟助理。因此，出于生成候选意图的目的，可以忽略第一候选文本表示(例如，“外面太黑了。”)。在一些实施方案中，确定是否要忽略候选文本表示还可基于上下文信息，诸如使用模式和/或感官数据的，如下文更详细描述的。
再次参考图8，在一些实施方案中，FTM 840可针对候选文本表示822中的每一个确定是否要忽略特定候选文本表示。如果要忽略候选文本表示822中的至少一个，则FTM 840可基于未要被忽略的候选文本表示生成一个或多个候选意图842。例如，基于未要被忽略的候选文本表示的预缓解意图，FTM 840可以推导候选意图842。接续图9中所示的上述示例，在设备900上操作的虚拟助理的FTM确定要忽略第一候选文本表示(例如，“外面太黑了。”)，而不要忽略第二候选文本表示(例如，“把灯打开，Siri。”)。因此，在一些实施方案中，虚拟助理的FTM可尝试将第二候选文本表示的预缓解意图与本体(例如，本体760)中的识别域中的一者相关联以对其进行解释，从而推导候选意图。例如，FTM可选择与第二候选文本表示相对应的预缓解意图(例如，打开用户起居室中的灯)作为候选意图，同时过滤掉与第一候选文本表示相对应的预缓解意图。
参考图8，在一些实施方案中，FTM 840可以获取与一个或多个候选意图842中的每一个相对应的置信水平。如上所述，对于每个预缓解意图，NLE 820可生成一个置信水平。例如，特定候选文本表示可以与多个已识别的域相关联，因此可以从同一候选文本表示推导出多个预缓解意图。NLE 820和/或FTM 840可以确定置信度得分(例如，基于其在本体中的各种触发节点的相对重要性)以选择具有最高置信度值的域，并且进而确定相应的候选意图。
参考图8，在一些实施方案中，虚拟助理800包括候选意图评估器(CIE)860。CIE860可确定一个或多个候选意图842是否包括至少一个可执行意图。例如，CIE 860可针对每个候选意图842确定是否可执行任务。在一些实施方案中，CIE 860可在不实际执行任务的情况下(例如，进行干运行)作出此类确定。作为一个示例，CIE 860可包括数字助理模块726的一个或多个子模块或其变型，诸如图7B中所示的任务流处理模块736和对话处理模块734。CIE 860可使用这些子模块或其变型来执行确定的候选意图842是否是可执行意图，而不将结果提供给语音合成模块740并且不输出结果。
作为图8所示的另一个示例，CIE 860可包括任务流处理模块862和对话处理模块864，以用于确定候选意图842是否是可执行意图。图8所示的任务流处理模块862和对话处理模块864可以是如图7B所示的任务流处理模块736和对话处理模块734的副本，不同之处在于任务流处理模块862和对话处理模块864可不将其处理结果提供给语音合成模块或以其他方式将结果输出给用户。因此，CIE 860可确定候选意图842是否是可执行意图，并且可在虚拟助理8000不实际执行任务的情况下作出此类确定。因此，如果任务不能执行或者仅能部分地执行，则CIE 860可在不使虚拟助理800实际执行任务的情况下作出此类确定，而是应当尝试获取用于实际执行任务的更多信息(例如，获取上下文信息或发起与用户的对话以获取更多信息)。在不实际执行任务的情况下确定候选意图是否是执行意图提高了操作效率并改进了人机界面。例如，这种确定节省了电力并避免输出部分执行的任务或使用户混淆。
接续图9所示的示例，如上所述，基于候选文本表示(例如，“把灯打开，Siri。”)，在设备900上操作的虚拟助理的FTM生成打开用户起居室中的灯的候选意图。虚拟助理的CIE(例如，CIE 860)确定是否可针对该候选意图执行任务。在一些实施方案中，CIE可使用任务流处理模块(例如，任务流处理模块862)和/或对话处理模块(例如，对话处理模块864)来执行这种确定。例如，任务流处理模块可基于使用相应候选意图生成的结构化查询来尝试执行打开用户起居室中的灯的任务。在一些示例中，任务流处理模块可以确定不能执行这样的任务，因为它无法找到控制起居室中的灯的家庭自动化设备。在一些示例中，任务流处理模块可以确定控制灯的家庭自动化设备可用，因此可以执行相应的任务。
参考图8，在一些实施方案中，如果CIE 860确定可以执行与候选意图842相对应的任务，则其确定特定候选意图842是可执行意图。CIE 860可对每个候选意图842进行重复确定并生成可执行意图868。如图8所示，CIE 860向任务执行模块880提供每个可执行意图868，该任务执行模块根据可执行意图868执行一个或多个任务。任务执行模块880可包括数字助理模块726的一个或多个子模块或其变型，诸如图7B中所示的任务流处理模块736和对话处理模块734。与不使得任务被实际执行的CIE 860不同，任务执行模块880根据可执行意图868接收一个结构化查询(或多个结构化查询)，完成结构化查询，如果需要，还执行“完成”用户的最终请求所需的任务。接续图9所示的示例，在接收到打开用户起居室中的灯的可执行意图时，在设备900上操作的虚拟助理的任务执行模块可以使灯打开并任选地输出可执行意图的执行结果(例如，提供音频和/或视觉输出942，诸如“您的灯已打开。”)。
再次参考图8，在一些实施方案中，CIE 860可基于与执行任务相关联的置信水平的估计来确定是否可以执行任务。例如，CIE 860可以估计与执行任务相关联的置信水平，并确定与执行任务相关联的置信水平是否满足阈值置信水平。如果CIE 860确定与执行任务相关联的置信水平满足阈值置信水平，则CIE 860确定可以执行任务。
图10示出了示例性虚拟助理1000的框图，以用于使用执行结果和上下文信息提供自然语言交互。在一些示例中，数字助理1000(例如，数字助理系统700)可由用户设备根据各种实施方案来实现。在一些实施方案中，用户设备、服务器(例如，服务器108)或其组合可实现虚拟助理1000。用户设备可利用例如如图1、图2A至图2B、图4、图9、图11A至图11B、图12A至图12D、图13A至图13B和图14A至图14D所示的设备104、200、400、900、1120、1220、1320或1420来实现。类似于虚拟助理800，虚拟助理1000包括输入模块810、自然语言引擎816、FTM 840、CIE 860和任务执行模块880。虚拟助理1000的这些模块或部件类似于上文关于虚拟助理800所述的那些，因此不再重复描述。在一些实施方案中，虚拟助理1000的各种模块、模型、应用程序、词汇和用户数据中的一者或多者可接收附加信息，诸如先前的执行结果和/或上下文信息，以帮助检测语音活动、确定候选文本表示、确定候选意图、确定可执行意图和/或执行可执行意图。
参考图10和图11A，例如，在设备1120上操作的虚拟助理(例如，虚拟助理1000)经由输入模块(例如，输入模块810)从用户1110接收音频流1112。音频流1112包括一个或多个用户话语，诸如“今天天气怎么样，Siri？你知道股票价格是多少吗？”虚拟助理使用包括在音频流1112中的话语来生成语音结果。基于语音结果，虚拟助理通过自然语言引擎(例如，自然语言引擎820)生成一个或多个候选文本表示(例如，候选文本表示1022)。
接下来，对于候选文本表示的每个候选文本表示，虚拟助理通过FTM(例如，FTM840)确定虚拟助理是否要忽略特定候选文本表示。如上所述，在一些实施方案中，虚拟助理可以确定例如特定候选文本表示是否包括词汇触发。作为图11A中所示的示例，表示音频流1112的候选文本表示包括第一候选文本表示(例如，“今天天气怎么样，Siri？”)和第二候选文本表示(例如，“你知道股票价格是多少吗？”)。虚拟助理确定第一候选文本表示包括词汇触发(例如，“Siri”)，因此不要被忽略，因为相应的话语指向在设备1120上操作的虚拟助理。关于第二候选文本表示，虚拟助理确定其不包括词法触发。根据这种确定，虚拟助理估计对应于第二候选文本表示的话语不指向虚拟助理1000的可能性。
参考图10和图11A，在一些实施方案中，为了估计对应于第二候选文本表示的话语不指向虚拟助理的可能性，虚拟助理获取上下文信息(例如，执行结果和上下文信息1044)。上下文信息可与在设备1120上操作的虚拟助理的使用模式相关联。虚拟助理的使用模式可指示用户1110使用虚拟助理和/或使用设备1120执行的特定活动的模式，如图11A所示。例如，用户1110可能经常在早上6点左右询问关于天气和股票价格的同一问题。因此，可以在早上6点或6点左右针对用户的活动(例如，向虚拟助理询问同一问题)生成使用模式。上下文信息可包括从设备1120获取的这种使用模式和时间1122(例如，指示当前时间是早上6点左右)。基于与使用模式相关联的上下文信息，虚拟助理经由FTM(例如，FTM 840)可以估计对应于第二候选文本表示的话语不指向虚拟助理的可能性。例如，基于指示用户经常在早上6点左右向虚拟助理询问股票价格以及当前时间是早上6点左右的上下文信息，虚拟助理可以估计话语“你知道股票价格是多少吗？”不指向虚拟助理1000的可能性很低(例如，不满足阈值)。因此，虚拟助理基于该估计的可能性确定不要忽略第二候选文本表示。
在一些实施方案中，上下文信息还可用于确定候选意图是否是可执行意图。接续图11A所示的上述示例，基于确定不要忽略第一候选文本表示(例如，“今天天气怎么样，Siri？”)和第二候选文本表示(例如，“你知道股票价格是多少吗？”)两者，在设备1120上操作的虚拟助理生成一个或多个候选意图。例如，虚拟助理生成获取今天的天气信息的第一候选意图和获取股票价格信息的第二候选意图。对于每个候选意图，虚拟助理通过CIE(例如，CIE 860)确定是否可以执行任务。如上所述，CIE可通过使用例如任务流处理模块和/或对话处理模块来作出这种确定，而无需实际执行任务。
在一些实施方案中，关于获取天气信息的第一候选意图，虚拟助理确定可能需要附加的位置信息来执行获取天气信息的任务。但是，该位置信息未在第一候选文本表示中呈现或由第一候选文本表示提供。因此，在一些实施方案中，虚拟助理可从通信地耦接到设备1120的一个或多个传感器获取与感官数据相关联的上下文信息，并基于上下文信息确定是否可以执行任务。例如，可以获取位置数据作为指示设备1120的当前位置的上下文信息。利用该上下文信息，虚拟助理确定获取天气信息的第一候选意图是可执行意图，因为可以从内部或外部数据源(例如，从天气信息网站)获取设备1120的当前位置的天气信息。
参考图11A，关于获取股票价格信息的第二候选意图，虚拟助理确定可能需要股票名称的附加信息来执行获取股票价格的任务。但是，该股票名称信息未在第二候选文本表示中呈现或由第二候选文本表示提供。因此，在一些实施方案中，虚拟助理可以获取与虚拟助理和/或设备1120的使用模式相关联的上下文信息。虚拟助理和/或设备1120的使用模式可以指示用户1110使用虚拟助理1000和/或使用用户设备1120执行的特定活动的模式，如图11A所示。例如，用户1110可能经常在早上6点左右询问关于标准普尔指数的问题。因此，可以在早上6点或6点左右针对用户的活动(例如，向虚拟助理询问标准普尔500指数的同一问题)生成使用模式。上下文信息可包括由设备1120提供的这种使用模式和时间1122(例如，指示当前时间是早上6点左右)。利用该上下文信息，虚拟助理确定获取股票价格的第二候选意图是可执行意图，因为可以获取标准普尔500指数信息。
图11B示出了示例性用户界面，以用于使用与感官数据相关联的上下文信息由虚拟助理(例如，图10中所示的虚拟助理1000)提供自然语言交互。如图10和图11B所示，例如，在设备1120上操作的虚拟助理从用户1110和用户1130接收一个或多个音频流。音频流可包括例如来自用户1130的话语1132、来自用户1130的话语1134和来自用户1110的话语1136。来自用户1110的一个或多个话语可指向虚拟助理或用户1130。例如，来自用户1110的话语1132可包括“Siri，今天的标准普尔指数是多少？”。类似于上文所述的那些，虚拟助理确定话语1132的第一候选文本表示包括词汇触发(例如，“Siri”)，因此不要被忽略。基于这种确定，虚拟助理生成第一候选意图并确定获取标准普尔500指数的第一候选意图是可执行的。因此，虚拟助理执行获取标准普尔500指数的任务并输出结果1138(例如，指示“今天的标准普尔500指数为12000”的音频和/或视觉输出)。
如图11B所示，在听到虚拟助理1000输出的标准普尔500指数时，用户1130可提供询问用户1110的话语1134“你有没有听说AAPL今天上涨了很多？”在设备1120上操作的虚拟助理可以生成对应于话语1134的第二候选文本表示，并确定是否要忽略第二候选文本表示。例如，虚拟助理可以确定第二候选文本表示不包括词汇触发，并且因此估计话语1134不指向虚拟助理的可能性。在一些实施方案中，为了估计该可能性，虚拟助理可以从通信地耦接到设备1120的一个或多个传感器获取感官数据，并且基于所获取的感官数据估计话语1134不指向虚拟助理的可能性。例如，设备1120可包括光学传感器264(例如，相机)，该光学传感器在任何给定时间检测用户1110对于设备1120的眼睛注视。光学传感器264可以检测例如用户1130在设备1120上操作的虚拟助理接收到话语1134时没有看设备1120。因此，虚拟助理使用光学传感器264提供的感官数据估计话语1134不指向虚拟助理的可能性很高(例如，与阈值比较)。因此，FTM 840确定要忽略第二候选文本表示。
接续图11B中所示的示例，在听到话语1134时，用户1110可以提供话语1136“真的吗，今天AAPL的价格是多少？”虚拟助理可以生成对应于话语1136的第三候选文本表示，并确定是否要忽略第三候选文本表示。类似于上文所述的那些，虚拟助理可以确定第三候选文本表示不包括词汇触发。基于这样的确定，虚拟助理可以估计话语1136不指向在设备1120上操作的虚拟助理的可能性。在一些实施方案中，为了估计该可能性，虚拟助理获取感官数据，并且基于所获取的感官数据估计话语1136不指向虚拟助理1000的可能性。例如，光学传感器264可以检测例如用户1110在虚拟助理接收到话语1136时正在看设备1120。因此，虚拟助理使用光学传感器264提供的感官数据估计话语1136不指向虚拟助理1000的可能性很低(例如，与可能性阈值比较)。因此，虚拟助理确定不要忽略第三候选文本表示。因此，虚拟助理可基于第三候选文本表示生成候选意图，并确定候选意图是可执行意图。因此，虚拟助理执行任务以获取AAPL的股票价格并输出结果1140(例如，指示“今天AAPL以200美元收盘”的音频和/或视觉输出)。
图12A至图12D示出了用于使用与执行先前确定的可执行意图相关联的上下文信息由在设备1220上操作的虚拟助理提供自然语言交互的示例性用户界面。如图10和图12A所示，用户1210提供第一音频流1212(例如，“Siri，放点儿音乐”)，该第一音频流由在设备1220上操作的虚拟助理接收。类似于上文所述的那些，虚拟助理确定第一音频流1212包括词汇触发(例如，“Siri”)、生成第一音频流1212(例如，“Siri，放点儿音乐。”)的候选文本表示、确定不要忽略第一音频流1212的候选文本表示(因为它包括词汇触发)、生成候选意图、确定候选意图是可执行意图(例如，可以执行播放音乐的任务)、执行可执行意图，并输出执行结果(例如，输出音频和/或视觉消息1224，诸如“这是您可能喜欢的一些音乐。”)。如图12A所示，虚拟助理1000可以在时间1222A(例如，上午9点)接收并处理第一音频流1212。
如图12B所示，当在设备1220上操作的虚拟助理正在执行播放音乐的任务时，它可以在时间1222B(例如，上午9:05)接收来自用户1210的第二音频流1214。在一些实施方案中，虚拟助理生成第二音频流1214的候选文本表示。基于第二音频流1214的候选文本表示，虚拟助理可以确定第二音频流1214(例如，“停止”)是否是与第一音频流1212(例如，“放点儿音乐”)相同的音频会话的一部分。
在一些实施方案中，为了确定第二音频流1214是否是包括第一音频流1212的同一音频会话的一部分，在设备1220上操作的虚拟助理可以获取与执行先前确定的可执行意图相关联的上下文信息。例如，虚拟助理检测到当接收到第二音频流1214时，播放音乐作为执行先前确定的可执行意图的结果。因此，虚拟助理确定第二音频流1214是或可能是包括第一音频流1212的同一音频会话的一部分。在一些实施方案中，这种确定还可以考虑第一音频流1212和第二音频流1214之间的关系(例如，语义关系、主题关系)。考虑到关系的实施方案在下文进一步详细描述。
参考图12B，根据确定的第二音频流1214是包括第一音频流1212的同一音频会话的一部分，虚拟助理基于第二音频流1214的候选文本表示生成第二候选意图。虚拟助理还确定第二候选意图是否包括可执行意图。在一些实施方案中，该确定可基于与虚拟助理先前执行或正在执行的任务相关联的上下文信息。例如，上下文信息可与执行播放音乐的先前任务相关联。如图12B所示，因此可以确定第二候选意图是停止播放当前正在播放的音乐。因此，虚拟助理可根据该第二候选意图确定可以执行任务(例如，停止播放音乐)，因此第二候选意图是可执行的。因此，虚拟助理执行停止播放音乐的可执行意图。在一些实施方案中，虚拟助理任选地提供指示执行结果的音频和/或视觉输出1226(例如，“好的”)。
图12C和图12D示出了类似的场景，其中在设备1220上操作的虚拟助理接收包括话语诸如“Siri，放点儿音乐。”的第一音频流1242。类似于上文所述的那些，虚拟助理确定播放音乐的可执行意图、执行可执行意图，并且任选地输出音频/视觉消息1222(例如，“这是您可能喜欢的一些音乐。”)。当音乐仍在播放时，虚拟助理接收包括话语诸如“跳过这首歌”的第二音频流1244。虚拟助理检测到当接收到第二音频流1244时，播放音乐作为执行先前确定的可执行意图的结果。因此，虚拟助理可确定第二音频流1244是或可能是包括第一音频流1242的同一音频会话的一部分。因此，虚拟助理基于第二音频流1244的候选文本表示生成第二候选意图。虚拟助理还确定第二候选意图是否包括可执行意图。例如，如图12D所示，可以确定第二候选意图是跳过当前正在播放的音轨1并开始播放下一个音轨。因此，虚拟助理可根据该第二候选意图确定可以执行任务，因此第二候选意图是可执行的。因此，虚拟助理执行该可执行意图以停止播放音轨1并开始播放音轨2。
图13A至图13B示出了示例性用户界面，以用于使用与用户话语或音频流的关系相关联的上下文信息由虚拟助理提供自然语言交互。如上所述，可将上下文信息提供给虚拟助理的一个或多个模块或部件(例如，图10中所示的虚拟助理1000的FTM 840和CIE 860)。在一些实施方案中，可将上下文信息提供给CIE(例如，CIE 860)以确定候选意图是否是可执行意图。这样的上下文信息可包括例如表示音频流中的用户话语的候选文本表示之间的一个或多个关系。
作为图13A所示的示例，在设备1320上操作的虚拟助理(例如，虚拟助理1000)接收音频流1312。音频流1312可包括第一话语(例如，“你知道吗，勇士队在上一场比赛中表现得非常出色。”)和第二话语(例如，“下一场比赛是什么时候，Siri？”)。基于音频流1312，可以生成候选文本表示以表示包括在音频流1312中的话语。虚拟助理可以确定(例如，使用FTM840)第一话语(例如，“你知道吗，勇士队在上一场比赛中表现得非常出色。”)的候选文本表示不包括词汇触发，并且第一话语可能不指向虚拟助理。因此，虚拟助理可以确定为了生成候选意图要忽略第一话语的候选文本表示。在一些实施方案中，虽然为了生成候选意图而忽略了第一话语的候选文本表示，但是可以将该候选文本表示保留以用于确定多个候选文本表示之间的关系。
接续图13A中所示的示例，虚拟助理可以确定(例如，使用FTM 840)第二话语(例如，“下一场比赛是什么时候，Siri？”)的候选文本表示包括词汇触发，因此第二话语可能指向虚拟助理。因此，第二话语的候选文本表示不要被忽略。因此，虚拟助理基于第二话语的候选文本表示生成候选意图，并确定候选意图是否是可执行意图。如上所述，为了确定候选意图是否是可执行意图，在一些实施方案中，虚拟助理确定是否可以根据可执行意图执行任务。可基于第二话语的候选文本表示并且基于指示候选文本表示之间的关系的上下文信息来确定是否可以执行任务。
如上所述，音频流1312中的第二话语的候选文本表示可包括“下一场比赛是什么时候，Siri？”。仅基于该候选文本表示，虚拟助理可能无法确定是否可以执行任务，因为候选文本表示未指示用户指的是哪个比赛。在一些示例中，虚拟助理可以确定相邻候选文本表示之间的关系。例如，虚拟助理确定第一话语(例如，“你知道吗，勇士队在上一场比赛中表现得非常出色。”)的候选文本表示在语义上、主题上和/或在时间上与第二话语(例如，“下一场比赛是什么时候，Siri？”)的候选文本表示相关。因此，虚拟助理可以使用与候选文本表示之间的关系相关联的上下文信息来确定是否可以执行任务。在该示例中，上下文信息指示当用户1310询问“下一场比赛是什么时候，Siri？”时，用户1310可能是指金州勇士队的比赛。因此，虚拟助理基于上下文信息确定可以执行任务(例如，可以通过搜索互联网来执行获取勇士队比赛的时间表的任务)，从而确定候选意图是可执行意图。因此，虚拟助理可以执行可执行意图并提供例如音频和/或视觉输出1326，诸如“金州勇士队下一场比赛将于明天下午5:30开始。”
现在转到图13B，与多个音频流之间的关系(例如，语义、主题、时间)相关联的上下文信息也可用于确定两个或更多个音频流是否在同一音频会话中。参考图13B，在设备1320上操作的虚拟助理(例如，图10中所示的虚拟助理1000)接收包括话语诸如“勇士队的比赛得分是多少？”的第一音频流1342。类似于上文所述的那些，虚拟助理生成第一音频流1342的候选文本表示、确定不要忽略该候选文本表示、生成候选意图、确定该候选意图是可执行意图、执行该可执行意图，并提供音频和/或视觉输出1346，诸如“勇士队以123比112的比分击败尼克斯队。”
在一些实施方案中，在虚拟助理输出对应于第一音频流1342的可执行意图的执行结果时或之后，在设备1320上操作的虚拟助理接收包括话语诸如“下一场比赛是什么时候？”的第二音频流1344。在一些实施方案中，虚拟助理生成候选文本表示以表示第二音频流1344。无论第二音频流1344是否包括词汇触发，都可以执行第二音频流1344的候选文本表示的生成。例如，虚拟助理可以确定接收第二音频流1344与执行对应于第一音频流1342的可执行意图之间的时间关系。虚拟助理还确定时间关系指示在从执行可执行意图的阈值时间段内接收到第二音频流1344，因此第二音频流1344中的词汇触发不需要用于生成第二音频流1344的候选文本表示。
在生成第二音频流1344的候选文本表示之后，在设备1320上操作的虚拟助理可以确定第二音频流1344是否是包括第一音频流1342的同一音频会话的一部分。虚拟助理可以确定第一音频流1322和第二音频流1344的各个候选文本表示之间的关系。例如，虚拟助理确定第一音频流1322(例如，“勇士队的比赛得分是多少？”)的候选文本表示在语义上、主题上和/或在时间上与第二音频流(例如，“下一场比赛是什么时候？”)的候选文本表示相关。因此，虚拟助理可使用与第一音频流和第二音频流的各个候选文本表示之间的关系相关联的上下文信息来确定音频流是否在同一音频会话中。在图13B所示的示例中，虚拟助理确定第二音频流1344是包括第一音频流1322的同一音频会话的一部分，因为音频流的各个候选文本表示在语义上和/或主题上是相关的。根据这种确定，虚拟助理基于第二音频流1322的候选文本表示生成候选意图，确定候选意图是否是可执行意图，并且如果是，则执行可执行意图。因此，虚拟助理提供音频和/或视觉输出1348，诸如“金州勇士队下一场比赛将于明天下午5:30开始。”
图14A至图14D示出了用于使用上下文信息从多个任务中选择任务的示例性用户界面。如上所述，可将先前的执行结果和/或上下文信息提供给虚拟助理的一个或多个模块或部件(例如，图10中所示的虚拟助理1000的FTM 840和CIE 860)。在一些实施方案中，可将上下文信息提供给任务执行模块880，以便选择要执行的一个或多个任务。参考图14A，在设备1420上操作的虚拟助理接收包括话语诸如“Siri，放点儿音乐。”的第一音频流1412。类似于上文关于图12A描述的那些，虚拟助理确定音频流1412包括词汇触发、生成候选文本表示、确定不要忽略该候选文本表示、生成候选意图、确定该候选意图是可执行意图，并执行该可执行意图。因此，虚拟助理开始播放音乐并任选地提供音频和/或视觉输出1424，诸如“这是您可能喜欢的一些音乐。”
参考图14B，在一些实施方案中，当虚拟助理正在执行先前确定的可执行意图(例如，播放音乐)时，它接收第二音频流1414。第二音频流1414可包括另一个用户请求，其可以在语义上或主题上不与第一音频流1412相关。例如，第二音频流1414包括话语诸如“我想给我老婆发一条消息，Siri。”在设备1420上操作的虚拟助理可以重复类似于上文所述那些的过程，并执行基于第二音频流1414推导的第二可执行意图。因此，虚拟助理使设备1420显示例如用于编写文本消息的文本消息用户界面1426。
转到图14C，在一些实施方案中，在执行先前确定的可执行意图(例如，播放音乐和显示用于编写文本消息的文本消息用户界面)时，在设备1420上操作的虚拟助理接收第三音频流1416。第三音频流1416可与先前确定的可执行意图中的一个或两个的执行相关。例如，第三音频流1416可包括话语诸如“停止。”基于第三音频流1416，虚拟助理可以确定例如停止播放当前正在播放的音乐的第一候选意图和停止编写文本消息的第二候选意图。虚拟助理还可确定第一候选意图和第二候选意图均是可执行意图，因为可以执行相应的任务。
在一些实施方案中，如果存在多个可执行意图，则虚拟助理从与多个可执行意图相关联的多个任务中选择要执行的单个任务。在一些实施方案中，对用于执行的单个任务的选择可基于上下文信息。例如，虚拟助理获取与由虚拟助理发起的最近任务相关联的上下文信息，并基于此类上下文信息选择单个任务以供执行。在如上文所述的该示例中，由虚拟助理发起的最近任务是显示用于编写文本消息的用户界面。因此，基于与显示用于编写文本消息的用户界面的该最近任务相关联的上下文信息，虚拟助理消除包括在第三音频流1416中的用户请求的歧义，并选择停止或取消编写文本消息的任务。任选地，如图14C所示，虚拟助理可提供音频和/或视觉输出1432，诸如“好的，给您老婆的消息已取消。”
在一些实施方案中，如果存在多个可执行意图，则虚拟助理基于用户选择从与多个可执行意图相关联的多个任务中选择要执行的单个任务。这在图14D中示出，其中虚拟助理输出多个任务选项。例如，虚拟助理提供音频和/或视觉输出1434(例如，“您想停止播放音乐还是想取消给您老婆发送信息？”)提示用户1410选择任务。虚拟助理接收音频流1418中的用户选择(例如，“停止播放音乐”)并基于该用户选择执行任务。任选地，如图14D所示，虚拟助理可提供音频和/或视觉输出1436，诸如“音乐已停止。”
在一些实施方案中，如果存在多个可执行意图，则虚拟助理基于与多个任务中的每个相关联的优先级从与多个可执行意图相关联的多个任务中选择要执行的单个任务。例如，虚拟助理(例如，虚拟助理1000)可接收包括话语诸如“今天天气怎么样，Siri？”的第一音频流。在虚拟助理响应之前，它接收到包括话语诸如“发生车祸了！Siri，拨打911！”的第二音频流。虚拟助理基于该音频流确定获取天气信息的第一可执行意图和进行紧急呼叫的第二可执行意图。在一些实施方案中，虚拟助理可以确定与要执行的多个任务中的每个相关联的优先级，并基于所确定的优先级来选择任务。在以上示例中，当在接收到第一音频流之后接收到第二音频流时，虚拟助理确定与进行紧急911呼叫的第二可执行意图相关联的任务的优先级比与获取天气信息的第一可执行意图相关联的任务的优先级更高。因此，虚拟助理选择与第二可执行意图相关联的任务以供执行(例如，进行紧急911呼叫)。
虽然上文所述的各种实施方案涉及特定类型的上下文信息，但应当理解，所述技术还可使用任何类型的上下文信息，如2017年9月1日提交的名称为“Methods and Systemsfor Customizing Suggestions Using User-specific Information”的美国专利申请15/694,267中所述，该专利申请据此全文以引用方式并入本文。
5.提供自然语言交互的过程
图15A至图15G示出了根据各种实施方案的过程1500，以用于操作虚拟助理以提供自然语言交互。例如使用实现虚拟助理的一个或多个电子设备来执行过程1500。在一些示例中，使用客户端-服务器系统(例如，系统100)来执行过程1500，并且在服务器(例如，DA服务器106)和客户端设备之间以任何方式来划分过程1500的框。在其他示例中，在服务器和多个客户端设备(例如，移动电话和智能手表)之间划分过程1500的框。因此，虽然过程1500的部分在本文中被描述为由客户端-服务器系统的特定设备执行，但应当理解，过程1500不限于此。在其他示例中，使用仅客户端设备(例如，用户设备104、200、400、600、900、1120、1220、1320或1420)或仅多个客户端设备来执行过程1500。在过程1500中，一些框被任选地组合，一些框的次序被任选地改变，并且一些框被任选地省略。在一些示例中，可结合过程1500来执行附加步骤。
如上所述，总是要求触发短语处于用户话语的开始部分可使得人机交互变得麻烦并且使得人机用户界面不太自然和高效。本申请中描述的技术(包括由过程1500表示的技术)消除或减少了这种用触发短语引导每个用户话语的要求的需要。相反，触发字词或短语可放置在可包括一个或多个用户话语的音频流的任何部分中。此外，本申请中所述的技术不需要使用包括多个字词的触发短语(例如，“嘿，Siri”)。单个字词(例如，“Siri”)可用于指示包括用户话语的音频流指向虚拟助理。这使得交流方式更加自然。因此，这些技术增强了设备的可操作性并且使用户-设备界面更有效，另外，通过使用户能够更快速且有效地使用设备，这减少了电力使用并且延长了设备的电池寿命。
参考图15A，在框1502处，经由麦克风接收第一音频流(例如，如图9所示的音频流912)，第一音频流包括一个或多个话语。在框1504处，确定第一音频流是否包括词汇触发。在一些实施方案中，词汇触发是单字词的词汇触发。在一些实施方案中，第一音频流包括第一话语，并且单字词的词汇触发位于第一话语的除第一话语的开始部分之外的部分中。作为图9中描述的示例，词汇触发(例如，“Siri”)位于话语的末尾(例如，“把灯打开，Siri。”)。
在框1506处，为了确定第一音频流是否包括词汇触发，检测第一音频流的开始点。作为检测第一音频流的开始点的一个示例，在框1508处，检测到在接收到第一音频流之前没有语音活动。在框1510处，确定在接收第一音频流之前没有语音活动的时间是否超过第一阈值时间段。在框1512处，根据确定的没有语音活动的时间超过第一阈值时间段，基于在接收到第一音频流之前没有语音活动确定第一音频流的开始点。
在框1514处，为了确定第一音频流是否包括词汇触发，检测第一音频流的结束点。作为检测第一音频流的结束点的一个示例，在框1516处，经由麦克风检测到在接收到第一音频流的一个或多个话语之后没有语音活动。在框1518处，确定在接收到第一音频流的一个或多个话语之后没有语音活动的时间是否超过第二阈值时间段。在框1520处，根据确定的在接收到第一音频流的一个或多个话语之后没有语音活动的时间超过第二阈值时间段，基于在接收到第一音频流的一个或多个话语之后没有语音活动来确定第一音频流的结束点。
作为检测第一音频流的结束点的另一个示例，在框1522处，获取电子设备被配置为接收第一音频流的预先配置的持续时间。参考图15B，在框1524处，基于检测到的第一音频流的开始点和预先配置的持续时间来确定第一音频流的结束点。
作为检测第一音频流的结束点的另一个示例，在框1526处，确定音频文件的大小，音频文件表示所接收的第一音频流的一个或多个话语。在框1528处，将音频文件的大小与存储音频文件的缓冲器的容量进行比较。在框1530处，基于将音频文件的大小与存储音频文件的缓冲器的容量进行比较的结果来确定第一音频流的结束点。以上关于例如图8和图9详细描述了检测音频流的开始点和结束点的各种实施方案。
在框1532处，为了确定第一音频流是否包括词汇触发(例如，“Siri”)，确定词汇触发是否包括在第一音频流的开始点和结束点之间。
在框1534处，根据确定的第一音频流包括词汇触发，生成一个或多个话语的一个或多个候选文本表示。如上文参考图8所述，候选文本表示可由自然语言引擎(例如，NLE820)生成。
在框1536处，为了生成一个或多个候选文本表示，执行第一音频流的一个或多个话语中的每一个的语音到文本转换，以生成一个或多个候选文本表示。例如，可以执行图9中所示的音频流912的每个话语的语音到文本转换，以生成包括第一候选文本表示(例如，“外面太黑了。”)和第二候选文本表示(例如，“把灯打开，Siri。”)的候选文本表示。在框1538处，确定对应于一个或多个候选文本表示的置信水平。
参考图15C，在框1540处，确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示。在框1542处，为了确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示，确定所述至少一个候选文本表示是否包括词汇触发。在框1544处，根据确定的所述至少一个候选文本表示不包括词汇触发，估计对应于所述至少一个候选文本表示的话语不指向虚拟助理的可能性。如上所述，在图9所示的示例中，在设备900上操作的虚拟助理的FTM确定候选文本表示(例如，“外面太黑了。”)不包括词汇触发。此外，使用决策树，虚拟助理的FTM可以估计对应于特定第一候选文本表示的话语不指向虚拟助理的可能性。
作为估计对应于至少一个候选文本表示的话语不指向虚拟助理的可能性的一个示例，在框1546处，获取与虚拟助理的使用模式(例如，在特定时间询问特定问题的频率，如图10和图11A所示)相关联的上下文信息。在框1548处，基于与虚拟助理的使用模式相关联的上下文信息，估计对应于至少一个候选文本表示的话语不指向虚拟助理的可能性。
作为估计对应于至少一个候选文本表示的话语不指向虚拟助理的可能性的另一个示例，在框1550处，从通信地耦接到电子设备的一个或多个传感器获取感官数据(例如，如上所述的位置数据)。在框1552处，基于感官数据，估计对应于至少一个候选文本表示的话语不指向虚拟助理的可能性。
作为估计对应于至少一个候选文本表示的话语不指向虚拟助理的可能性的另一个示例，确定候选文本表示符合对应于对虚拟助理的识别/有效请求的语言模型(LM)和/或上下文无关文法(CFG)的程度。例如，候选文本表示诸如“吃蔬菜”可能与LM和/或CFG的一致性程度较低，因此不太可能指向虚拟助理。另一个候选文本表示诸如“预订一张两人桌”可能与LM和/或CFG的一致性程度较高，因此更有可能指向虚拟助理。
在框1554处，基于该估计的可能性，确定虚拟助理是否要忽略一个或多个候选文本表示的至少一个候选文本表示。作为上文关于图11A描述的一个示例，基于指示用户经常在早上6点左右向虚拟助理询问股票价格以及当前时间是早上6点左右的上下文信息，虚拟助理可以估计话语“你知道股票价格是多少吗？”不指向虚拟助理的可能性很低(例如，不满足阈值)。因此，虚拟助理基于该估计的可能性确定不要忽略特定候选文本表示。
参考图15D，在框1556处，根据确定的虚拟助理要忽略至少一个候选文本表示，基于除了要被忽略至少一个候选文本表示之外的一个或多个候选文本表示的候选文本表示生成一个或多个候选意图。为了生成候选意图，在框1558处，获取对应于一个或多个话语的一个或多个候选文本表示的一个或多个预缓解意图。在框1560处，从一个或多个预缓解意图选择对应于除了要被忽略的至少一个候选文本表示之外的一个或多个候选文本表示的一个或多个候选意图。如上文关于图10所描述的，候选意图可由FTM(例如，FTM 1044)生成。
在框1562处，确定一个或多个候选意图是否包括至少一个可执行意图。在框1564处，为了确定一个或多个候选意图是否包括至少一个可执行意图，对于一个或多个候选意图中的每一个，确定是否可以执行任务。如上所述，在一些实施方案中，这种确定可由CIE(例如，图10中所示的CIE 860)执行。作为确定是否可以执行任务的一个示例，在框1566处，获取与虚拟助理的使用模式相关联的上下文信息。在框1568处，基于与虚拟助理的使用模式相关联的上下文信息，确定是否可以执行任务。以上参考图11B示出了基于使用模式的这种确定的一个示例。
作为确定是否可以执行任务的另一个示例，在框1570处，获取与虚拟助理执行的先前任务相关联的上下文信息。在框1572处，基于与虚拟助理执行的先前任务相关联的上下文信息，确定是否可以执行任务。以上参考图12A至图12D示出了基于虚拟助理执行的先前任务的这种确定的一个示例。
参考图15E，作为确定是否可以执行任务的另一个示例，在框1574处，确定一个或多个候选文本表示之间的一个或多个关系。在框1576处，确定是否可以基于一个或多个候选文本表示中的一个或多个关系来执行任务。以上参考图13A至图13B示出了基于一个或多个关系的这种确定的一个示例。
作为确定是否可以执行任务的另一个示例，在框1578处，从通信地耦接到电子设备的一个或多个传感器获取感官数据(例如，位置数据)。在框1580处，确定是否可以基于感官数据执行任务。
作为确定是否可以执行任务的另一个示例，在框1582处，估计与执行任务相关联的置信水平。在框1584处，确定与执行任务相关联的置信水平是否满足阈值置信水平。在框1586处，根据确定的与执行任务相关联的置信水平满足阈值置信水平，确定可以执行任务。
在框1588处，根据确定的可以执行任务，确定一个或多个候选意图包括至少一个可执行意图。例如，如上文参考图11A所述，基于上下文信息(例如，使用模式和时间)，虚拟助理确定获取股票价格的特定候选意图是可执行意图。
在框1590处，根据确定的一个或多个候选意图包括至少一个可执行意图，执行至少一个可执行意图。在框1592处，根据至少一个可执行意图执行一个或多个任务。
参考图15F，为了执行至少一个可执行意图，在框1594处，从与多个可执行意图相关联的多个任务中选择用于执行的第一任务。作为选择用于执行的第一任务的一个示例，在框1596处，获取与由虚拟助理发起的最近任务相关联的上下文信息(例如，显示用于编写文本消息的用户界面，如图14B所示)。在框1598处，基于与虚拟助理执行的先前任务相关联的上下文信息来选择第一任务。
作为选择用于执行的第一任务的一个示例，在框1600处，输出对应于与多个可执行意图相关联的多个任务的多个任务选项。在框1602处，从多个任务选项接收用户选择。在框1604处，基于用户选择来选择用于执行的第一任务。以上参考图14D示出了基于用户选择来选择用于执行的任务。
作为选择用于执行的第一任务的一个示例，在框1606处，确定与多个任务中的每一个相关联的优先级。在框1608处，基于与多个任务中的每一个相关联的优先级来选择用于执行的第一任务。在框1610处，执行所选择的第一任务。如上所述，选择优先级较高的任务(例如，进行紧急呼叫)而不是优先级较低的任务(例如，报告天气信息)。
在框1612处，输出执行至少一个可执行意图的结果。
参考图15G，在框1614处，在执行至少一个可执行意图时，经由麦克风接收第二音频流。在框1616处，生成一个或多个第二候选文本表示以表示第二音频流。在框1618处，基于一个或多个第二候选文本表示，确定第二音频流是否是包括第一音频流的音频会话的一部分。
在框1620处，作为确定第二音频流是否是包括第一音频流的音频会话的一部分的一个示例，获取与执行至少一个可执行意图相关联的上下文信息。在框1622处，基于与执行至少一个可执行意图相关联的上下文信息，确定第二音频流是否是包括第一音频流的音频会话的一部分。
在框1624处，作为确定第二音频流是否是包括第一音频流的音频会话的一部分的另一个示例，确定第一音频流和第二音频流的各个候选文本表示之间的关系。在框1626处，基于第一音频流和第二音频流的各个候选文本表示之间的关系，确定第二音频流是否是包括第一音频流的音频会话的一部分。
在框1628处，根据确定的第二音频流是包括第一音频流的音频会话的一部分，基于一个或多个第二候选文本表示生成一个或多个第二候选意图。
在框1630处，确定一个或多个第二候选意图是否包括至少一个第二可执行意图。在框1632处，根据确定的一个或多个第二候选意图包括至少一个第二可执行意图，执行至少一个第二可执行意图。在框1634处，输出执行至少一个第二可执行意图的结果。以上参考图12A至图12D描述了图15G中示出的过程的示例。
出于解释的目的，前面的描述是通过参考具体实施方案来描述的。然而，上面的例示性论述并非旨在是穷尽的或将本发明限制为所公开的精确形式。根据以上教导内容，很多修改形式和变型形式都是可能的。选择并描述这些实施方案是为了最好地解释这些技术的原理及其实际应用程序。本领域的其他技术人员由此能够最好地利用这些技术以及具有适合于所预期的特定用途的各种修改的各种实施方案。
虽然参照附图对本公开以及示例进行了全面的描述，但应当注意，各种变化和修改对于本领域内的技术人员而言将变得显而易见。应当理解，此类变化和修改被认为被包括在由权利要求书所限定的本公开和示例的范围内。
如上所述，本技术的一个方面是收集和使用可从各种来源(例如，与虚拟助理或设备的使用模式相关联的上下文信息)获取的数据以改进人机界面，从而提供更自然的语言交互。本公开预期，在一些实例中，这些所采集的数据可包括唯一地识别或可用于联系或定位特定人员的个人信息数据。此类个人信息数据可以包括人口统计数据、基于位置的数据、电话号码、电子邮件地址、推特ID、家庭地址、与用户的健康或健康水平有关的数据或记录(例如，生命体征测量、药物信息、锻炼信息)、出生日期或任何其他识别信息。
本公开认识到在本发明技术中使用此类个人信息数据可用于使用户受益。例如，该个人信息数据可用于递送用户较感兴趣的目标内容。因此，使用此类个人信息数据使得能够对所递送的内容进行有计划的控制。此外，本公开还预期个人信息数据有益于用户的其他用途。例如，健康和健身数据可用于向用户的总体健康状况提供见解，或者可用作使用技术来追求健康目标的个人的积极反馈。
本公开还设想负责此类个人信息数据的收集、分析、公开、发送、存储或其他用途的实体将遵守已确立的隐私政策和/或隐私实践。具体地，此类实体应当实行并坚持使用被公认为满足或超出对维护个人信息数据的隐私性和安全性的行业或政府要求的隐私政策和实践。此类策略应当能被用户方便地访问，并应应当随着数据的采集和/或使用变化而被更新。来自用户的个人信息应当被收集用于实体的合法且合理的用途，并且不在这些合法使用之外共享或出售。此外，此类收集/分享应当仅在用户知情同意之后进行。另外，此类实体应当采取任何所需的步骤，以保障和保护对此类个人信息数据的访问，并且确保能够访问个人信息数据的其他人遵守他们的隐私政策和程序。另外，此类实体可使其本身经受第三方评估，以证明其遵守广泛接受的隐私政策和实践。此外，应当调整政策和实践，以便采集和/或访问的特定类型的个人信息数据，并适用于包括管辖范围的具体考虑的适用法律和标准。例如，在美国，对某些健康数据的收集或获取可能受联邦和/或州法律的管辖，诸如健康保险转移和责任法案(HIPAA)；而其它国家的健康数据可能受到其它法规和政策的约束并应当相应地处理。因此，在每个国家应当为不同的个人数据类型保持不同的隐私实践。
不管前述情况如何，本公开还预期用户选择性地阻止使用或访问个人信息数据的实施方案。即本公开预期可提供硬件元件和/或软件元件，以防止或阻止对此类个人信息数据的访问。例如，就收集用户活动的使用模式而言，本技术可被配置为允许用户在此类收集之前或期间选择“加入”或“退出”参与对个人信息数据的收集。在另一个示例中，用户可以选择不提供或共享用户的活动信息。在又一个示例中，用户可以选择限制维护用户活动信息的时间长度或者基于活动信息完全禁止开发使用模式。除了提供“选择加入”和“选择退出”选项外，本公开设想提供与访问或使用个人信息相关的通知。例如，可在下载应用时向用户通知其个人信息数据将被访问，然后就在个人信息数据被应用访问之前再次提醒用户。
此外，本公开的目的是应当管理和处理个人信息数据以使无意或未经授权访问或使用的风险最小化。一旦不再需要数据，通过限制数据采集和删除数据可最小化风险。此外，并且当适用时，包括在某些健康相关应用程序中，数据去标识可用于保护用户的隐私。在适当的情况下，可以通过移除特定标识符(例如，出生日期等)、控制存储的数据的量或特征(例如，在城市级而非地址级收集位置数据)、控制数据的存储方式(例如，在用户之间聚合数据)和/或其他方法来促进去标识。
因此，虽然本公开广泛地覆盖了使用个人信息数据来实现一个或多个各种所公开的实施方案，但本公开还预期各种实施方案也可在无需访问此类个人信息数据的情况下被实现。即，本发明技术的各种实施方案不由于缺少此类个人信息数据的全部或一部分而无法正常进行。例如，可基于非个人信息数据或最少量的个人信息(例如，由与用户相关联的设备所请求的内容、虚拟助理可用的其他非个人信息或公开可用信息)来估计用户话语指向虚拟助理的可能性。
Claims (31)
1.一种方法，包括：
在具有一个或多个处理器、存储器和麦克风的电子设备(900)处：
经由所述麦克风接收第一音频流，所述第一音频流包括一个或多个话语；
确定所述第一音频流是否包括词汇触发；
根据确定所述第一音频流包括所述词汇触发，生成所述一个或多个话语的一个或多个候选文本表示；
基于从所述电子设备的一个或多个传感器获得的感官数据和所述虚拟助理的使用模式，确定所述虚拟助理是否要忽略所述一个或多个候选文本表示的至少一个候选文本表示；
根据确定所述虚拟助理要忽略至少一个候选文本表示，基于除了要被忽略的所述至少一个候选文本表示之外的所述一个或多个候选文本表示的候选文本表示，生成一个或多个候选意图，其中生成所述一个或多个候选意图包括；
确定所述一个或多个候选意图是否包括至少一个可执行意图；
根据确定所述一个或多个候选意图包括至少一个可执行意图，执行所述至少一个可执行意图；
输出所述执行所述至少一个可执行意图的结果。
2.根据权利要求1所述的方法，其中所述词汇触发是单字词的词汇触发。
3.根据权利要求2所述的方法，其中所述第一音频流包括第一话语，并且其中所述单字词的词汇触发位于所述第一话语的除所述第一话语的所述开始部分之外的部分中。
4.根据权利要求1至2所述的方法，其中确定所述第一音频流是否包括词汇触发包括：
检测所述第一音频流的开始点；
检测所述第一音频流的结束点；以及
确定在所述第一音频流的所述开始点和所述结束点之间是否包括词汇触发。
5.根据权利要求4所述的方法，其中检测所述第一音频流的所述开始点包括：
经由所述麦克风检测到在接收到所述第一音频流之前没有语音活动；
确定在接收到所述第一音频流之前没有所述语音活动的时间是否超过第一阈值时间段；以及
根据确定没有所述语音活动的时间超过所述第一阈值时间段，基于在接收到所述第一音频流之前没有所述语音活动确定所述第一音频流的所述开始点。
6.根据权利要求4所述的方法，其中检测所述第一音频流的所述结束点包括：
经由所述麦克风检测在接收到所述第一音频流的所述一个或多个话语之后没有语音活动；
确定在接收到所述第一音频流的所述一个或多个话语之后没有所述语音活动的时间是否超过第二阈值时间段；以及
根据确定在接收到所述第一音频流的所述一个或多个话语之后没有所述语音活动的时间超过所述第二阈值时间段，基于在接收到所述第一音频流的所述一个或多个话语之后没有所述语音活动来确定所述第一音频流的所述结束点。
7.根据权利要求4所述的方法，其中检测所述第一音频流的所述结束点包括：
获取预先配置的持续时间，即所述电子设备被配置为接收所述第一音频流的时间；以及
基于检测到的所述第一音频流的所述开始点和预先配置的所述持续时间来确定所述第一音频流的所述结束点。
8.根据权利要求4所述的方法，其中检测所述第一音频流的所述结束点包括：
确定音频文件的大小，所述音频文件表示所接收的所述第一音频流的所述一个或多个话语；
将所述音频文件的所述大小与存储所述音频文件的缓冲器的容量进行比较；以及
基于将所述音频文件的所述大小与存储所述音频文件的所述缓冲器的所述容量进行比较的结果来确定所述第一音频流的所述结束点。
9.根据权利要求1至8所述的方法，其中所述第一音频流的所述一个或多个话语包括至少一个话语，所述至少一个话语不指向所述虚拟助理。
10.根据权利要求1至9所述的方法，其中生成所述一个或多个话语的一个或多个候选文本表示包括：
执行所述第一音频流的所述一个或多个话语中的每一个的语音到文本转换，以生成所述一个或多个候选文本表示；以及
确定对应于所述一个或多个候选文本表示的置信水平。
11.根据权利要求1至10所述的方法，其中确定所述虚拟助理是否要忽略所述一个或多个候选文本表示的所述至少一个候选文本表示包括：
确定所述至少一个候选文本表示是否包括所述词汇触发；以及
根据确定所述至少一个候选文本表示不包括所述词汇触发，估计对应于所述至少一个候选文本表示的所述话语不指向所述虚拟助理的可能性；以及
基于所估计的所述可能性，确定所述虚拟助理是否要忽略所述一个或多个候选文本表示的所述至少一个候选文本表示。
12.根据权利要求11所述的方法，其中估计对应于所述至少一个候选文本表示的所述话语不指向所述虚拟助理的所述可能性包括：
基于与时间相关联的所述虚拟助理的所述使用模式，估计对应于所述至少一个候选文本表示的所述话语不指向所述虚拟助理的所述可能性。
13.根据权利要求11所述的方法，其中估计对应于所述至少一个候选文本表示的所述话语不指向所述虚拟助理的所述可能性包括：
基于所述注视数据，估计对应于所述至少一个候选文本表示的所述话语不指向所述虚拟助理的所述可能性。
14.根据权利要求1至13所述的方法，其中基于除了要被忽略的所述至少一个候选文本表示之外的所述一个或多个候选文本表示的所述候选文本表示生成所述一个或多个候选意图包括：
获取对应于所述一个或多个话语的所述一个或多个候选文本表示的一个或多个预缓解意图；以及
从所述一个或多个预缓解意图选择对应于除了要被忽略的所述至少一个候选文本表示之外的所述一个或多个候选文本表示的所述一个或多个候选意图。
15.根据权利要求1至14所述的方法，其中确定所述一个或多个候选意图是否包括至少一个可执行意图包括：
对于所述一个或多个候选意图中的每一个，确定是否可以执行任务；以及
根据确定可以执行所述任务，确定所述一个或多个候选意图包括至少一个可执行意图。
16.根据权利要求15所述的方法，其中确定是否可以执行所述任务包括：
获取与所述虚拟助理的使用模式相关联的上下文信息；以及
基于与所述虚拟助理的所述使用模式相关联的所述上下文信息，确定是否可以执行所述任务。
17.根据权利要求15所述的方法，其中确定是否可以执行所述任务包括：
获取与所述虚拟助理执行的先前任务相关联的上下文信息；以及
基于与所述虚拟助理执行的所述先前任务相关联的所述上下文信息，确定是否可以执行所述任务。
18.根据权利要求15所述的方法，其中确定是否可以执行所述任务包括：
确定所述一个或多个候选文本表示之间的一个或多个关系；
确定是否可以基于所述一个或多个候选文本表示之间的所述一个或多个关系来执行所述任务。
19.根据权利要求15所述的方法，其中确定是否可以执行所述任务包括：
从通信地耦接到所述电子设备的一个或多个传感器获取感官数据；以及
确定是否可以基于所述感官数据执行所述任务。
20.根据权利要求15所述的方法，其中确定是否可以执行所述任务包括：
估计与执行所述任务相关联的置信水平；
确定与执行所述任务相关联的所述置信水平是否满足阈值置信水平；以及
根据确定的与执行所述任务相关联的所述置信水平满足所述阈值置信水平，确定可以执行所述任务。
21.根据权利要求1至20所述的方法，其中执行所述至少一个可执行意图包括：
根据所述至少一个可执行意图执行一个或多个任务。
22.根据权利要求1至21中任一项所述的方法，其中所述一个或多个候选意图包括多个可执行意图，并且其中执行所述至少一个可执行意图包括：
从与所述多个可执行意图相关联的多个任务中选择用于执行的第一任务；以及
执行所选择的所述第一任务。
23.根据权利要求22所述的方法，其中从与所述多个可执行意图相关联的所述多个任务中选择用于执行的所述第一任务包括：
获取与所述虚拟助理发起的最新任务相关联的上下文信息；以及
基于与所述虚拟助理执行的先前任务相关联的所述上下文信息来选择所述第一任务。
24.根据权利要求22所述的方法，其中从与所述多个可执行意图相关联的所述多个任务中选择用于执行的所述第一任务包括：
输出对应于与所述多个可执行意图相关联的所述多个任务的多个任务选项；
从所述多个任务选项接收用户选择；以及
基于所述用户选择来选择所述第一任务。
25.根据权利要求22所述的方法，其中从与所述多个可执行意图相关联的所述多个任务中选择用于执行的所述第一任务包括：
确定与所述多个任务中的每一个相关联的优先级；以及
基于与所述多个任务中的每一个相关联的所述优先级来选择用于执行的所述第一任务。
26.根据权利要求1至25所述的方法，其中所述一个或多个程序还包括用于执行以下操作的指令：
在执行所述至少一个可执行意图时，经由所述麦克风接收第二音频流；
生成一个或多个第二候选文本表示以表示所述第二音频流；
基于所述一个或多个第二候选文本表示，确定所述第二音频流是否是包括所述第一音频流的音频会话的一部分；
根据确定所述第二音频流是包括所述第一音频流的所述音频会话的一部分，基于所述一个或多个第二候选文本表示生成一个或多个第二候选意图；
确定所述一个或多个第二候选意图是否包括至少一个第二可执行意图；
根据确定所述一个或多个第二候选意图包括至少一个第二可执行意图，执行所述至少一个第二可执行意图；以及
输出所述执行所述至少一个第二可执行意图的结果。
27.根据权利要求26所述的方法，其中确定所述第二音频流是否是包括所述第一音频流的所述音频会话的一部分包括：
获取与执行所述至少一个可执行意图相关联的上下文信息；以及
基于与执行所述至少一个可执行意图相关联的所述上下文信息，确定所述第二音频流是否是包括所述第一音频流的所述音频会话的一部分。
28.根据权利要求26所述的方法，其中确定所述第二音频流是否是包括所述第一音频流的所述音频会话的一部分包括：
确定所述第一音频流和所述第二音频流的各个候选文本表示之间的关系；以及
基于所述第一音频流和所述第二音频流的各个候选文本表示之间的所述关系，确定所述第二音频流是否是包括所述第一音频流的所述音频会话的一部分。
29.根据权利要求1至28所述的方法，其中所述虚拟助理的所述使用模式与一天中的时间相关联。
30.一种电子设备(900)，包括：
一个或多个处理器；
存储器；以及
一个或多个程序，所述一个或多个程序被存储在所述存储器中，所述一个或多个程序包括用于执行根据权利要求1至29中任一项所述的方法的指令。
31.一种计算机可读存储介质，包括用于由电子设备的一个或多个处理器执行的一个或多个程序，所述一个或多个程序包括在由所述一个或多个处理器执行时使所述电子设备执行根据权利要求1至29中任一项所述的方法的指令。
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