CN107195306B - 识别提供凭据的语音输入 - Google Patents

识别提供凭据的语音输入 Download PDF

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CN107195306B
CN107195306B CN201710109781.1A CN201710109781A CN107195306B CN 107195306 B CN107195306 B CN 107195306B CN 201710109781 A CN201710109781 A CN 201710109781A CN 107195306 B CN107195306 B CN 107195306B
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character
word
utterance
user
speech input
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CN107195306A (zh
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M·艾克巴卡克
B·汉森
G·埃弗曼
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Apple Inc
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    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/26Speech to text systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31User authentication
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/10Text processing
    • G06F40/166Editing, e.g. inserting or deleting
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/20Natural language analysis
    • G06F40/279Recognition of textual entities
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/08Speech classification or search
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/08Speech classification or search
    • G10L15/18Speech classification or search using natural language modelling
    • G10L15/183Speech classification or search using natural language modelling using context dependencies, e.g. language models
    • G10L15/19Grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
    • G10L15/197Probabilistic grammars, e.g. word n-grams
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/22Procedures used during a speech recognition process, e.g. man-machine dialogue
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/24Speech recognition using non-acoustical features
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/28Constructional details of speech recognition systems
    • G10L15/30Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/08Speech classification or search
    • G10L2015/086Recognition of spelled words
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/22Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G10L2015/223Execution procedure of a spoken command

Abstract

本发明提供了用于识别提供一个或多个用户凭据的语音输入的系统和过程。在一个示例性过程中,可以接收语音输入。基于语音输入可识别第一字符、用于识别第二字符的短语、以及字词。响应于该识别,可将第一字符、第二字符和字词转换为文本。可使得利用显示器以对应于第一字符、第二字符和字词在语音输入中的次序的序列来显示文本。

Description

识别提供凭据的语音输入
相关申请的交叉引用
本申请要求2016年9月16日提交的标题为“IDENTIFICATION OF VOICE INPUTSPROVIDING CREDENTIALS”的美国专利申请序列号15/268,360的优先权,后者要求2016年3月14日提交的标题为“IDENTIFICATION OF VOICE INPUTS PROVIDING CREDENTIALS”的美国临时专利申请序列号62/308,090的优先权。这些专利申请中每一者的内容据此全文以引用方式并入以用于所有目的。
技术领域
本发明整体涉及语音识别,并且更具体地涉及识别提供凭据的语音输入。
背景技术
常规地,认证通常需要用户提供诸如用户名和密码的凭据。可以使用诸如计算机、平板电脑、移动设备、电视机、多媒体设备、机顶盒等设备来执行认证。语音识别越来越受到口述和控制设备的欢迎。凭据可以包括字符、字词、短语、命令等的混合。这种混合输入使得难以准确地识别用户语音。因此,需要增强使用语音的凭据的准确输入。
发明内容
提供了用于识别提供一个或多个凭据的语音输入的系统和过程。根据一个或多个实施例,一种方法包括在具有显示器、一个或多个处理器和存储器的用户设备处接收语音输入。该方法还包括基于该语音输入,识别第一字符、用于识别第二字符的短语,和字词。该方法还包括,响应于该识别,将所述第一字符、第二字符和字词转换为文本;以及使得利用所述显示器以对应于所述第一字符、第二字符和字词在所述语音输入中的次序的序列显示所述文本。
附图说明
为了更好地理解本发明的各种所描述的实施方案,应该结合以下附图参考下面的具体实施方式,在附图中,类似的附图标号指示所有附图中对应的部分。
图1是示出根据各种实施例的用于实现数字助理的系统和环境的框图。
图2A是示出根据一些实施方案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是示出根据各种实施例的用于事件处理的示例性部件的框图。
图3示出了根据各种实施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是根据各种实施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示出了根据各种实施例的便携式多功能设备上的应用程序菜单的示例性用户界面。
图5B示出了根据各种实施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示出了根据各种实施例的个人电子设备。
图6B是示出根据各种实施例的个人电子设备的框图。
图7A是示出根据各种实施例的数字助理系统或其服务器部分的框图。
图7B示出了根据各种实施例的图7A所示数字助理的功能。
图7C示出了根据各种实施例的知识本体的一部分。
图8A-图8B示出了根据各种实施例的设备的示例性架构的框图。
图9示出了根据各种实施例的示例性自动语音识别模块的框图。
图10A-图10F示出了根据各种实施例的用于输入凭据的语音输入识别功能。
图11A-图11D示出了根据各种实施例的用于输入凭据的语音输入识别功能。
图12A-图12D示出了根据各种实施例的用于识别语音输入的示例性过程的流程图。
图13示出了根据各种实施例的电子设备的框图。
具体实施方式
在以下对本公开和实施方案的描述中将引用附图,在附图中以举例的方式示出了可被实施的特定实施方案。应当理解,在不脱离本公开的范围的情况下,可实践其他实施方案和实施例并且可做出变化。
需要用于识别语音输入的技术。如本文所述,用于识别语音输入的技术被期望用于各种目的,例如输入通常包括字符、字词、短语和/或命令的混合的凭据。此类技术允许用户不用手就能输入凭据,因此是有利的。此外,此类用于识别语音输入的技术可以使用户不必用手向设备逐个字符地输入凭据或任何其他信息,这种手动操作可能是耗时而且繁琐的。
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,在不脱离各种所述实施例的范围的情况下,第一字符可以被称为第二字符,并且类似地,第二字符可以被称为第一字符。第一字符和第二字符可以都是字符,并且在一些情况下,可以是单独和不同的字符。
在本文中对各种所述实施例的描述中所使用的术语只是为了描述特定实施例的目的,而并非旨在进行限制。如在对各种所述实施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(“a”,“an”)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”(“includes”,“including”,“comprises”和/或“comprising”)当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”(“when”或“upon”)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示出了根据各种实施例的系统100的框图。在一些实施例中,系统100可实现数字助理。术语“数字助理”、“虚拟助理”、“智能自动化助理”或“自动数字助理”可指解译口头和/或文本形式的自然语言输入以推断用户意图,并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,为了按照推断出的用户意图来操作,系统可执行以下内容中的一个或多个:通过设计用以实现所推断出的用户意图的步骤和参数来识别任务流,将来自推断出的用户意图的具体要求输入到任务流中;通过调用程序、方法、服务、API等来执行任务流;以及生成对用户的听觉(例如,语音)和/或视觉形式的输出响应。
具体地讲,数字助理可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,用户请求可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。针对用户请求的令人满意的响应可以是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,用户可向数字助理提出诸如“我现在在哪里?”之类的问题。基于用户的当前位置,数字助理可回答“你在中央公园西门附近。”用户还可请求执行任务,例如“请邀请我的朋友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”来确认该请求,然后代表用户将合适的日历邀请发送到用户的电子通讯录中列出的用户朋友中的每个朋友。在执行所请求的任务期间,数字助理可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,数字助理还可提供其他视觉或声音形式的响应,例如,作为文本、警报、音乐、视频、动画等。
如图1所示,在一些实施例中,数字助理可根据客户端-服务器模型来实施。数字助理可以包括在用户设备104上执行的客户端侧部分102(后文称作“DA客户端102”)和在服务器系统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可通过一个或多个网络110与DA服务器106通信。DA客户端102可提供客户端侧功能诸如面向用户的输入和输出处理,并且与DA服务器106通信。DA服务器106可为任意数量的DA客户端102提供服务器侧功能,所述任意数量的DA客户端102各自位于相应的用户设备104上。
在一些实施例中,DA服务器106可包括面向客户端的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可促进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可以利用数据和模型116来处理语音输入,并且基于自然语言输入来确定用户的意图。此外,一个或多个处理模块114基于推断出的用户意图执行任务执行。在一些实施例中,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118的I/O接口可促进此类通信。
用户设备104可以是任何合适的电子设备。例如,用户设备可以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-图6B描述的设备600)。便携式多功能设备可以是例如还包含诸如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示例性实施例可包括得自加利福尼亚州库比蒂诺的苹果公司(Apple Inc.,Cupertino,California)的
Figure GDA0001314435430000051
iPod
Figure GDA0001314435430000052
Figure GDA0001314435430000053
设备。便携式多功能设备的其他实施例可以包括但不限于膝上型电脑或平板电脑。此外,在一些实施例中,用户设备104可以是非便携式多功能设备。具体地讲,用户设备104可以是台式计算机、游戏机、电视机或电视机顶盒。在一些实施例中,用户设备104可以包括触敏表面(例如触摸屏显示器和/或触控板)。此外,电子设备104可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。下面更详细地描述诸如多功能设备的电子设备的各种实施例。
一个或多个通信网络110的示例可包括局域网(LAN)和广域网(WAN),例如互联网。一个或多个通信网络110可使用任何已知的网络协议,包括各种有线或无线协议,诸如例如以太网、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来实施。
服务器系统108可在一个或多个独立式数据处理设备或计算机分布式网络上实施。在一些实施例中,服务器系统108还可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的基本计算资源和/或基础结构资源。
在一些实施例中,用户设备104可以经由第二用户设备122与DA服务器106通信。第二用户设备122可以与用户设备104相似或相同。例如,第二用户设备122可以类似于下面参考图2A、图4和图6A-图6B描述的设备200、400或600。用户设备104可以被配置为经由诸如蓝牙、NFC、BTLE等的直接通信连接或者经由诸如本地Wi-Fi网络的有线或无线网络通信地耦接到第二用户设备122。在一些实施例中,第二用户设备122可以被配置为充当用户设备104和DA服务器106之间的代理。例如,用户设备104的DA客户端102可以被配置为经由第二用户设备122向DA服务器106发送信息(例如,在用户设备104处接收到的用户请求)。DA服务器106可以处理该信息,并且经由第二用户设备122向用户设备104返回相关数据(例如,响应所述用户请求的数据内容)。
在一些实施例中,用户设备104可以被配置为向第二用户设备122传送缩减的数据请求,以减少从用户设备104发送的信息量。第二用户设备122可以被配置为确定要添加到所述缩减请求以生成发送到DA服务器106的完整请求的补充信息。该系统架构可以有利地允许具有有限通信能力和/或有限电池电量的用户设备104(例如手表或类似的紧凑型电子设备)通过使用具有更高通信能力和/或电池电量的第二用户设备122(例如移动电话、膝上型电脑、平板电脑等)作为DA服务器106的代理来访问由DA服务器106提供的服务。虽然图1中仅示出了两个用户设备104和122,应当理解,系统100可以包括在该代理配置中配置的任何数量和类型的用户设备以与DA服务器系统106通信。
尽管图1所示的数字助理可包括客户端侧部分(例如DA客户端102)和服务器侧部分(例如,DA服务器106)两者,但在一些实施例中,数字助理的功能可被实现为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,在一些实施例中,DA客户端可以是仅提供面向用户的输入和输出处理功能,且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
现在转为关注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是示出了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”,并且有时可被称为或被叫做“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任选地包括用于检测设备200(例如,触敏表面,诸如设备200的触敏显示器系统212)上的接触的强度的一个或多个接触强度传感器265。设备200任选地包括用于在设备200上生成触觉输出的一个或多个触觉输出发生器267(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的触摸板455上生成触觉输出)。这些部件任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被合并(例如,加权平均数)以确定估计的接触力。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面积的大小和/或其变化、接触附近触敏表面的电容和/或其变化,和/或接触附近触敏表面的电阻和/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超过强度阈值(例如,强度阈值是以与替代物测量对应的单位来描述的)。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的对触摸敏感的表面(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性的所感知的变化。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为或感测为触敏表面的“粗糙度”。虽然由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,但是存在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,“松开点击”、“按下点击”、“摩擦”)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)用户的所描述的感官知觉。
应当理解,设备200仅是便携式多功能设备的一个实施例,并且设备200任选地具有比所示出的更多或更少的部件,任选地组合两个或更多个部件,或者任选地具有这些部件的不同配置或布置。图2A中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电路和/或专用集成电路。
存储器202可包括一个或多个计算机可读存储介质。该计算机可读存储介质可以是有形的和非暂态的。存储器202可包括高速随机存取存储器并且还可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可控制设备200的其他部件访问存储器202。
在一些实施例中,存储器202的非暂态计算机可读存储介质可用于存储指令(例如用于执行下面描述的过程1200的各方面),这些指令供指令执行系统、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。在其他实施例中,(例如用于执行下面描述的过程1200的各方面)的指令可被存储在服务器系统108的非暂态计算机可读存储介质(未示出)上,或者可以在存储器202的非暂态计算机可读存储介质和服务器系统108的非暂态计算机可读存储介质之间划分。在本文的语境中,“非暂态计算机可读存储介质”可以是可包括或存储程序以供指令执行系统、装置和设备使用或与其结合的任何介质。
外围设备接口218可被用于将设备的输入外围设备和输出外围设备耦接到CPU220和存储器202。所述一个或多个处理器220运行或执行存储在存储器202中的各种软件程序和/或指令集以执行设备200的各种功能并处理数据。在一些实施例中,外围设备接口218、CPU 220、和存储器控制器222可在单个芯片诸如芯片204上实现。在一些其他实施例中,它们可在单独的芯片上实现。
RF(射频)电路208接收和发送也被叫做电磁信号的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,并且经由电磁信号来与通信网络以及其他通信设备进行通信。RF电路208任选地包括用于执行这些功能的熟知的电路,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任选地通过无线通信来与网络以及其他设备进行通信,该网络为诸如互联网(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任选地包括用于检测近场通信(NFC)场的熟知的电路,诸如通过近程通信无线电部件来进行检测。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通信标准、协议和技术,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+、双单元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、无线保真(Wi-Fi)(例如,IEEE 802.11a、IEEE 802.11b、IEEE 802.11g、IEEE 802.11n和/或IEEE 802.11ac)、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),或者包括在本文档提交日期时还未开发出的通信协议的任何其他适当的通信协议。
音频电路210、扬声器211和麦克风213提供用户和设备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见的声波。音频电路210还接收由麦克风213根据声波转换的电信号。音频电路210将电信号转换为音频数据,并将音频数据传输到外围设备接口218以用于处理。音频数据可由外围设备接口218从存储器202和/或RF电路208进行检索和/或被传输至所述存储器和/或RF电路。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)。耳麦插孔提供音频电路210和可移除的音频输入/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耦接至外围设备接口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/将电信号发送到其他输入控制设备116。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、点击式转盘等等。在一些另选的实施方案中,一个或多个输入控制器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,以及指针设备诸如鼠标。一个或多个按钮(例如,图3中的308)任选地包括用于扬声器211和/或麦克风213的音量控制的增大/减小按钮。一个或多个按钮任选地包括下压按钮(例如,图3中的306)。
快速按下下压按钮可解除触摸屏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,如在于2005年12月23日提交的标题为“Unlocking a Device byPerforming Gestures on an Unlock Image”的美国专利申请11/322,549以及美国专利申请7,657,849中所述的,上述美国专利申请据此全文以引用方式并入本文。更长地按下下压按钮(例如306)可使设备200开机或关机。用户能够对一个或多个按钮的功能进行自定义。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/或将电信号发送至触摸屏112。触摸屏212向用户显示视觉输出。该视觉输出可包括图形、文本、图标、视频及它们的任意组合(统称为“图形”)。在一些实施方案中,一些视觉输出或全部的视觉输出可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。在一个示例性实施方案中,触摸屏212和用户之间的接触点对应于用户的手指。
触摸屏212可使用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,但是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可使用现在已知的或以后将开发出的多种触摸感测技术中的任何触摸感测技术以及其他接近传感器阵列或用于确定与触摸屏212的一个或多个接触点的其他元件来检测接触及其任何移动或中断,该多种触摸感测技术包括但不限于电容性技术、电阻性技术、红外技术和表面声波技术。在一个示例性实施方案中,使用投射式互电容感测技术,诸如在Apple Inc.(Cupertino,California)的
Figure GDA0001314435430000111
和iPod
Figure GDA0001314435430000112
发现的技术。
触摸屏212的一些实施方案中的触敏显示器可类似于以下美国专利中所述的多点触敏触摸板: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,这些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。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。
触摸屏212的一些实施方案中的触敏显示器可如在以下专利申请中那样进行描述:(1)于2006年5月2日提交的标题为“Multipoint Touch Surface Controller”美国专利申请11/381,313;(2)于2004年5月6日提交的标题为“Multipoint Touchscreen”美国专利申请10/840,862;(3)于2004年7月30日提交的标题为“Gestures For Touch SensitiveInput Devices”美国专利申请10/903,964;(4)于2005年1月31日提交的标题为“GesturesFor Touch Sensitive Input Devices”美国专利申请11/048,264;(5)于2005年1月18日提交的标题为“Mode-Based Graphical User Interfaces For Touch Sensitive InputDevices”美国专利申请11/038,590;(6)于2005年9月16日提交的标题为“Virtual InputDevice Placement On A Touch Screen User Interface”美国专利申请11/228,758;(7)于2005年9月16日提交的标题为“Operation Of A Computer With A Touch ScreenInterface”美国专利申请11/228,700;(8)于2005年9月16日提交的标题为“ActivatingVirtual Keys Of A Touch-Screen Virtual Keyboard”美国专利申请11/228,737;和(9)于2006年3月3日提交的标题为“Multi-Functional Hand-Held Device”美国专利申请11/367,749。所有这些专利申请全文以引用方式并入本文。
触摸屏212可具有超过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。用户可使用任何合适的对象或附加物诸如触笔、手指等等来与触摸屏212接触。在一些实施方案中,用户界面被设计用于主要与基于手指的接触和手势工作,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翻译为精确的指针/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可包括用于激活或去激活特定功能的触摸板(未示出)。在一些实施方案中,触摸板是设备的触敏区域,该触敏区域与触摸屏不同,其不显示视觉输出。触摸板可以是与触摸屏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部分。
设备200还包括用于为各种部件供电的电力系统262。电力系统262可包括电力管理系统、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、功率变换器或逆变器、电源状态指示器(例如,发光二极管(LED))和与便携式设备中的电力的生成、管理和分配相关联的任何其他部件。
设备200还可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可包括电荷耦合器件(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(也称为相机模块),光学传感器264可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的与设备的前部上的触摸屏显示器212相背对的后部上,使得触摸屏显示器可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可获取该用户的图像,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可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、电气式力传感器、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的与位于设备200的前部上的触摸屏显示器212相背对的后部上。
设备200还可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可耦接至I/O子系统206中的输入控制器260。接近传感器266可如以下美国专利申请中所述的那样执行:11/241,839,名称为“ProximityDetector In Handheld Device”;11/240,788,名称为“Proximity Detector In HandheldDevice”;11/620,702,名称为“Using Ambient Light Sensor To Augment ProximitySensor Output”;11/586,862,名称为“Automated Response To And Sensing Of UserActivity In Portable Devices”;以及11/638,251,名称为“Methods And Systems ForAutomatic 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任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、电活性聚合物、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,并且任选地通过垂直地(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的与位于设备200的前部上的触摸屏显示器212相背对的后部上。
设备200还可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可耦接至I/O子系统206中的输入控制器260。加速度计268可如以下美国专利公开中所述的那样执行:20050190059,名称为“Acceleration-based Theft Detection System for Portable Electronic Devices”和20060017692,名称为“Methods And Apparatuses For Operating A Portable Device Based On AnAccelerometer”,这两个美国专利公开均全文以引用方式并入本文。在一些实施方案中,基于对从该一个或多个加速度计所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任选地除了一个或多个加速度计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,被存储在存储器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可存储数据和模型,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中所示的。设备/全局内部状态257包括以下各项中的一者或多者:活动应用程序状态,该活动应用程序状态用于指示哪些应用程序(如果有的话)当前是活动的;显示状态,该显示状态用于指示什么应用程序、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,该传感器状态包括从设备的各个传感器和输入控制设备216获得的信息;和关于设备位置和/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、功率管理等)的各种软件部件和/或驱动程序,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,并且还包括用于处理由RF电路208和/或外部端口224所接收的数据的各种软件部件。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)耦接。在一些实施方案中,外部端口是与
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(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)、确定接触的强度(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者接触断开)。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),该接触点的移动由一系列接触数据来表示。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和显示器控制器256检测触控板上的接触。
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,强度阈值不是由特定物理致动器的激活阈值来确定的,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接触图案(例如,所检测到的接触的不同运动、计时和/或强度)。因此,任选地通过检测具体接触图案来检测手势。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包括用于在触摸屏212或其他显示器上呈现和显示图形的各种已知的软件部件,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,包括但不限于文本、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存储待使用的用于表示图形的数据。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包括用于生成指令的各种软件部件,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。
可作为图形模块232的部件的文本输入模块234提供用于在多种应用程序(例如,联系人237、电子邮件240、即时消息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这种信息以在各种应用程序中使用(例如,提供至用于基于位置的拨号的电话238;提供至相机243作为图片/视频元数据;以及提供至提供基于位置的服务诸如天气桌面小程序、当地黄页桌面小程序和地图/导航桌面小程序的应用程序)。
数字助理客户端模块229可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可能够通过便携式多功能设备200的各种用户界面(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也能够通过便携式多功能设备200的各种输出界面(例如,扬声器211、触敏显示器系统212、触觉输出发生器267等)提供音频形式输出(例如,语音输出)、视觉形式输出和/或触觉形式输出。例如,可将输出提供为语音、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可利用RF电路208与DA服务器106通信。
用户数据与模型231可包括与用户相关联的各种数据(例如,用户特定词汇数据、用户偏好数据、用户指定名称发音、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可包括各种模型(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确定用户意图。
在一些实施例中,数字助理客户端模块229可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。在一些实施例中,数字助理客户端模块229可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以帮助推断用户的意图。在一些实施例中,数字助理还可使用上下文信息来确定如何准备输出并将其传送至用户。上下文信息可被称为上下文数据。
在一些实施例中,伴随用户输入的上下文信息可包括传感器信息,例如照明、环境噪声、环境温度、周围环境的图像或视频等。在一些实施例中,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。在一些实施例中,还可将与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。
在一些实施例中,数字助理客户端模块229可响应于来自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)。在一些实施例中,数字助理客户端模块229还可在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界面的附加输入。数字助理客户端模块229可将所述附加输入传送至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。
数字助理的更详细描述在下文参考图7A-图7C描述。应认识到,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的任何数量的子模块。
应用程序236可包括以下模块(或指令集),或者其子集或超集:
·联系人模块237(有时叫做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,其可包括以下各项中的一者或多者: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、词典桌面小程序249-5、和由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。
可被存储在存储器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、数字权益管理、语音识别、和语音复制。
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可用于管理地址簿或联系人列表(例如,被存储在存储器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地址簿;从地址簿删除一个或多个姓名;使一个或多个电话号码、一个或多个电子邮件地址、一个或多个物理地址或其他信息与姓名相关联;使图像与姓名相关联;对姓名归类和分类;提供电话号码或电子邮件地址以发起和/或促进通过电话238、视频会议模块239、电子邮件240、或IM 241进行通信;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可用于输入与电话号码对应的字符序列、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,无线通信可使用多个通信标准、协议和技术中的任一者。
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,所传输的和/或所接收的即时消息可包括图形、照片、音频文件、视频文件和/或在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传输的消息)和基于互联网的消息(例如,使用XMPP、SIMPLE、或IMPS传输的消息)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包括用于以下操作的可执行指令: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(移动设备)进行通信;接收健身传感器数据;校准用于监测健身的传感器;选择健身音乐并进行播放;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、一个或多个光学传感器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性、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包括用于排列、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,浏览器模块247包括用于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)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、电子邮件客户端模块240和浏览器模块247,日历模块248包括用于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、和字典桌面小程序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可由用户用于创建桌面小程序(例如,将网页的用户指定部分转到桌面小程序中)。
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包括用于根据用户指令来搜索存储器202中的匹配一个或多个搜索条件(例如,一个或多个用户指定的搜索词)的文本、音乐、声音、图像、视频和/或其他文件的可执行指令。
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可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包括指令,所述指令允许用户访问、浏览、(例如,通过流式传输和/或下载)接收、(例如,在触摸屏上或在经由外部端口224连接的外部显示器上)回放、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。在一些实施方案中,即时消息模块241而不是电子邮件客户端模块240被用于发送至特定的在线视频的链接。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可存储上述模块和数据结构的子集。此外,存储器202可存储上文没有描述的附加模块和数据结构。
在一些实施方案中,设备200是唯一地通过触摸屏和/或触控板来执行设备上的预定义的一组功能的操作的设备。通过使用触摸屏和/或触摸板作为用于设备200的操作的主要输入控制设备,可减少设备200上的物理输入控制设备(诸如下压按钮、拨号盘等等)的数量。
唯一地通过触摸屏和/或触摸板执行的该预定义的一组功能任选地包括在用户界面之间进行导航。在一些实施方案中,触控板在被用户触摸时将设备200从被显示在设备200上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237-251、255、480-490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用于确定哪个(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用于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包括另外的信息,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、指示正被应用程序236-1显示的信息或准备好用于被该应用程序显示的信息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,以及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,作为多点触摸手势的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、一个或多个加速度计268和/或麦克风213(通过音频电路210))所接收的信息。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。视图由用户可在显示器上查看的控件和其他元件构成。
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)应用程序视图可对应于应用程序的程序化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任选地被叫做命中视图,并且被识别为正确输入的那组事件至少部分地基于开始基于触摸的手势的初始触摸的命中视图来确定。
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将命中视图识别为该分级结构中应当处理该子事件的最低视图。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确定仅命中视图才应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都是活跃参与的视图,因此确定所有活跃参与的视图都应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,但在分级结构中较高的视图将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。作为另外一种选择,应用程序236-1包括事件分类器270。在其他实施方案中,事件分类器270是独立的模块,或者是被存储在存储器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,其中每个应用程序视图包括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的指令。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更高水平的对象。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所接收的事件数据279。事件处理程序290可利用或调用数据更新器276、对象更新器277或GUI更新器278,以更新应用程序内部状态292。作为另外一种选择,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中的一者或多者被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还至少包括以下各项的子集:元数据283,和事件递送指令288(其可包括子事件递送指令)。
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的信息,例如触摸或触摸移动。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,事件信息还可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个取向(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,并且基于比较结果,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中的子事件包括例如触摸开始、触摸结束、触摸移动、触摸取消和多点触摸。在一个实施例中,事件1(287-1)的定义是在所显示对象上的双击。例如,双击包括被显示对象上的预先确定时长的第一次触摸(触摸开始)、预先确定时长的第一次抬起(触摸结束)、被显示对象上的预先确定时长的第二次触摸(触摸开始)以及预先确定时长的第二次抬起(触摸结束)。在另一个示例中,事件2(287-2)的定义是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、以及触摸的抬起(触摸结束)。在一些实施方案中,事件还包括用于一个或多个相关联的事件处理程序290的信息。
在一些实施方案中,事件定义287包括用于相应用户界面对象的事件的定义。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,在应用程序视图(其中在触摸显示器212上显示三个用户界面对象)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哪一个与触摸(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应当被激活。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,该延迟动作延迟事件信息的递送,直到已确定子事件序列是否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)继续跟踪和处理持续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该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包括用于指示事件识别器彼此如何交互或可如何交互的可配置属性、标志和/或列表。在一些实施方案中,元数据283包括用于指示子事件是否被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、标记和/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激活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将与该事件相关联的事件信息递送到事件处理程序290。激活事件处理程序290不同于将子事件发送(和延期发送)到相应的命中视图。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的过程。
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激活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串相关联的事件处理程序或递送到活跃参与的视图。与子事件串或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创建和更新在应用程序236-1中使用的数据。例如,数据更新器276对联系人模块237中所使用的电话号码进行更新,或者对视频播放器模块中所使用的视频文件进行存储。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准备显示信息并将其发送至图形模块232以用于显示在触敏显示器上。
在一些实施方案中,一个或多个事件处理程序290包括数据更新器276、对象更新器277和GUI更新器278或者具有对该数据更新器、该对象更新器和该GUI更新器的访问权限。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讨论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压或保持结合的鼠标移动和鼠标按钮按压;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;所检测到的眼睛移动;生物特征输入;和/或作为与子事件对应的输入的用于定义要识别的事件其任意的组合。
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。触摸屏任选地在用户界面(UI)300内显示一个或多个图形。在本实施方案中以及在下文中描述的其他实施方案中,用户能够通过例如利用一个或多个手指302(在附图中没有按比例绘制)或者利用一个或多个触笔303(在附图中没有按比例绘制)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会选择图形。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会选择相应应用程序。
设备200还可包括一个或多个物理按钮,诸如“home”按钮或菜单按钮304。如前所述,菜单按钮304可被用于导航到可在设备200上执行的应用程序集中的任何应用程序236。另选地,在一些实施方案中,菜单按钮被实现为被显示在触摸屏212上的GUI中的软键。
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被任选地用于:通过按下按钮并使按钮在下压状态保持预先确定的时间间隔来使设备通电/断电;通过按下按钮并在经过预先确定的时间间隔之前释放按钮来锁定设备;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来接受用于激活或去激活某些功能的语音输入。设备200还任选地包括用于检测触摸屏212上的接触的强度的一个或多个接触强度传感器265,和/或用于为设备200的用户生成触觉输出的一个或多个触觉输出发生器267。
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是膝上型计算机、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任选地包括使系统部件互连并且控制系统部件之间的通信的电路系统(有时叫做芯片组)。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和触摸板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任选地包括远离一个或多个CPU 410定位的一个或多个存储设备。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中所存储的程序、模块和数据结构类似的程序、模块以及数据结构,或者它们的子集。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个元件可被存储在一个或多个前面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)不必被实现为单独的软件程序、过程或模块,并且因此这些模块的各种子集可在各种实施方案中被组合或以其他方式重新布置。在一些实施方案中,存储器470可存储上述模块和数据结构的子集。此外,存储器470可存储上文没有描述的附加模块和数据结构。
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。类似的用户界面可在设备400上实现。在一些实施方案中,用户界面500包括以下元素或者其子集或超集:
一种或多种无线通信(诸如蜂窝信号和Wi-Fi信号)的一个或多个信号强度指示器502;
·时间504;
·蓝牙指示器505;
·电池状态指示器506;
·具有常用应用程序图标的托盘508,图标诸如:
○电话模块238的被标记为“电话”的图标516,该图标任选地包括未接来电或语音留言的数量的指示器514;
○电子邮件客户端模块240的被标记为“邮件”的图标518,该图标任选地包括未读电子邮件的数量的指示器510;
○浏览器模块247的被标记为“浏览器”的图标520;和
○视频和音乐播放器模块252(也称为iPod(Apple Inc.的商标)模块252)的被标记为“iPod”的图标522;以及
·其他应用程序的图标,诸如:
○IM模块241的被标记为“消息”的图标524;
○日历模块248的被标记为“日历”的图标526;
○图像管理模块244的被标记为“照片”的图标528;
○相机模块243的被标记为“相机”的图标530;
○在线视频模块255的被标记为“在线视频”的图标532;
○股市桌面小程序249-2的被标记为“股市”的图标534;
○地图模块254的被标记为“地图”的图标536;
○天气桌面小程序249-1的被标记为“天气”的图标538;
○闹钟桌面小程序249-4的被标记为“时钟”的图标540;
○健身支持模块242的被标记为“健身支持”的图标542;
○记事本模块253的被标记为“记事本”的图标544;和
○用于设置应用程序或模块的被标记为“设置”的图标546,该图标提供对设备200及其各种应用程序236的设置的访问。
应当指示的是,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可任选地被标记为“音乐”或“音乐播放器”。其他标签任选地用于各种应用程序图标。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的平板电脑或触摸板455)的设备(例如,图4的设备400)上的示例性用户界面。设备400还任选地包括用于检测触敏表面551上的接触的强度的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),和/或用于为设备400的用户生成触觉输出的一个或多个触觉输出发生器459。
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(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以及它们的移动)被该设备用于操控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)来替代。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,而不是对接触的检测,之后是终止检测接触)来替代。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可包括针对设备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具有在下文中称为触摸屏604的触敏显示屏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)可具有用于检测所施加的接触(例如,触摸)的强度的一个或多个强度传感器。触摸屏604(或触敏表面)的一个或多个强度传感器可提供表示触摸的强度的输出数据。设备600的用户界面可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。
例如,可在如下相关专利申请中找到用于检测和处理触摸强度的技术:于2013年5月8日提交的名称为“Device,Method,and Graphical User Interface for DisplayingUser Interface Objects Corresponding to an Application”的国际专利申请序列号PCT/US2013/040061,以及于2013年11月11日提交的名称为“Device,Method,andGraphical User Interface for Transitioning Between Touch Input to DisplayOutput Relationships”的国际专利申请序列号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)可以是物理形式的。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)可允许将设备600与例如帽子、眼镜、耳环、项链、衬衣、夹克、手镯、表带、手链、裤子、皮带、鞋子、钱包、背包等附接。这些附接机构可允许用户穿戴设备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可包括参考图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可连接到显示器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可与通信单元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可包括输入机构606和/或608。例如,输入机构606可以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可以是按钮。
在一些示例中,输入机构608可以是麦克风。个人电子设备600可包括各种传感器,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可以是用于存储计算机可执行指令的非暂态计算机可读存储介质,该计算机可执行指令在由一个或多个计算机处理器616执行时例如可使得计算机处理器执行下文描述的技术,包括过程1200(图12A-图12D)。该计算机可执行指令也可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。对于本文的目的而言,“非暂态计算机可读存储介质”可以是可有形地包含或存储计算机可执行指令以供指令执行系统、装置和设备使用或与其结合的任何介质。非暂态计算机可读存储介质可包括但不限于磁存储器、光学存储器和/或半导体存储器。此类存储器的示例包括磁盘、基于光盘的CD、DVD或Blu-ray技术,以及持久性固态存储器诸如闪存、固态驱动器等。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”是指可在设备200、设备400和/或设备600(图2、图4和图6)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,链接)可各自构成示能表示。
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,触摸屏上的所检测到的接触充当“焦点选择器”,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,焦点选择器根据用户界面的不同区域之间的焦点移动而移动。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激活相应按钮(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“特性强度”这一术语是指基于接触的一个或多个强度的接触特征。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,在检测到接触抬起之前,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可包括第一强度阈值和第二强度阈值。在该实施例中,特性强度未超过第一阈值的接触导致第一操作,特性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,而特性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,使用特性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性强度。例如,触敏表面可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。在该实施例中,接触在结束位置处的特性强度可仅基于连续轻扫接触的一部分,而不是整个轻扫接触(例如,仅结束位置处的轻扫接触的一部分)。在一些实施方案中,可在确定接触的特性强度之前向轻扫手势的强度应用平滑化算法。例如,该平滑化算法任选地包括以下各项中的一者或多者: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,以实现确定特性强度的目的。
可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控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,当检测到特性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,比该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,而无需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。
接触的特性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起。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。
为了便于解释,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:接触的强度增大到高于按压输入强度阈值、接触的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、接触的强度减小到低于按压输入强度阈值,和/或接触的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实施例中,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示出了根据各种实施例的数字助理系统700的框图。在一些实施例中,数字助理系统700可在独立式计算机系统上实现。在一些实施例中,数字助理系统700可跨多个计算机分布。在一些实施例中,数字助理的模块和功能中的一些可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。在一些实施例中,数字助理系统700可以是图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实施例,且该数字助理系统700可具有比所示更多或更少的部件、可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中所示的各种部件可在硬件、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)或者它们的组合中实现。
数字助理系统700可包括存储器702、一个或多个处理器704、输入/输出(I/O)接口706以及网络通信接口708。这些部件可通过一条或多条通信总线或者信号线710彼此通信。
在一些实施例中,存储器702可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)。
在一些实施例中,I/O接口706可将数字助理系统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,可接收用户输入(例如,声音输入、键盘输入、触摸输入等)并相应地对这些输入进行处理。在一些实施例中,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可包括相对于图2A、图4、图6A-图6B中各自的设备200、设备400或设备600所描述的部件和I/O通信接口中的任一者。在一些实施例中,数字助理系统700可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。
在一些实施例中,网络通信接口708可包括一个或多个有线通信端口712,以及/或者无线传输和接收电路714。一个或多个有线通信端口可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可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。无线通信可使用多种通信标准、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可使数字助理系统700通过网络,诸如互联网、内联网以及/或者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。
在一些实施例中,存储器702或存储器702的计算机可读存储介质可存储程序、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。具体而言,存储器702或存储器702的计算机可读存储介质可存储用于执行下文描述的过程1200的指令。一个或多个处理器704可执行这些程序、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或者嵌入式操作系统诸如VxWorks)可包括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、功率管理等)的各种软件组件和/或驱动器,并且有利于各种硬件、固件与软件部件之间的通信。
通信模块720可促进数字助理系统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可与电子设备的RF电路208通信,诸如,分别在图2A、图4、图6A-图6B中示出的设备200、设备400和设备600。通信模块720还可包括各种部件,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可经由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还可准备输出(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、扬声器和触控板等)传送至用户。
应用程序724可包括被配置为由一个或多个处理器704执行的程序和/或模块。例如,如果数字助理系统在独立式用户设备上实现,则应用程序724可包括用户应用程序,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可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还可存储数字助理模块726(或数字助理的服务器部分)。在一些实施例中,数字助理模块726可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可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。
在一些实施例中,使用在数字助理模块726中实现的处理模块、数据和模型,数字助理可执行以下内容中的至少一些:将语音输入转换成文本;识别从用户接收的自然语言输入中表达的用户的意图;主动引出并获得充分推断用户意图所需的信息(例如,通过消除字词、游戏、意向等的歧义);确定用于实现推断出的意图的任务流;以及执行任务流以实现推断出的意图。
在一些实施例中,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,以获得用户输入(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可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。上下文信息可包括用户特定的数据、词汇和/或与用户输入相关的偏好。在一些实施例中,上下文信息还包括在接收到用户请求时用户设备的软件和硬件状态,和/或与在接收到用户请求时用户周围环境相关的信息。在一些实施例中,I/O处理模块728还可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接收且用户请求可包括语音输入时,I/O处理模块728可将语音输入转发至STT处理模块730(或语音识别器)以进行语音文本转换。
STT处理模块730可包括一个或多个ASR系统。一个或多个ASR系统可处理通过I/O处理模块728接收到的语音输入,以产生识别结果。每个ASR系统可包括前端语音预处理器。前端语音预处理器可从语音输入中提取代表性特征。例如,前端语音预处理器可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。此外,每个ASR系统可包括一个或多个语音识别模型(例如,声音模型和/或语言模型),并且可实现一个或多个语音识别引擎。语音识别模型的示例可包括隐马尔可夫模型、高斯混合模型、深层神经网络模型、n元语言模型以及其他统计模型。语音识别引擎的示例可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。一个或多个语音识别模型和一个或多个语音识别引擎可用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、字词串或符号的序列)。在一些实施例中,语音输入可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,或符号的序列)的识别结果,识别结果即可被传送至自然语言处理模块732以供意图推断。图9中更详细地描述了示例性ASR系统。
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。
在一些实施例中,STT处理模块730可包括可识别字词的词汇和/或可经由语音字母转换模块731访问该词汇。每个词汇字词可与以语音识别语音字母表示的字词的一个或多个候选发音相关联。具体而言,所述可识别字词的词汇可包括与多个候选发音相关联的字词。例如,该词汇可包括与
Figure GDA0001314435430000411
Figure GDA0001314435430000412
的候选发音相关联的字词“tomato”。此外,词汇字词可与基于先前来自用户的语音输入的自定义候选发音相关联。此类自定义候选发音可存储在STT处理模块730中,并且可经由设备上的用户配置文件而与特定用户相关联。在一些实施例中,字词的候选发音可基于字词的拼写以及一个或多个语言学和/或语音学规则进行确定。在一些实施例中,候选发音可手动生成,例如,基于已知的标准发音而手动生成。
在一些实施例中,候选发音可基于候选发音的普通性来排名。例如,候选发音
Figure GDA0001314435430000413
可比
Figure GDA0001314435430000414
排名更高,因为(例如,在所有用户中,对于特定地理区域的用户而言,或者对于任何其他合适的用户子集而言)前者是更常用的发音。在一些实施例中,候选发音可基于候选发音是不是与用户相关联的自定义候选发音来排名。例如,自定义候选发音可比标准候选发音排名更高。这可用于识别具有偏离标准发音的独特发音的专有名词。在一些实施例中,候选发音可与一个或多个语音特征相关联,诸如地理起源、国家或种族。例如,候选发音
Figure GDA0001314435430000415
可与美国相关联,而候选发音
Figure GDA0001314435430000416
可与英国相关联。此外,候选发音的排名可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用户与美国相关联。基于用户与美国相关联,候选发音
Figure GDA0001314435430000418
(与美国相关联)可比候选发音
Figure GDA0001314435430000417
(与英国相关联)排名更高。在一些实施例中,排名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可被用来(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可首先识别对应于该语音输入的一部分的音素序列
Figure GDA0001314435430000421
那么它随后可基于词汇索引744确定该序列对应于字词“tomato”。
在一些实施例中,STT处理模块730可使用模糊匹配技术来确定语音输入中的字词。因此,例如,STT处理模块730可确定音素序列
Figure GDA0001314435430000422
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”)可取得由STT处理模块730生成的字词或符号的序列(“符号序列”),并尝试将该符号序列与由数字助理所识别的一个或多个“可执行意图”相关联。“可执行意图”可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。相关联的任务流可以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可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可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。
在一些实施例中,除从STT处理模块730获得的字词或符号的序列之外,自然语言处理器732还可(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可任选地使用上下文信息来明确、补充和/或进一步定义在从STT处理模块730接收的符号序列中包含的信息。上下文信息可包括例如: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。如本文中所述,上下文信息可以是动态的,并且可随对话的时间、位置、内容以及其他因素而变化。
在一些实施例中,自然语言处理可以是基于例如知识本体760进行的。知识本体760可以是包含许多节点的分级结构,每个节点表示“可执行意图”或者与“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”可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”可表示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中的可执行意图节点与属性节点之间的连接可定义由属性节点表示的参数如何与由可执行意图节点表示的任务相关。
在一些实施例中,知识本体760可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可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,每个属性节点可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可执行意图节点。例如,如图7C所示,知识本体760可包括“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“同行人数”均可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”可以是属性节点“餐厅”的子节点,并且均可通过中间属性节点“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还可包括“设定提醒”节点(即,另一可执行意图节点)。属性节点“日期/时间”(针对设定提醒)和“主题”(针对提醒)均可连接至“设定提醒”节点。由于属性“日期/时间”可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”可连接至知识本体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,可被描述为“域”。在本讨论中,每个域可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(以及其间的关系)。例如,图7C中示出的知识本体760可包括在知识本体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“同行人数”以及子属性节点“菜系”、“价格区间”、“电话号码”和“位置”。提醒域764可包括可执行意图节点“设置提醒”和属性节点“主题”和“日期/时间”。在一些实施例中,知识本体760可由多个域组成。每个域可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”属性节点还可与许多不同域(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,但其他域可包括例如“找一部电影”、“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”域可与“发送消息”可执行意图节点相关联,并且还可包括属性节点诸如“一个或多个接收人”、“消息类型”和“消息正文”。属性节点“接收人”可进一步例如由子属性节点诸如“接收人姓名”和“消息地址”来定义。
在一些实施例中,知识本体760可包括数字助理能够理解并对其起作用的所有域(以及因此可执行的意图)。在一些实施例中,知识本体760可诸如通过添加或移除整个域或节点或者通过修改知识本体760内节点之间的关系来修改。
在一些实施例中,可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”超级域可包括与旅行有关的属性节点和可执行意图节点的群集。与旅行有关的可执行意图节点可包括“机票预订”、“酒店预订”、“汽车租赁”、“路线规划”、“寻找兴趣点”等。同一超级域(例如,“旅行”超级域)下的可执行意图节点可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“寻找兴趣点”的可执行意图节点可共享属性节点“起始位置”、“目的地”、“出发日期/时间”、“到达日期/时间”和“同行人数”中的一者或多者。
在一些实施例中,知识本体760中的每个节点可与跟由节点表示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/或短语可以是所谓的与节点相关联的“词汇”。与每个节点相关联的相应组的字词和/或短语可被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可包括字词,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可包括字词和短语,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可任选地包括不同语言的字词和短语。
自然语言处理模块732可从STT处理模块730接收符号序列(例如,文本串),并确定符号序列中的字词牵涉哪些节点。在一些实施例中,如果发现符号序列中的字词或短语与知识本体760中的一个或多个节点相关联(经由词汇索引744),则所述字词或短语可“触发”或“激活”这些节点。基于已激活节点的数量和/或相对重要性,自然语言处理模块732可选择可执行意图中的一个可执行意图作为用户意图使数字助理执行的任务。在一些实施例中,可选择具有最多“已触发”节点的域。在一些实施例中,可(例如,基于其各个已触发节点的相对重要性)选择具有最高置信度的域。在一些实施例中,可基于已触发节点的数量和重要性的组合来选择域。在一些实施例中,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可包括用户特定的信息,诸如用户特定的词汇、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,以及每位用户的其他短期或长期信息。在一些实施例中,自然语言处理模块732可使用用户特定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聚会”,自然语言处理模块732可能够访问用户数据748以确定“朋友”是哪些人以及“生日聚会”将于何时何地举行,而不需要用户在其请求中明确地提供此类信息。
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。
在一些实施例中,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便可生成结构化查询以表示所识别的可执行意图。在一些实施例中,结构化查询可包括域内针对可执行意图的一个或多个节点的参数,并且所述参数中的至少一些填充有在用户请求中指定的特定信息和要求。例如,用户可说“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可能够基于用户输入将可执行意图正确地识别为“餐厅预订”。根据知识主体,“餐厅预订”域的结构化查询可包括参数诸如{菜系}、{时间}、{日期}、{同行人数}等。在一些实施例中,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可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,在该实施例中,用户的语音输入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,在结构化查询中可能未指定其他必要参数,诸如{同行人数}和{日期}。在一些实施例中,自然语言处理模块732可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,在一些实施例中,如果用户请求“附近的”寿司店,则自然语言处理模块732可用来自用户设备的GPS坐标来填充结构化查询中的{位置}参数。
在一些实施例中,自然语言处理模块732可将结构化查询(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”)。任务流处理模块736可被配置为接收来自自然语言处理模块732的结构化查询,完成结构化查询(必要时),以及执行“完成”用户最终请求所需的动作。在一些实施例中,完成这些任务所必需的各种过程可在任务流模型754中提供。在一些实施例中,任务流模型754可包括用于获取来自用户的附加信息的过程,以及用于执行与可执行意图相关联的动作的任务流。
如上所述,为了完成结构化查询,任务流处理模块736可能需要发起与用户的附加对话,以便获得附加信息并/或弄清可能有歧义的语音输入。当有必要进行此类交互时,任务流处理模块736可调用对话流处理模块734来参与与用户的对话。在一些实施例中,对话流处理模块734可确定如何(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可将问题提供给用户并可从用户接收回答。在一些实施例中,对话流处理模块734可经由音频和/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“同行人数”和“日期”信息时,对话流处理模块734可生成诸如“一行几位?”和“预订哪天?”之类的问题传递给用户。一旦接收到来自用户的回答,对话流处理模块734则可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以完成结构化查询中的缺失信息。
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便可着手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可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”的任务流模型可包括用于联系餐厅并实际地请求在特定时间针对特定同行人数的预订的步骤和指令。例如,通过使用结构化查询诸如:{餐厅预订,餐厅=ABC咖啡馆,日期=2012/3/12,时间=下午7点,同行人数=5人},任务流处理模块736可执行以下步骤:(1)登录到ABC咖啡馆的服务器或餐厅预订系统诸如
Figure GDA0001314435430000471
(2)在网站上的表格中输入日期、时间和同行人数信息,(3)提交表格,以及(4)在用户日历中针对该预订制作日历条目。
在一些实施例中,任务流处理模块736可在服务处理模块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可代表任务流处理模块736发起电话呼叫、设置日历条目、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)或与第三方服务交互。在一些实施例中,可通过服务模型756中的相应服务模型指定每项服务所需的协议和应用编程接口(API)。服务处理模块738可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,则餐厅可提交服务模型,该服务模型指定用于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,并将预订的必要参数(例如,时间、日期、同行人数)以符合在线预订服务的API的格式发送至在线预订接口。
在一些实施例中,自然语言处理模块732、对话流处理模块734以及任务流处理模块736可共同且反复地被使用,以推断并限定用户的意图、获得信息以进一步明确并提炼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。所生成的响应可以是对至少部分满足用户意图的语音输入的对话响应。此外,在一些实施例中,所生成的响应可作为语音输出被输出。在这些实施例中,所生成的响应可被发送至语音合成模块740(例如,语音合成器),其中该响应可被处理,以将对话响应合成为语音形式。在其他实施例中,所生成的响应可以是与满足语音输入中的用户请求相关的数据内容。
语音合成模块740可被配置为合成语音输出以呈现给用户。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,所生成的对话响应可为文本串的形式。语音合成模块740可将文本串转换成可听语音输出。语音合成模块740可使用任何适当的语音合成技术,以便从文本生成语音输出,所述技术包括但不限于:拼接合成、单位选择合成、双音子合成、域特定合成、格式合成、发音合成、基于隐马尔可夫模型(HMM)的合成,以及正弦波合成。在一些实施例中,语音合成模块740可被配置为基于对应于字词的音素串来合成各个字词。例如,音素串可与所生成的对话响应中的字词相关联。音素串可存储在与字词相关联的元数据中。语音合成模型740可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。
在一些实施例中,替代于使用语音合成模块740(或作为补充),语音合成可在远程设备(例如,服务器系统108)上执行,并且合成的语音可发送到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,其有可能获得比客户端侧合成将实现的质量更高的语音输出。
有关数字助理的更多细节可见于提交于2011年1月10日的名称为“IntelligentAutomated Assistant”的美国实用新型专利申请12/987,982以及提交于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13/251,088中,其全部公开内容以引用方式并入本文。
4.设备的示例性架构
图8A示出了根据本公开各种实施例的用于设备800的示例性架构的框图。在一些实施例中,设备800和遥控器810可实现数字助理系统(例如,数字助理系统700)。在一些实施例中,设备800、遥控器810和服务器(例如,服务器108)可实现数字助理系统(例如,数字助理系统700)。在图8A的实施方案中,媒体或其他内容任选地由设备800经由网络接口802接收,该网络接口任选地是无线连接或有线连接。一个或多个处理器804可任选地执行存储在存储器806或存储装置中的任何数量的程序,这些程序任选地包括用于执行本文所述的方法和/或过程(例如,过程1200)中的一者或多者的指令。
在一些实施方案中,显示控制器808使得一个或多个用户界面显示在显示器814上。另外,对设备800的输入任选地由遥控器810使用无线或有线连接经由遥控器接口812来提供。应当理解,图8A的实施方案不意味着限制本公开的设备的特征,并且有利于本公开所述的其他特征的其他部件也任选地包括于图8A的架构中或从该架构中省略。在一些实施方案中,设备800任选地对应于图2A和图3中的便携式多功能设备200以及图4中的设备400中的一者或多者;网络接口802任选地对应于图2A和图4中的RF电路208、外部端口224和外围设备接口218以及图4中的网络通信接口460中的一者或多者;处理器804任选地对应于图2A中的一个或多个处理器220以及图4中的一个或多个CPU 410中的一者或多者;显示控制器808任选地对应于图2A中的显示控制器256和图4中的I/O接口430中的一者或多者;存储器806任选地对应于图2A中的存储器202和图3中的存储器470中的一者或多者;遥控器接口812任选地对应于图2A中的外围设备接口218和I/O子系统206(和/或其部件)以及图4中的I/O接口430中的一者或多者;遥控器812任选地对应于和/或包括图2A中的扬声器211、触敏显示器系统212、麦克风213、一个或多个光学传感器264、一个或多个接触强度传感器265、一个或多个触觉输出发生器267、其他输入控制设备216、一个或多个加速度计268、接近传感器266和I/O子系统206、图4中的键盘/鼠标450、触控板455、一个或多个触觉输出发生器457和一个或多个接触强度传感器459以及图5B中的触敏表面551中的一者或多者;并且显示器814任选地对应于图2A和图3中的触敏显示器系统212以及图4中的显示器440中的一者或多者。
图8B示出了根据本公开各种实施例的用于遥控器810的示例性结构。遥控器810任选地包括触敏表面551。在一些实施方案中,触敏表面551是边对边的(例如,触敏表面551延伸到遥控器810的相对边缘,使得遥控器810的很少或没有表面存在于触敏表面551和遥控器810的一个或多个边缘之间,如图8B所示)。根据本文描述的实施例,触敏表面551任选地能够感测接触以及接触强度(例如,触敏表面551的点击)。遥控器810还任选地包括按钮816、818、820、822、824和826。按钮816、818、820、822、824和826任选地为机械按钮或机械按钮替代形式,其能够感测与此类按钮的接触或按压以在例如设备800上发起相应的动作。在一些实施方案中,用户对“菜单”按钮816的选择使设备800在当前执行的应用程序或当前显示的用户界面中向后导航(例如,回到在当前显示的用户界面之前显示的用户界面),或者将设备800导航到比当前显示的用户界面级别更高的用户界面。在一些实施方案中,用户对“home”按钮818的选择将设备800从显示在设备800的显示器814上的任何用户界面导航到主、原始或根用户界面(例如,导航到设备800的主屏幕,该主屏幕任选地包括设备800上可访问的一个或多个应用程序)。在一些实施方案中,用户对“播放/暂停”按钮820的选择导致在设备800上播放和暂停当前播放的内容项之间切换(例如,如果在选择“播放/暂停”按钮820时设备800上正在播放某个内容项,则该内容项任选地被暂停,并且如果在选择“播放/暂停”按钮820时设备800上暂停了某个内容项,则任选地播放该内容项)。在一些实施方案中,用户对按钮“+”822或“-”824的选择相应地增大或减小设备800重现的音频的音量(例如,设备800上当前播放的内容项的音量)。在一些实施方案中,用户对“语音输入”按钮826的选择允许数字助理(例如,数字助理系统700)接收用户的语音输入。遥控器810还可以将所接收的语音输入或其表示发送到另一设备(例如,设备800或服务器)以用于进一步处理。在一些实施方案中,遥控器810包括用于检测关于遥控器的运动的信息的一个或多个加速度计;任选地以下文阐述的实施方案的描述中提供的方式来利用这些加速度计。
图9示出了根据一些实施方案的自动语音识别(ASR)系统900的示例性示意框图。在一些实施例中,ASR系统900可对应于数字助理系统700的ASR系统731。在一些实施例中,可以使用包括但不限于设备200、400和800(图2A、图4和图8A)的一个或多个多功能设备来实现ASR系统900。多功能设备可以包括诸如服务器、个人计算机、移动设备、遥控器等的设备。具体地讲,ASR系统900可在一个或多个设备的存储器(例如,存储器202或470)和/或处理器(例如处理器220或CPU 410)中实现。ASR系统900可以包括在数字助理中,并且可以在多功能设备中提供语音识别能力。具体地讲,ASR系统900可以被配置为执行下文描述的任何过程或方法(例如,过程1200)中的任一者。ASR系统900可以包括下文进一步描述的特征提取器902和识别引擎904。
通常,ASR系统900可以接收语音输入(例如,语音输入);基于该语音输入识别字符、短语、命令、字词或其组合(统称为“内容”);并将所识别的语音输入的内容转换为文本。ASR系统900还可以使得以该内容被包括在所述语音输入中的次序相对应的序列显示该文本。
在一些实施方案中,字符可以包括字母、数字、控制字符或空格。字母可以是例如字母表上的任何小写字母或大写字母(例如,“a”、“b”、..“z”或“A”、“B”、..“Z”)。数字可以是例如具有0和9之间的值的任何数字(“0”、“1”、“2”、..“9”)。控制字符可以是标点符号(例如,“@”、“#”、“%”、“!”)字符。在一些实施例中,标点符号可以由标点字词识别。例如,标点符号“@”可以由标点字词“at”识别;标点符号“#”可以由标点字词“井号”识别;标点符号“%”可以由标点字词“百分比”或“百分号”识别;并且标点符号“!”可以由标点字词“感叹号”识别。标点符号及其对应的标点字词的其他实施例可以包括例如由标点字词“斜杠”识别的标点符号“/”、由标点字词“连字符”或“破折号”识别的标点符号“-”、由标点字词“句号”或“点”识别的标点符号“.”、由标点字词“逗号”识别的标点符号“,”、由标点字词“冒号”识别的标点符号“:”标点符号、由标点字词“分号”识别的标点符号“;”、由标点字词“问号”识别的标点符号“?”、由标点字词“撇号”识别的标点符号“`”、由标点字词“左括号”识别的标点符号“(”、由标点字词“右括号”识别的标点符号“)”、由标点字词“美元符号”识别的标点符号“$”、由标点字词“星号”识别的标点符号“*”、由标点字词“&符号”识别的标点符号“&”等。控制字符也可以是非标点符号字符。例如,控制字符可以是回车、制表符等。
短语可以用于识别对应的字符,并且可以例如包括用于识别该字符的拼写字词。例如,用于识别字母“a”的拼写字词可以是“apple”、“alpha”等。类似地,用于识别字母“b”的拼写字词可以是“boy”、“bravo”等。在一些实施例中,用于识别对应字符的短语可以具有某种格式,诸如“apple中的a”、“boy中的b”,“Nancy的n”和“Mary的m”。应当理解,任何拼写字词都可以用于识别对应的字符,并且用于识别该对应字符的短语可以具有任何期望的格式。
命令可以实现对所显示的文本的编辑和/或针对所显示的文本执行一个或多个其他功能。示例性命令包括“大写”、“小写”、“插入”、“删除”、“替换”、“复制”、“粘贴”、“选择”、“搜索”等。命令可以包括一个或多个伴随参数。例如,命令“插入”可以伴随有指示要插入的字符(例如,“插入c”)、插入位置、插入次数等的参数。在一些实施例中,命令还可以与其他命令结合地使用。命令“插入”可以例如与命令“大写”(例如,“插入大写c”)结合地使用。
字词可以包括多个字符。在一些实施例中,字词可以包括多个字符的任何组合,诸如自然语言字词“Lincoln”和“center”。在一些情况下,字词可以包括预定字符组合。例如,标点符号“@”之后的字词可以包括形成域扩展名(例如,“com”、“net”、“org”)、首字母缩略词(例如,FBI、IRS)等的预定字符组合。这种类型的字词可以具有预定数量的字符组合。
在ASR系统900的示例性操作中,在接收到语音输入后,特征提取器902可以预处理该语音输入,并将预处理后的语音输入提供给识别引擎904。在一些实施例中,预处理该语音输入可以包括从该语音输入提取一个或多个声学特征。因此,特征提取器902可以从语音输入提取声学特征,并将提取的声学特征提供给识别引擎904。在接收到预处理的语音输入后,识别引擎904可以该识别语音输入的内容。识别引擎904可以使用例如词汇912、语音识别模型914、上下文数据916和识别的凭据模型918(统称为知识库910)中的一者或多者来识别该内容。例如,识别引擎904可以将语音输入的内容与存储在知识库910中的字符、短语、命令和/或词(统称为已知类型)进行比较。如果找到一个或多个匹配,则识别引擎904可以将所述内容识别为已知类型的任何组合。例如,识别引擎904可以将该语音输入的内容识别为包括第一字符(例如,字母“a”)、由短语识别的第二字符(例如,由“boy中的b”识别的字母“b”),和/或字词(例如,“Lincoln”)。
一旦识别了内容,则识别引擎904可以将该语音输入的内容转换为文本,并且使得该文本以对应于该语音输入内容的次序的序列来显示。例如,所显示的文本的次序可以是“a”“b”“r”,其对应于这些字符在该语音输入中的次序(图10A-图10C)。
在一些实施例中,识别语音输入的内容可以包括识别该语音输入中包括的一个或多个话语。如上所述,由特征提取器902提取的声学特征可以被提供给识别引擎904以用于内容识别。基于所述声学特征,识别引擎可以识别对应的语音输入中的一个或多个话语。在一些情况下,声学特征可以用于确定一个或多个话语的开始和结束。例如,识别引擎904可以确定一个或多个声学特征对应于(例如,匹配)话语之间的延长静音或暂停,并且因此识别单独的或单个的话语。又如,暂停或静音的频谱可以不同于字符、短语、命令或字词的话语的频谱。因此,对该频谱的分析可以用于识别语音输入内的一个或多个话语。
在一些实施方案中,识别语音输入的内容可以包括确定所识别的话语的类型。例如,对于每个所识别的话语,识别引擎904可以确定话语的类型。识别引擎904可以确定例如话语的类型是否对应于字符、用于识别对应字符的短语、命令或字词。在一些实施例中,先前识别的字符、短语、字词和命令可以存储在知识库910的一个或多个部分中。例如,存储在知识库910中的字符、短语、命令和字词可以包括常用字符、短语、命令和字词,和/或由识别引擎904在一个或多个先前语音输入中接收的那些字符,短语和命令。知识库910可以存储在设备800、服务器(例如,服务器108)、多个服务器(例如,服务器场)或其组合上。
如上所述,知识库910可以包括词汇912、语音识别模型914、上下文数据916和/或识别的凭据模型918。词汇912可以包括常用字符(例如,26个字母字符)、短语(例如包括NATO的语音字母表的短语)、命令(例如编辑命令)和字词(例如自然语言字词、域扩展名和/或首字母缩略词)。如上所述,语音识别模型914可以包括例如声学模型和/或语言模型,并且可以实现一个或多个语音识别引擎。语音识别模型的示例可包括隐马尔可夫模型、高斯混合模型、深层神经网络模型、n元语言模型以及其他统计模型。语音识别引擎的示例可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。
在一些实施方案中,语音识别模型914可以是用户特定的,并且可以由语音识别和语言模型生成器913使用用户特定的数据来生成。语音识别和语言模型生成器913可以被配置为接收或获得用户特定的数据,诸如用户输入、用户使用数据、用户配置文件信息等。语音识别和语言模型生成器913还可以被配置为使用用户特定的数据生成一个或多个用户特定的语音识别模型914。
上下文数据916可以包括例如用户偏好、用户语音配置文件、硬件和/或软件状态、收集的传感器信息、数字助理和用户之间的先前交互等。上下文数据916还可以包括指示用户正在向其提供凭据的安全链接或设备的性质的信息。例如,上下文数据916可以指示用户正在向web电子邮件帐户(例如,Yahoo、Gmail)、云(例如,Apple iCloud)帐户或设备提供凭据。
识别出的凭据模型918可以包括常用凭据模型,和/或基于用户与数字助理的过往交互的凭据模型。例如,识别出的凭据模型918可以包括用户名模型和密码模型。示例性用户名模型可以包括firstname.lastname@domain_name.com(例如,Abraham.Lincoln@Lincolncenter.com)、firstinital.lastname@domain_name.com(例如,ALincoln@Lincolncenter.com)、firstnamelastname_numerical_digits@domain_name.com(例如,AbrahamLincoln_123@Lincolncenter.com)等。
如上所述,识别引擎904可以例如基于由特征提取器902提供的声学特征来确定语音输入的话语的类型。在一些实施例中,识别引擎904可以(例如,使用声学模型)识别与语音输入的一个或多个识别出的话语相对应的中间识别结果(例如,音素、音素串和子字词)。中间识别结果可以例如用于确定每个话语的类型。在一些实施方案中,识别引擎904可以确定话语的类型是否对应于字符、短语、命令或字词。例如,识别引擎904可以(例如,使用语言模型)将中间识别结果与知识库910中的已知类型进行比较。
在一些实施例中,识别引擎904可以将话语的音素序列(例如,字符或字词的发音)与包括在知识库910中的已知类型的一个或多个音素序列进行比较。可以(例如,使用声学特征)为话语识别音素序列。如果话语的音素序列与知识库910中已知类型的音素序列匹配(例如,基本匹配),则识别引擎904相应地确定该话语的类型。在一些实施例中,音素序列匹配的程度可以用于确定置信水平。例如,如果音素序列完全匹配,则置信水平可以是100%。又如,如果序列的6个音素中的5个匹配,则置信水平可以是90%。如果音素序列与字符、短语、命令或字词匹配(例如,基本匹配),则所述话语的类型被分别确定为字符、短语、命令或字词。
在一些实施例中,根据确定语音输入的话语的类型对应于字符、短语、字词或其组合,识别引擎904可以获得对应于该话语的语音输入内容的表示。该表示可以是音频表示、文本表示,空间/向量表示或其组合。
在一些实施例中,如果音素序列匹配知识库910中的不止一个类型,则识别引擎904可以确定每个匹配类型的置信水平,并选择具有最高置信水平的类型。例如,如果音素序列与字词(例如,字词“插入”)和命令(例如,命令“插入”)两者匹配,则识别引擎904可以确定作为字词类型的置信水平以及作为命令类型的置信水平。在一些实施例中,可以基于语音输入中的附加内容或与语音输入有关的其他上下文来确定置信水平。例如,命令可以伴随有用于根据该命令执行动作的一个或多个参数。因此,如果识别引擎904识别与语音输入中的命令相关联的一个或多个参数,则其可以确定命令类型的置信水平高于字词类型的置信水平。在一些实施例中,识别引擎904可以基于上下文数据916来确定置信水平。在一些实施例中,如果没有找到匹配,则识别引擎904可以被配置为确定所述话语对应于字词(例如,自然语言字词),且将此作为默认配置。在一些实施例中,如果没有找到匹配,则识别引擎904还可以被配置为确定一个或多个候选类型。候选类型可以例如基于每种类型的置信水平来确定。在一些实施例中,候选类型可以用于获得语音输入的内容的候选表示。候选表示可以是音频表示、文本表示、空间/向量表示或其组合的形式。候选表示可以被呈现给用户以供选择。
应当理解,可以关于字符、短语、字词或命令的任何次序或任何组合来执行对话语类型的确定。例如,识别引擎904可以首先确定话语的类型是否对应于字符。如果话语的类型不对应于字符,则识别引擎进一步确定其类型是否对应于短语、字词等。又如,识别引擎904还可以首先确定话语的类型是否对应于短语。如果话语的类型不对应于短语,则识别引擎进一步确定其类型是否对应于字符、字词等。还可以相对于字符、短语、字词或命令并行地执行该确定。
在获得表示后,识别引擎904可以将该表示转换为文本。在转换为文本后,识别引擎904可以使该文本显示。
在一些实施例中,识别语音输入的内容可以包括确定置信水平。置信水平可以例如指示语音输入的内容被准确识别的概率。在一些实施例中,置信水平可以与所识别的语音输入的内容相关联。如上所述,在一些实施例中,识别语音输入的内容可以包括识别语音输入的话语、确定该话语的类型,和/或获得语音输入的内容的表示,下面将进一步详细描述。因此,置信水平因此可以与话语的识别、话语被确定的类型、所获得的语音输入内容的表示或其组合相关联。例如,如果相关联的置信水平大于或等于阈值,则识别引擎904可以将内容识别为包括特定类型的话语。相反,如果相关联的置信水平不大于或等于阈值,则识别引擎904可以不将内容识别为包括任何类型的话语。与此相反,识别引擎904可以忽略所识别的话语类型,并且提供该话语的一个或多个候选类型、错误消息或其组合。候选类型可以例如基于每种类型的置信水平来确定。可以视觉形式、听觉形式或其组合向用户提供候选类型。在一些实施例中,识别引擎904还可以导致向用户提供错误消息(例如,“对不起,我没听见。你能再说一遍吗?”)。
在一些实施例中,识别引擎904可以获得语音输入内容的表示的置信水平。如前所述,置信水平表示关于话语类型的确定的确定度。根据确定置信水平大于或等于阈值,识别引擎904将所述表示转换为文本。在一些实施例中,根据确定置信水平小于阈值,识别引擎904可以识别获得相应的候选表示的一个或多个候选类型。可以向用户提供候选表示以供选择。在一些实施例中,识别引擎904可以提供候选表示、错误消息(例如,“我不认识你说的话,请说一个字母或短语,例如“apple中的a”)或其组合。在一些实施例中,可以基于中间识别结果(例如,音素、音素串和子字词)和存储在知识库910中的已知类型(例如,使用语言模型)之间的匹配来生成候选表示。
在一些实施例中,识别引擎904可以基于语音输入来识别命令。如上所述,在一些实施方案中,识别引擎904可以首先识别语音输入的话语,并且确定该话语的类型是否对应于命令。根据确定话语的类型对应于命令,识别引擎904可以使得根据该命令发起动作。例如,识别引擎904可以使先前显示的文本被编辑(例如,插入或删除字符)。
在一些实施例中,识别引擎904还可以使一个或多个话语被存储以用于学习和/或培训目的。话语可以被存储在例如存储器(例如,存储器202)和/或数据库中。在一些实施例中,一个或多个话语对应于识别由识别引擎904所识别的相应字符、命令和/或字词的字符、短语。这些话语(例如,话语的声学特征)可以用于更新知识库910的至少一部分,使得可以更精确地确定后续用户话语的类型。
5.语音输入识别实施例
图10A-图10F示出了根据各种实施例的语音输入识别功能。根据本文所述的一个或多个实施例,电子设备(诸如图8A的设备800)和/或遥控器810可以使用用户提供的口头用户输入(例如,语音输入、话音输入)来控制。设备800、遥控器810、服务器(例如,服务器108)或其组合可以实现数字助理系统(数字助理系统700)。参考图10A至10F,在一些实施例中,设备800可以从用户1030接收一个或多个语音输入,诸如1024A至1024F。用户1030可以提供语音输入以用于例如口述或以其它方式输入用户凭据(例如,用户名和/或密码)的目的。显示器814可以用于提示和/或允许用户1030输入用户名和密码以用于认证目的。例如,可以提示用户输入凭据以登录到设备、帐户、服务等。设备800可以直接从用户1030或间接地通过另一设备(例如,遥控器810)接收语音输入。可以经由设备800的麦克风(例如,麦克风213)或遥控器810接收语音输入1024A至1024F。在一些实施例中,设备800可以识别根据本文所述实施例的语音输入1024A至1024F的内容(例如,字符、用于识别字符的短语、命令、字词或其组合)。语音输入1024A至1024F的内容的识别可以由例如包括自动语音识别系统(例如,ASR系统900)的数字助理来执行。
参考图10A,在一些实施例中,设备800可以基于语音输入来识别字符。例如,在接收到语音输入1024A后,设备800可以识别语音输入1024A的一个或多个话语。如图所示,语音输入1024A的所识别的话语可以包括字符“a”。
在识别一个或多个话语后,设备800可以确定话语的类型。在一些实施例中,该确定可以基于存储在知识库中的字符,诸如常用的字母字符、数字和控制字符,和/或先前从用户1030接收的字符设备800。包括在知识库910中的字符可以被存储在设备800或服务器(例如,服务器108)上。例如,设备800可以通过将话语的音素序列(例如,字符的发音)与已知字符的音素序列进行匹配,来确定该话语的类型是否对应于字符。
在一些实施例中,根据确定话语的类型对应于字符,设备800将字符识别为包括在语音输入1024A的内容中(例如,字符“a”),并将该字符转换为文本。
响应于转换到文本,设备800可以使得例如使用显示器814显示语音输入1024A的内容的文本(例如,字符“a”的文本)。
参考图10B,在一些实施例中,设备800可以识别由短语识别的字符。例如,在接收到语音输入1024B后,设备800可以识别语音输入1024B的一个或多个话语。如图所示,语音输入1024B可以包括短语(例如,“boy中的b”)以用于识别该短语的相应字符(例如,“b”)。
在识别语音输入1024B的一个或多个话语后,设备800可以确定话语的类型。在一些实施方案中,该确定可以基于存储在知识库中的短语,诸如常用短语。用于识别字符的常用短语可以使用在NATO的语音字母表中指定的拼写字词(例如,Alpha、Bravo、Charlie、Delta、Echo、Foxtrot、Golf、Hotel、India、Juliet、Kilo、Lima、Mike、November、Oscar、Papa、Quebec、Romeo、Sierra、Tango、Uniform、Victor、Whiskey、X-ray、Yankee、Zulu)。
在一些实施方案中,知识库中的短语还可以包括先前接收到的短语。例如,用户1030可以不使用NATO的语音字母表作为用于识别字符的拼写字词。相反,用户1030可能先前已经使用了自定义短语,诸如“Aaron中的a”或“Lincoln中的l”。设备800还可以存储用户1030先前在知识库中提供的此类自定义短语。因此,如果用户1030说出先前使用的自定义短语,则设备800还可以确定该话语的类型对应于用于识别相应字符的短语。用于识别知识库中的相应字符的短语可以被存储在设备800或服务器(例如,服务器108)上。
如上所述,可以响应于用户提供语音输入来确定话语的类型。例如,设备800可以通过将话语的音素序列(例如,短语的发音)与知识库中短语的音素序列进行匹配,来确定该话语的类型是否对应于短语。
在一些实施例中,根据确定话语的类型对应于用于识别相应字符的短语,设备800将该短语识别为包括在语音输入1024B的内容中,并将该短语识别的字符转换为文本。响应于转换到文本,设备800可以使得例如使用显示器814显示语音输入1024B的内容的文本(例如,字符“b”的文本)。
参考图10C,在一些实施例中,设备800可以基于附加的语音输入来识别附加的字符和短语。例如,在接收到语音输入1024C后,设备800可以识别语音输入1024C的一个或多个话语。如图所示,语音输入1024C可以包括附加字符(例如“r”、“a”、“h”和“a”)和附加短语(例如,“Mary中的m”)。如上所述,响应于接收到语音输入1024C,设备800可以识别语音输入1024C的一个或多个话语、确定话语的类型,并将识别的语音输入1024C内容的字符转换为文本以用于在显示器814上显示。
在一些实施例中,设备800C可以基于语音输入来识别标点字词。例如,在接收到语音输入1024C后,设备800可以识别语音输入1024C的一个或多个话语。如图所示,语音输入1024C可以包括识别(例如,对应于)标点符号“@”的标点字词“at”。
在识别语音输入1024C的一个或多个话语时,设备800可确定话语的类型。在一些实施例中,该确定可基于存储在知识储存库中的标点字词,诸如常用标点字词(例如,“at”、“英镑符号”、“美元符号”等)和/或先前从用户1030接收的定制标点字词设备800。例如,在意欲使标点字词“星”也对应于标点符号“*”的情况下,用户1030可于先前说该出标点字词“星”,而不是对应于标点符号“*”的标点符号“星号”。此类定制标点字词也可存储在知识储存库中。包括在知识储存库中的标点字词可存储在设备800或服务器(例如,服务器108)上。
如文中所述,可以响应于用户提供语音输入来确定话语的类型。例如,设备800可通过将话语的音素序列(例如,字符的话语)与包括在知识储存库910中的标点字词的音素序列相匹配,来确定话语的类型是否对应于标点字词。在一些情况下,可能存在一个以上的实质匹配。因此,设备800可基于标点字词的上下文和/或使用置信水平来消除有歧义的匹配。例如,设备800可基于自用户1030提供的语音输入所识别的一个或多个其他话语,来确定哪个匹配是适当的。又如,设备800可确定每个匹配类型的置信水平,并选择具有最高置信水平的类型。例如,如果音素序列与标点字词(例如,标点字词“at”)和字词(例如,自然语言字词“at”)二者皆匹配,则设备800可确定作为标点字词的类型以及作为字词的类型的置信水平。在一些实施例中,可基于语音输入1024C中的附加话语来确定置信水平。例如,使用识别的凭据模型,设备800可确定用户意欲在语音输入1024C中提供电子邮件地址作为用户名。因此,设备800可确定标点字词类型的置信水平高于自然语言字词类型的置信水平。
在一些实施例中,根据话语类型对应于标点字词这一确定结果,设备800识别语音输入1024C内容的标点字词(例如,字词“at”),并将该标点字词转换为相应标点符号的文本。例如,设备800可以将标点字词“at”转换为标点符号“@”的文本。参考图10C,响应于该转换,设备800可例如利用显示器814显示语音输入1024C内容的文本(例如,标点符号“@”的文本)。
参考图10D,在一些实施例中,设备800可例如通过识别语音输入1024D的一个或多个话语,而基于该语音输入来识别一个或多个字词。如图所示,语音输入1024D可包括一个或多个字词,每个字词可包括多个字符的任何组合。字词可以是例如“Lincoln”和“中心”这类自然语言字词。
在识别语音输入1024D的话语时,设备800可确定话语的类型。在一些实施例中,该确定可基于存储在知识储存库中的词,诸如用于输入凭据(例如,“yahoo”,“gmail”和“aol”)的常用字词和/或用户1030先前说出的字词。例如,用户1030先前可已经说出用于输入用户名的字词“Lincoln”和“center”。因此,字词“Lincoln”和“center”存储在知识储存库中。包括在知识储存库中的字词可存储在设备800或服务器(例如,服务器108)上。
设备800可通过将话语的音素序列(例如,字词的话语)与包括在知识储存库中的字词的音素序列相匹配,来确定话语的类型是否对应于字词。
在一些实施例中,设备800可基于预先确定的配置来确定话语的类型是否对应于字词。例如,设备800可以被预先配置为确定话语的类型,使得话语的默认类型对应于字词。例如,在接收到语音输入时,设备800可识别一个或多个话语,并且确定每个所识别的话语的类型是否对应于一个字符(例如,字母,数字,或诸如标点符号的控制字符)、识别对应字符的短语,或命令。如果设备800确定话语的类型不对应于这些类型中的任何类型,则设备800可被配置为默认地确定话语的类型对应于一个字词。
在一些实施例中,根据话语类型对应于字词这一确定结果,设备800识别该字词(例如,字词“Lincoln”),并将识别出的字词转换为文本。参考图10D,在转换为文本时,设备800可使用显示器814来显示语音输入1024D内容的文本(例如,字词“Lincoln”的文本)。
参考图10E,在一些实施例中,设备800可例如通过识别语音输入1024E中的一个或多个话语来识别额外的标点字词。如图所示,语音输入1024E可包括额外的标点字词(例如,标点字词“dot”)。响应于接收到语音输入1024E,设备800可识别话语,将话语的类型确定为标点字词,并将话语转换为文本以在显示器814上显示。
在一些实施例中,设备800还可基于语音输入来识别具有预先确定的字符组合的字词。例如,在接收到语音输入1024E时,设备800可识别语音输入1024E的话语。如图所示,语音输入1024E可包括具有预先确定的字符组合(例如,域扩展名)的字词。如文中所述,具有预先确定的字符组合的字词可包括形成例如域扩展名(例如,“com”、“net”和“org”)的多个字符、首字母缩略词(例如FBI、IRS)等等。
在基于语音输入1024E识别话语时,设备800可确定话语的类型。在一些实施例中,该确定可基于先前识别的并存储在知识储存库(例如,知识储存库910)中的词语。例如,这些字词可包括用于输入凭证(例如,域扩展名“com”、“net”和“org”)的一些常用字词。又如,这些字词可包括用户1030先前说出的词,例如缩略词“FBI”、“IRS”和“USPTO”。因此,先前说出的词语也可存储在知识储存库中。包括在知识储存库中的字词可存储在设备800或服务器(例如,服务器108)上。
如文中所述,响应于用户提供语音输入,话语的类型可得到确定。例如,如上所述,设备800可通过将话语的音素序列与知识储存库中字词的音素序列相匹配,来确定话语的类型是否对应于具有预先确定的字符组合的字词。
在一些实施例中,根据话语类型对应于具有预先确定的字符组合的字词这一确定结果,设备800识别该具有预先确定的字符组合(例如,“com”)的字词,并将该字词转换为文本。参考图10E,响应于转换为文本,设备800可利用显示器814显示语音输入1024E内容的文本(例如,字词“com”的文本)。
参考图10F,在一些实施例中,设备800可以识别额外的字符、标点字词和短语。设备800还可识别命令。例如,在接收到语音输入1024F时,设备800可识别语音输入1024F中的一个或多个话语。如图所示,语音输入1024F可包括字符、短语和命令(例如,字符“a”、标点字词“星号”、字符“b”、命令“大写”、字符“c”、标点字词“美元符号”、数字“1”、“2”和“3”以及标点字词“百分号”)的混合形式。响应于接收到语音输入1024F,设备800可识别字符“a”、标点字词“星号”、字符“b”、标点字词“美元符号”、数字“1”、“2”和“3”以及标点符号“百分号”的话语。设备800还可确定这些话语的类型,并且将这些话语转换为用于在显示器814上显示的文本。
参考图10F,设备800还可例如通过识别语音输入1024F中的话语,而基于语音输入来识别命令。如图所示,语音输入1024F可包括命令(例如,命令“大写”)。命令使得所显示的文本能够受到编辑,或者执行关于所显示文本的任何期望的功能。示例性命令包括“大写”、“小写”、“插入”、“删除”、“替换”、“复制”、“粘贴”、“选择”、“搜索”等。
在基于语音输入1024F识别话语时,设备800可确定话语的类型。在一些实施例中,该确定可基于先前识别的并存储在知识储存库(例如,知识储存库910)中的命令。在一些实施例中,这些命令可包括诸如“插入”、“删除”、“大写”、“小写”等常用命令。这些命令还可包括先前从用户1030接收的命令设备800。包括在知识储存库中的命令可存储在设备800或服务器(例如,服务器108)上。设备800可通过将话语的序列(例如,命令的话语)与知识储存库中的命令的音素序列相匹配,来确定话语的类型是否对应于命令。
在一些实施例中,根据话语类型对应于命令这一确定结果,设备800可使得某一动作根据要发起的命令而得到发起。例如,如图10F所示,根据“大写”的话语类型对应于命令的这一确定结果,设备800可使得语音输入1024F的内容(例如,字符“c”的话语)被转换为文本,并且发起将“c”的文本转换为其大写形式“C”的动作。
图11A-图11D示出根据各种实施例的语音输入识别的功能。参考图11A,在一些实施例中,设备800可识别额外的字符和短语。例如,在接收到语音输入1144A时,设备800可识别语音输入1144A中的一个或多个话语。如图所示,语音输入1144A可包括字符、短语和命令(例如,字符“a”、短语“boy中的b”,多个字符“r”、“a”和“h”)的混合形式。如文中所述,响应于接收到语音输入1144A,设备800可识别字符“a”、“r”和“a”和短语“boy中的b”的话语,将它们转换为文本,并将该文本显示在显示器814上。
设备800还可基于语音输入来识别额外的命令。例如,设备800可能错误地将字符“h”识别为字符“s”,并且因此导致在显示器814上显示字符“s”而不是字符“h”。如图11A所示,用户1130可能希望纠正这样的错误,并且因此在语音输入1144A中说出“删除”,意图删除字符“s”。在一些实施例中,用户1130可另选地说出“Henry中的h”,以明确强调用户的预期输入。
在一些实施例中,根据语音输入1144A中的话语的类型对应于命令的这一确定结果,设备800可以根据命令发起动作。例如,如图11A所示,根据语音输入1144A中的话语的类型对应于命令(例如,命令“删除”)这一确定,设备800可在显示器814上显示或删除当前字符或紧邻的前一字符(例如,字符“s”)。在一些实施例中,如果识别了一个以上的“删除”命令,则设备800可使显示器814上所显示的当前字符和一个或多个紧邻的前一字符被删除。例如,如果语音输入1144A包括两个连续的“删除”命令,则设备800可使得紧邻的前两个字符(例如,字符“s”和“a”)被删除;并且如果语音输入1144A包括三个连续的“删除”命令,则设备800可使得紧邻的前三个字符(例如,字符“s”,“a”和“r”)被删除,以此类推。
在一些实施例中,在提供了包括命令“删除”的语音输入之后,用户1030可使用例如短语(例如,“Henry中的h”)来提供额外的语音输入以阐明用户的意图。在接收到语音输入1144A时,设备800可基于语音输入1144A来识别正确的字符(例如,“h”)。例如,设备800可识别短语的话语,基于该识别将正确的字符转换为文本,并且使该文本在显示器814上显示。如图11A所示,作为根据命令(例如,删除“s”并显示“h”)所执行的动作的结果,设备800可以使显示器814显示语音输入1144A内容的文本。
参考图11B,在一些实施例中,设备800可识别额外的命令。例如,用户1130可能希望插入字符“a”,并且因此可说出“插入‘a’”。
在一些实施例中,根据话语类型对应于命令(例如,“插入”)这一确定结果,设备800可使得某一动作根据该命令而得到发起。例如,如图11B所示,根据语音输入1144B的话语的类型对应于命令这一确定,设备800使得命令“插入”之后所接的字符(例如,“a”)插入到显示器814上所显示的当前字符的前一紧邻位置处(例如,在字符“m”之前)。如图11B所示,作为根据命令(例如,在字符“m”前插入字符“a”)执行动作的结果,设备800可(例如,使用显示器814)使语音输入1144B的文本得到显示。
参考图11C,在一些实施例中,可以结合一个或多个参数来提供命令。例如,用户1130可在语音输入1144C的大部分已由用户1130提供之后才识别输入不正确。例如,在以尝试输入用户名时,用户1130可能在用户1030说出“dot”“com”之后才意识到缺失字符“a”。其结果是,用户1130可能期望在字词“abraham”的字符“h”和“m”之间插入字符“a”。因此,用户1130可以提供包括了命令“插入”、并且还指定了“a”处于“at”之前的“h”和“m”之间的语音输入1144C。在一些实施例中,语音输入1144C可包括诸如“在字词‘abraham’中的‘h’和‘m’之间插入‘a’”的命令。如文中所述,在接收到语音输入1144C时,设备800可识别语音输入1144C中的话语。
在识别话语时,设备800还可确定该话语的类型是否对应于命令(例如,“插入”)和一个或多个相关联的参数。在一些实施例中,设备800可以首先确定这些话语中的一个是否对应于命令(例如,“插入”)。根据话语的类型对应于命令这一确定结果,设备800还可确定该命令是否伴随有用于根据命令而执行动作的一个或多个参数。此类参数可包括,例如要插入或删除的字符(例如,“a”)和编辑的位置(例如,“在‘at’之前的‘h’和‘m’之间”、“在字词‘abraham’中的‘h’和‘m’之间”)。在一些实施例中,确定命令是否伴随有一个或多个参数,可使得动作能够根据用户的意图来发起,而不是根据默认配置来发起。例如,如下所述,设备800可使得动作根据命令和参数来发起,而不是根据命令和一个或多个默认配置(例如,默认配置为删除紧邻的前一字符,在当前字符之后插入,等等)来发起。
根据命令伴随有一个或多个参数这一确定结果,设备800可使得动作对应于命令和参数来发起。例如,如图11C所示,根据“插入”的话语类型对应于命令这一确定结果,以及存在伴随“插入”命令的参数这一确定结果,设备800可使得动作根据该命令(例如,插入相应字符,诸如字母“a”)和参数(例如,在字词“abraham”中的“h”和“m”之间)来发起。参考图11C,作为根据命令(例如,将字符“a”插入到正确位置)和参数来执行动作的结果,设备800可以(例如,使用显示器814)使语音输入1144C内容的文本得到显示。
参考图11D,设备800可识别一个或多个额外的命令。例如,用户1130可以重复前一个字符。例如,在语音输入1144D中,在打算在密码中输入两次字符“b”的情况下,用户1130可以说出“boy中的b”,然后说出命令“重复”。
如文中所述,根据话语类型对应于命令这一确定结果,设备800可使得某一动作根据命令而得到发起。例如,如图11D所示,设备800可使得动作根据命令(例如,重复紧邻的前一字符)来发起。参考图11D,作为根据命令(例如,显示额外字符“b”)执行动作的结果,设备800可使得语音输入1144D内容的文本得到显示。
应当理解,虽然使用设备800作为示例来描述图10A-图10F和图11A-图11D,但是本文描述的数字助理功能和处理中的一者或多者可另选地由服务器(例如,服务器108)或设备800和服务器的组合来执行。例如,在接收到语音输入1024A-F中的一者或多者时,设备800可以向服务器108提供表示语音输入1024A-F的数据,并且服务器108可识别语音输入1024A-F的内容。例如,服务器108可识别一个或多个话语,确定该一个或多个话语的类型,并获得语音输入1024A-F的内容的表示。在一些实施例中,服务器108可以向设备800提供语音输入1024A-F内容的表示。在从服务器108接收到语音输入1024A-F内容的表示时,设备800可将所获得的表示转换为文本,并使文本显示在显示器814上。在一些实施例中,服务器108可将语音输入1024A-F的表示转换为文本,并将该文本提供给设备800。此后设备800可使该文本显示在显示器814上。
6.识别语音输入的过程
图12A-图12D示出了根据一些实施方案的用于语音输入识别的示例性过程1200的流程图。可使用一个或多个设备104,108,200,400,600,800或810(图1、图2A、图4、图6A-图6B或图8A-图8B)来执行过程1200。过程1200中的操作任选地被组合或拆分,并且/或者一些操作的次序任选地被改变。
参考图12A,在框1202处,接收语音输入。该语音输入可包括对应于字符、短语、命令和/或字词的一个或多个话语。该语音输入可以对应于表示用户名的第一用户凭据或表示密码的第二用户凭据中的至少一者。
在框1204处,基于语音输入来识别第一字符、用于识别第二字符的短语,以及字词。在一些实施例中,第一字符包括以下项中的至少一者:字母、数字、控制字符或空格。控制字符可包括由标点字词识别出的标点符号(例如,跳格,回车)或非标点符号字符。用于识别第二字符的短语可包括用于辅助识别第二字符的拼写字词。该字词可包括表示例如自然语言字词的多个字符的任何组合。该字词还可包括表示例如域扩展名和/或首字母缩略词的预先确定的字符组合。
在一些实施例中,基于与用户相关联的上下文数据或者一个或多个所识别的凭据模型中的至少一者,来识别第一字符、用于识别第二字符的短语,以及基于语音的字词。例如,上下文数据可包括用户的日历、联系人、用户语音配置文件或任何其他用户特定型数据。在一些实施例中,所识别的凭据模型可表示所识别的凭证格式,诸如用户名格式(例如,名_姓@域名.com,首字母_姓@域名.org)或诸如字母、大小写、控制字符,以及数字。
在一些实施例中,基于注视检测来识别第一字符、用于识别第二字符的短语,以及基于语音的字词。例如,当接收到来自用户的语音输入时,可以(例如,通过使用相机)确定用户是否正在观看某个方向或区域。如果确定该方向或区域对应于用于输入凭据的键盘或键,则用户观看方向或区域的这一信息可以帮助识别第一字符、识别出短语的第二字符,以及字词。
在框1206处,可基于存储在用户设备(例如,图10A-图10F和图11A-图11D中的设备800)中的一个或多个语音识别模型来识别语音输入的内容。在一些实施例中,可以在不与服务器(例如,服务器108)通信的情况下,在用户设备上执行识别。
在框1208处,在一些实施例中,可使用用户设备和服务器来执行语音输入内容的识别。例如,识别可包括将表示语音输入的数据从用户设备提供给服务器。服务器可基于存储在服务器中的一个或多个语言模型,来执行第一字符、用于识别第二字符的短语以及词语中的至少一者的识别。然后,用户设备从服务器接收表示所识别的第一字符、所识别的用于识别第二字符的短语或所识别的字词中的至少一者的数据。
参考图12B,在框1212处,识别语音输入的内容包括识别语音输入的话语。在框1214处,第一字符、用于识别第二字符的短语和字词的识别包括确定话语的类型。
在框1216处,确定话语的类型是否对应于所识别的字符。在框1218处,针对该话语确定其是否对应于控制字符。在框1220处,根据话语对应于控制字符这一确定结果,针对该话语确定其是否对应于标点字词。
在框1221处,根据话语对应于标点字词这一确定结果,获得对应于该标点字词的标点符号的表示。在框1222处,根据话语不对应于标点字词这一确定结果,获得不同于标点字词的控制字符的表示。
在框1224处,确定话语的类型是否对应于所识别的用于识别第二字符的短语。在框1226处,确定话语的类型是否对应于字词。
在框1228处,基于所确定的话语类型,获得第一字符的表示、由短语识别的第二字符,或对应于话语的字词。在一些实施例中,该表示可包括音频表示、文本表示、空间/向量表示或其组合。
在框1230处,获得表示的置信水平。置信水平表示识别的准确度。在框1232处,确定置信水平是否大于或等于阈值。在框1234处,根据置信水平大于或等于阈值这一确定结果,将对应于该话语的第一字符、由短语识别的第二字符或字词的表示转换为文本。在框1236处,根据置信水平小于阈值这一确定结果,可以提供一个或多个候选表示、错误消息或其组合。
在框1238处,可识别至少一个命令。该命令使所显示的文本能够得到编辑。在框1240处,为了识别命令,识别至少一个话语。在框1242处,确定话语的类型是否对应于所识别的命令。在框1244处,根据语音的类型对应于所识别的命令这一确定结果,根据所识别的命令发起动作,以编辑所显示的文本。
在框1246处,存储对应于至少一个命令的话语,并且存储与对应于该至少一个命令的话语相关联的信息。与对应于至少一个命令的话语相关联的信息可包括,例如用户说出命令“删除”的次数。该信息可以指示识别的准确度。
在框1248处,响应于该识别,将第一字符、第二字符和字词转换为文本。在框1250处,以对应于语音输入中第一字符、第二字符和字词的次序在显示器上显示文本。例如,可以按照第一字符、接着是字词、再接着是用于识别第二字符的短语这样的次序提供语音输入。因此,所显示的文本呈第一字符、接着是字词、再接着是第二字符的次序。
在框1252处,可存储一个或多个所识别的语音输入的话语、对应于第一字符、用于识别第二字符的短语以及字词的一个或多个所识别的话语。存储话语可使数字助理得到学习与训练,从而提高识别的准确性。
7.电子设备
图13示出了根据各种所述实施例(包括参考图9、图10A-图10F和图11A-图11D描述的那些)的原理进行配置的电子设备1300的功能框图。该设备的功能块可任选地由执行各种所述实施例的原理的硬件、软件或硬件和软件的组合来实现。本领域技术人员应当理解,图13中所述的功能框可任选地组合或分离为子框,以实现各种所述实施例的原理。因此,本文的描述任选地支持本文所述的功能块的任何可能的组合、分离或进一步限定。
如图10所示,电子设备1300可以包括麦克风1302和处理单元1308。在一些实施例中,处理单元1308包括接收单元1310、识别单元1312、转换单元1314和致使单元1316,并任选地包括,提供单元1318、确定单元1320、获得单元1322和存储单元1324。
处理单元1308被配置为:接收(例如,利用接收单元1310)语音输入;并且基于语音输入来识别(例如,利用识别单元1312)第一字符、用于识别第二字符的短语和字词。处理单元还被配置为响应于该识别,将第一字符、第二字符和字词转换(例如,利用转换单元1314)为文本;并使得(例如,利用致使单元1316)该文本以对应于语音输入中第一字符、第二字符和字词的次序利用显示器得到显示。
在一些实施例中,第一字符包括以下项中的至少一者:字母、数字、控制字符或空格。
在一些实施例中,控制字符包括由标点字词所识别的标点符号。
在一些实施例中,短语包括用于辅助识别第二字符的拼写字词。
在一些实施例中,字词包括多个字符。
在一些实施例中,多个字符表示域扩展名或首字母缩略词中的至少一者。
在一些实施例中,第一字符、用于识别第二字符的短语和字词的识别包括,(例如,利用识别单元1312)基于存储在用户设备中的一个或多个语音识别模型,来识别第一字符、用于识别第二字符的短语或字词中的至少一者。
在一些实施例中,第一字符、用于识别第二字符的短语和字词的识别包括,(例如,利用提供单元1318)向服务器提供表示语音输入的数据;以及(例如,利用接收单元1310)从服务器接收表示所识别的第一字符、用于识别第二字符的所识别的短语,或所识别的字词中的至少一者的数据。
在一些实施例中,第一字符、用于识别第二字符的短语和字词的识别包括,(例如,利用识别单元1312)基于存储在服务器中的一个或多个语言模型,来识别第一字符、用于识别第二字符的短语或字词中的至少一者。
在一些实施例中,基于语音输入来识别第一字符、用于识别第二字符的短语和字词包括,(例如,利用识别单元1312)识别语音输入的话语;(例如,利用确定单元1320)确定话语的类型;并且(例如,利用获得单元1322)基于所确定的话语的类型,获得对应于话语的第一字符、由短语识别的第二字符或字词的表示。
在一些实施例中,确定话语的类型包括执行以下各项中的至少一者:(例如,利用确定单元1320)确定话语的类型是否对应于所识别的字符;(例如,利用确定单元1320)确定话语的类型是否对应于所识别的用于识别第二字符的短语;以及(例如,利用确定单元1320)确定话语的类型是否对应于字词。
在一些实施例中,确定话语的类型是否对应于所识别的字符包括:(例如,利用确定单元1320)针对话语确定其是否对应于控制字符;并且根据该话语对应于控制字符这一确定结果,(例如,利用确定单元1320)针对该话语确定其是否对应于标点字词。
在一些实施例中,基于所确定的话语类型来获得字符的表示包括:根据对话语对应于标点字词这一确定结果,(例如,利用获得单元1322)获得对应于标点字符的标点符号的表示,并根据话语不对应于标点字符这一确定结果,(例如,利用获得单元1322)获得不同于标点字符的控制字符的表示。
在一些实施例中,基于语音输入来识别第一字符、用于识别第二字符的短语和字词还包括:(例如,利用获得单元1322)获得表示的置信水平;(例如,利用确定单元1320)确定置信水平是否大于或等于阈值。
在一些实施例中,将第一字符、第二字符和字词转换为文本包括:根据置信水平大于或等于阈值这一确定结果,(例如,利用转换单元1314)将对应于话语的第一字符、由短语识别的第二字符,或字词的表示转换为文本;并根据置信水平小于阈值这一确定结果,(例如,利用提供单元1318)提供一个或多个候选表示、错误消息或它们的组合。
在一些实施例中,处理单元1308还被配置为(例如,利用识别单元1312)识别至少一个命令,其中所述至少一个命令使得所显示的文本能够得到编辑。
在一些实施例中,识别至少一个命令包括:(例如,利用识别单元1312)识别至少一个话语;(例如,利用确定单元1320)确定该话语的类型是否对应于所识别的命令;并且根据该话语的类型对应于所识别的命令这一确定结果,(例如,利用致使单元1316)致使动作根据所识别的命令来发起,以编辑所显示的文本。
在一些实施例中,处理单元1308还被配置为(例如,利用存储单元1324)存储与至少一个命令相对应的话语,并且(例如,利用存储单元1324)存储与对应于所述至少一个命令的话语相关联的信息。
在一些实施例中,基于语音输入,识别第一字符、用于识别第二字符的短语、以及字词基于与用户相关联的上下文数据或一个或多个识别出的凭据模型中的至少一者。
在一些实施例中,与用户相关联的上下文数据包括用户语音配置文件。
在一些实施例中,一个或多个所识别的凭据模型表示一个或多个所识别的凭证格式。
在一些实施例中,基于语音输入来识别第一字符、用于识别第二字符的短语和词,是基于注视检测进行的。
在一些实施例中,语音输入对应于表示用户名的第一用户凭据或表示密码的第二用户凭据中的至少一者。
在一些实施例中,处理单元1308还被配置为(例如,利用存储单元1324)存储语音输入的一个或多个话语,所述一个或多个话语对应于第一字符、用于识别第二字符的短语,以及字词。
以上参考图13描述的操作任选地由图1、图2A、图4、图6A-图6B、图7A、图8A-图8B或图9中描绘的部件来实现。例如,接收操作1310,识别操作1312,转换操作1314以及致使操作1316任选地由处理器220实现。本领域的普通技术人员会清楚地知道如何可基于在图1、图2A、图4、图6A-图6B、图7A、图8A-图8B或图9中所描绘的部件来实现其他过程。
本领域的技术人员应当理解,图13中所述的功能块任选地被组合或被分离为子块,以便实现各种所描述的实施方案的原理。因此,本文的描述可选地支持本文描述的功能块的任何可能的组合或分离或进一步的定义。例如,处理单元1308可具有相关联的“控制器”单元,其可操作地与处理单元1308耦接在一起以启用操作。该控制器单元在图13中未单独示出,但应当理解,其在设计了具有处理单元1308的设备(诸如设备1300)的本领域普通技术人员的掌握之中。又如,在一些实施例中,诸如接收单元1310的一个或多个单元,可以是不同于一些实施方案中的处理单元1308的硬件单元。因此,本文的描述任选地支持本文所述的功能块的任何可能的组合、分离或进一步限定。
出于解释的目的,前面的描述是参考具体的实施方案来描述的。然而,上面的示例性讨论并非旨在是穷尽的,也并非旨在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。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。

Claims (40)

1.一种用于识别提供一个或多个用户凭据的语音输入的方法,包括:
在具有显示器、一个或多个处理器和存储器的用户设备处:
接收语音输入,所述语音输入包括一个或多个字符、一个或多个短语、和一个或多个字词的组合;
基于单个语音输入,识别第一字符、用于识别第二字符的短语、以及字词,其中识别所述第一字符、所述短语、或所述字词包括:
识别所述语音输入的话语;
确定所述话语的类型;以及
基于所述话语的所确定的类型,获得对应于所述话语的所述第一字符、由所述短语识别的所述第二字符、或所述字词的表示;
响应于所述识别,将所述第一字符、所述第二字符和所述字词转换为文本;以及
使得利用所述显示器以对应于所述第一字符、所述第二字符和所述字词在所述语音输入中的次序的序列来显示所述文本。
2.根据权利要求1所述的方法,其中所述第一字符包括字母、数字、控制字符或空格中的至少一者。
3.根据权利要求2所述的方法,其中所述控制字符包括由标点字词所识别的标点符号。
4.根据权利要求1所述的方法,其中所述短语包括用于辅助识别所述第二字符的拼写字词。
5.根据权利要求1所述的方法,其中所述字词包括多个字符。
6.根据权利要求5所述的方法,其中所述多个字符表示域扩展名或首字母缩略词中的至少一者。
7.根据权利要求1所述的方法,其中基于所述单个语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、和所述字词包括:
基于存储在所述用户设备中的一个或多个语音识别模型,识别所述第一字符、用于识别所述第二字符的所述短语、或所述字词中的至少一者。
8.根据权利要求1所述的方法,其中基于所述语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、和所述字词包括:
向服务器提供表示所述语音输入的数据;以及
从所述服务器接收表示所述第一字符、用于识别所述第二字符的所述短语、或所述字词中的至少一者的数据,
其中基于所述语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词包括
基于存储在所述服务器中的一个或多个语言模型,识别所述第一字符、用于识别所述第二字符的所述短语、或所述字词中的至少一者。
9.根据权利要求1所述的方法,其中确定所述话语的类型包括执行以下各项中的至少一者:
确定所述话语的类型是否对应于字符;
确定所述话语的类型是否对应于用于识别字符的短语;以及
确定所述话语的类型是否对应于字词。
10.根据权利要求9所述的方法,其中确定所述话语的类型是否对应于字符包括:
针对所述话语,确定所述话语是否对应于控制字符;
根据确定所述话语对应于控制字符,针对所述话语确定所述话语是否对应于标点字词;以及
其中基于所述话语的所确定的类型,获得所述字符的表示包括:
根据确定所述话语对应于标点字词,获得对应于所述标点字词的标点符号的表示,
根据确定所述话语不对应于标点字词,获得不同于标点字词的所述控制字符的表示。
11.根据权利要求1所述的方法,其中基于所述单个语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词进一步包括:
获得所述表示的置信水平;
确定所述置信水平是否大于或等于阈值;并且
其中将所述第一字符、所述第二字符和所述字词转换为文本包括:
根据确定所述置信水平大于或等于所述阈值,将对应于所述话语的所述第一字符、由所述短语识别的所述第二字符、或所述字词的所述表示转换为文本;
根据确定所述置信水平小于所述阈值,提供一个或多个候选表示、错误消息或它们的组合。
12.根据权利要求1所述的方法,还包括:
基于所述单个语音输入,识别至少一个命令,其中所述至少一个命令使得能够编辑所显示的文本。
13.根据权利要求12所述的方法,其中识别所述至少一个命令包括:
识别至少一个话语;
确定所述话语的类型是否对应于命令;并且
根据确定所述话语的类型对应于命令,使得发起与用于编辑所显示的文本的所述命令对应的动作。
14.根据权利要求13所述的方法,还包括:
存储对应于所述至少一个命令的所述话语,并且存储与对应于所述至少一个命令的所述话语相关联的信息。
15.根据权利要求1所述的方法,其中基于所述单个语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词基于与用户相关联的上下文数据或一个或多个所识别的凭据模型中的至少一者。
16.根据权利要求15所述的方法,其中与所述用户相关联的所述上下文数据包括用户语音配置文件。
17.根据权利要求15所述的方法,其中所述一个或多个所识别的凭据模型表示一个或多个所识别的凭据格式。
18.根据权利要求1所述的方法,其中基于所述语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词基于注视检测。
19.根据权利要求1所述的方法,其中所述语音输入对应于表示用户名的第一用户凭据或表示密码的第二用户凭据中的至少一者。
20.根据权利要求1所述的方法,还包括:
存储所述语音输入的一个或多个话语,所述一个或多个话语对应于基于所述识别而识别的所述第一字符、用于识别所述第二字符的所述短语、以及所述字词。
21.一种电子设备,包括:
处理单元,所述处理单元被配置为:
接收语音输入,所述语音输入包括一个或多个字符、一个或多个短语、和一个或多个字词的组合;
基于单个语音输入,识别第一字符、用于识别第二字符的短语、以及字词,其中识别所述第一字符、所述短语、或所述字词包括:
识别所述语音输入的话语;
确定所述话语的类型;以及
基于所述话语的所确定的类型,获得对应于所述话语的所述第一字符、由所述短语识别的所述第二字符、或所述字词的表示;
响应于所述识别,将所述第一字符、所述第二字符和所述字词转换为文本;并且
使得以对应于所述第一字符、所述第二字符和所述字词在所述语音输入中的次序的序列来显示所述文本。
22.根据权利要求21所述的电子设备,其中所述第一字符包括字母、数字、控制字符或空格中的至少一者。
23.根据权利要求22所述的电子设备,其中所述控制字符包括由标点字词所识别的标点符号。
24.根据权利要求21所述的电子设备,其中所述短语包括用于辅助识别所述第二字符的拼写字词。
25.根据权利要求21所述的电子设备,其中所述字词包括多个字符。
26.根据权利要求25所述的电子设备,其中所述多个字符表示域扩展名或首字母缩略词中的至少一者。
27.根据权利要求21所述的电子设备,其中基于所述语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词包括:
基于存储在所述电子设备中的一个或多个语音识别模型,识别所述第一字符、用于识别所述第二字符的所述短语、或所述字词中的至少一者。
28.根据权利要求21所述的电子设备,其中基于所述单个语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词包括:
向服务器提供表示所述语音输入的数据;以及
从所述服务器接收表示所述第一字符、用于识别所述第二字符的所述短语、或所述字词中的至少一者的数据,
其中基于所述语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词包括
基于存储在所述服务器中的一个或多个语言模型,识别所述第一字符、用于识别所述第二字符的所述短语、或所述字词中的至少一者。
29.根据权利要求21所述的电子设备,其中确定所述话语的类型包括执行以下各项中的至少一者:
确定所述话语的类型是否对应于字符;
确定所述话语的类型是否对应于用于识别字符的短语;以及
确定所述话语的类型是否对应于字词。
30.根据权利要求29所述的电子设备,其中确定所述话语的类型是否对应于字符包括:
针对所述话语,确定所述话语是否对应于控制字符;
根据确定所述话语对应于控制字符,针对所述话语确定所述话语是否对应于标点字词;以及
其中基于所述话语的所确定的类型,获得所述字符的表示包括:
根据确定所述话语对应于标点字词,获得对应于所述标点字词的标点符号的表示,
根据确定所述话语不对应于标点字词,获得不同于标点字词的所述控制字符的表示。
31.根据权利要求21所述的电子设备,其中基于所述单个语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词进一步包括:
获得所述表示的置信水平;
确定所述置信水平是否大于或等于阈值;并且
其中将所述第一字符、所述第二字符和所述字词转换为文本包括:
根据确定所述置信水平大于或等于所述阈值,将对应于所述话语的所述第一字符、由所述短语识别的所述第二字符、或所述字词的所述表示转换为文本;
根据确定所述置信水平小于所述阈值,提供一个或多个候选表示、错误消息或它们的组合。
32.根据权利要求21所述的电子设备,其中所述处理单元被进一步配置为:
基于所述单个语音输入,识别至少一个命令,其中所述至少一个命令使得能够编辑所显示的文本。
33.根据权利要求32所述的电子设备,其中识别所述至少一个命令包括:
识别至少一个话语;
确定所述话语的类型是否对应于命令;并且
根据确定所述话语的类型对应于命令,使得发起与用于编辑所显示的文本的所述命令对应的动作。
34.根据权利要求33所述的电子设备,其中所述处理单元被进一步配置为:
存储对应于所述至少一个命令的所述话语,并且存储与对应于所述至少一个命令的所述话语相关联的信息。
35.根据权利要求21所述的电子设备,其中基于所述单个语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词基于与用户相关联的上下文数据或一个或多个所识别的凭据模型中的至少一者。
36.根据权利要求35所述的电子设备,其中与所述用户相关联的所述上下文数据包括用户语音配置文件。
37.根据权利要求35所述的电子设备,其中所述一个或多个所识别的凭据模型表示一个或多个所识别的凭据格式。
38.根据权利要求21所述的电子设备,其中基于所述语音输入,识别所述第一字符、用于识别所述第二字符的所述短语、以及所述字词基于注视检测。
39.根据权利要求21所述的电子设备,其中所述语音输入对应于表示用户名的第一用户凭据或表示密码的第二用户凭据中的至少一者。
40.根据权利要求21所述的电子设备,还包括:
存储所述语音输入的一个或多个话语,所述一个或多个话语对应于基于所述识别而识别的所述第一字符、用于识别所述第二字符的所述短语、以及所述字词。
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