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公开(公告)号：US20160364385A1
公开(公告)日：2016-12-15
申请号：US15249068
申请日：2016-08-26
Applicant: Facebook, Inc.
Inventor： Naomi Aoki Waibel , Alexander Waibel , Christian Fuegen , Kay Rottmann
CPC classification number: G06F17/289 , G10L13/00 , G10L13/02 , G10L15/30
Abstract: A hybrid speech translation system whereby a wireless-enabled client computing device can, in an offline mode, translate input speech utterances from one language to another locally, and also, in an online mode when there is wireless network connectivity, have a remote computer perform the translation and transmit it back to the client computing device via the wireless network for audible outputting by client computing device. The user of the client computing device can transition between modes or the transition can be automatic based on user preferences or settings. The back-end speech translation server system can adapt the various recognition and translation models used by the client computing device in the offline mode based on analysis of user data over time, to thereby configure the client computing device with scaled-down, yet more efficient and faster, models than the back-end speech translation server system, while still be adapted for the user's domain.
Abstract translation: 一种混合语音翻译系统，其中无线使能的客户端计算设备可以在离线模式下将输入语音话语从一种语言本地转换为另一种语言，并且还可以在存在无线网络连接的在线模式中具有远程计算机执行 翻译并经由无线网络将其发送回客户端计算设备，以便客户端计算设备进行声音输出。 客户端计算设备的用户可以在模式之间切换，也可以根据用户偏好或设置自动切换。 后端语音翻译服务器系统可以基于用户数据随时间的分析，在离线模式下适应客户端计算设备所使用的各种识别和翻译模型，从而使客户端计算设备按比例缩小但更有效率 而且比后端语音翻译服务器系统的模型更快，同时仍然适应用户的领域。
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公开(公告)号：US10902221B1
公开(公告)日：2021-01-26
申请号：US15199890
申请日：2016-06-30
Applicant: Facebook, Inc.
Inventor： Ying Zhang , Christian Fuegen , Guillaume Lample , Jing Zheng
Abstract: Components of language processing engines, such as translation models and language models, can be customized for groups of users or based on user type values. Users can be organized into groups or assigned a value on a continuum based on factors such as interests, biographical characteristics, social media interactions, etc. In some implementations, translation engine components can be customized for groups of users by selecting the training data from content created by users in that group. In some implementations, the group identifier or continuum value can be part of the input into a general translation component allowing the translation component to take a language style of that user group into account when performing language processing tasks.
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公开(公告)号：US20160188727A1
公开(公告)日：2016-06-30
申请号：US14588298
申请日：2014-12-31
Applicant: Facebook, Inc.
Inventor： Alexander Waibel , Christian Fuegen , Thilo Wolfgang Koehler
CPC classification number: G06F17/30867 , G06F17/30528 , G09B5/06 , G09B7/00 , G09B19/04 , H04L67/306
Abstract: A social networking system obtains user pronunciations of terms whose pronunciations might vary among different users, such as names of users. The social networking system additionally obtains demographic information about the users from whom the pronunciations were obtained, as well as social graph information for those users, such as information about connections of those users in the social graph. Based on the obtained pronunciations, the demographic information, and the social graph information, the social networking system determines, for a user having that name (or other term in question), one or more suggested pronunciations for the name that are likely to be the pronunciations that that user would use.
Abstract translation: 社交网络系统获得用户的发音，其发音可能在不同用户之间变化，例如用户名称。 社交网络系统还获得关于获得发音的用户的人口统计信息，以及这些用户的社交图表信息，例如社交图中用户的连接信息。 基于获得的发音，人口统计信息和社交图表信息，社交网络系统为具有该名称（或其他术语的用户）的用户确定对于可能是该名称的名称的一个或多个建议发音 该用户将使用的发音。
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公开(公告)号：US11107462B1
公开(公告)日：2021-08-31
申请号：US16175086
申请日：2018-10-30
Applicant: Facebook, Inc.
Inventor： Christian Fuegen , Yongquiang Wang , Anuj Kumar , Baiyang Liu , Dmitrii Serdiuk
Abstract: Exemplary embodiments relate to improvements in spoken language understanding (SLU) systems. Conventionally, SLU systems include an automatic speech recognition (ASR) component configured to receive an input of audio data and to generate a textual representation of the audio data. Conventional SLU systems also include a natural language understanding (NLU) component configured to receive a text-based transcript and perform language-based tasks such as domain classification, intent determination, and slot-filling. However, these two components are typically trained separately based on different metrics. In real-world situations, errors in the ASR component propagate to the NLU component, which degrades the performance of the overall system. Exemplary embodiments described herein perform SLU in an end-to-end manner that infers semantic meaning directly from audio features without an intermediate text representation. This may allow for more a more accurate translation performed in a more resource-efficient manner (particularly in terms of processing resources).
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Patent Agency Ranking
公开(公告)号：US10061855B2
公开(公告)日：2018-08-28
申请号：US14588298
申请日：2014-12-31
Applicant: Facebook, Inc.
Inventor： Alexander Waibel , Christian Fuegen , Thilo Wolfgang Koehler
CPC classification number: G06F16/9535 , G06F16/24575 , G09B5/06 , G09B7/00 , G09B19/04 , H04L67/306
Abstract: A social networking system obtains user pronunciations of terms whose pronunciations might vary among different users, such as names of users. The social networking system additionally obtains demographic information about the users from whom the pronunciations were obtained, as well as social graph information for those users, such as information about connections of those users in the social graph. Based on the obtained pronunciations, the demographic information, and the social graph information, the social networking system determines, for a user having that name (or other term in question), one or more suggested pronunciations for the name that are likely to be the pronunciations that that user would use.
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公开(公告)号：US10902215B1
公开(公告)日：2021-01-26
申请号：US15244179
申请日：2016-08-23
Applicant: Facebook, Inc.
Inventor： Ying Zhang , Christian Fuegen , Guillaume Lample , Jing Zheng
Abstract: Components of language processing engines, such as translation models and language models, can be customized for groups of users or based on user type values. Users can be organized into groups or assigned a value on a continuum based on factors such as interests, biographical characteristics, social media interactions, etc. In some implementations, translation engine components can be customized for groups of users by selecting the training data from content created by users in that group. In some implementations, the group identifier or continuum value can be part of the input into a general translation component allowing the translation component to take a language style of that user group into account when performing language processing tasks.
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公开(公告)号：US10331794B2
公开(公告)日：2019-06-25
申请号：US15249068
申请日：2016-08-26
Applicant: Facebook, Inc.
Inventor： Naomi Aoki Waibel , Alexander Waibel , Christian Fuegen , Kay Rottmann
Abstract: A hybrid speech translation system whereby a wireless-enabled client computing device can, in an offline mode, translate input speech utterances from one language to another locally, and also, in an online mode when there is wireless network connectivity, have a remote computer perform the translation and transmit it back to the client computing device via the wireless network for audible outputting by client computing device. The user of the client computing device can transition between modes or the transition can be automatic based on user preferences or settings. The back-end speech translation server system can adapt the various recognition and translation models used by the client computing device in the offline mode based on analysis of user data over time, to thereby configure the client computing device with scaled-down, yet more efficient and faster, models than the back-end speech translation server system, while still be adapted for the user's domain.
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公开(公告)号：US09430465B2
公开(公告)日：2016-08-30
申请号：US13915820
申请日：2013-06-12
Applicant: Facebook, Inc.
Inventor： Naomi Aoki Waibel , Alexander Waibel , Christian Fuegen , Kay Rottman
CPC classification number: G06F17/289 , G10L13/00 , G10L13/02 , G10L15/30
Abstract: A hybrid speech translation system whereby a wireless-enabled client computing device can, in an offline mode, translate input speech utterances from one language to another locally, and also, in an online mode when there is wireless network connectivity, have a remote computer perform the translation and transmit it back to the client computing device via the wireless network for audible outputting by client computing device. The user of the client computing device can transition between modes or the transition can be automatic based on user preferences or settings. The back-end speech translation server system can adapt the various recognition and translation models used by the client computing device in the offline mode based on analysis of user data over time, to thereby configure the client computing device with scaled-down, yet more efficient and faster, models than the back-end speech translation server system, while still be adapted for the user's domain.
Abstract translation: 一种混合语音翻译系统，其中无线使能的客户端计算设备可以在离线模式下将输入语音话语从一种语言本地转换为另一种语言，并且还可以在存在无线网络连接的在线模式中具有远程计算机执行 翻译并经由无线网络将其发送回客户端计算设备，以便客户端计算设备进行声音输出。 客户端计算设备的用户可以在模式之间切换，也可以根据用户偏好或设置自动切换。 后端语音翻译服务器系统可以基于用户数据随时间的分析，在离线模式下适应客户端计算设备所使用的各种识别和翻译模型，从而使客户端计算设备按比例缩小但更有效率 而且比后端语音翻译服务器系统的模型更快，同时仍然适应用户的领域。
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公开(公告)号：US20140337007A1
公开(公告)日：2014-11-13
申请号：US13915820
申请日：2013-06-12
Applicant: Facebook, Inc.
Inventor： Naomi Aoki Waibel , Alexander Waibel , Christian Fuegen , Kay Rottmann
IPC: G06F17/28
CPC classification number: G06F17/289 , G10L13/00 , G10L13/02 , G10L15/30
Abstract: A hybrid speech translation system whereby a wireless-enabled client computing device can, in an offline mode, translate input speech utterances from one language to another locally, and also, in an online mode when there is wireless network connectivity, have a remote computer perform the translation and transmit it back to the client computing device via the wireless network for audible outputting by client computing device. The user of the client computing device can transition between modes or the transition can be automatic based on user preferences or settings. The back-end speech translation server system can adapt the various recognition and translation models used by the client computing device in the offline mode based on analysis of user data over time, to thereby configure the client computing device with scaled-down, yet more efficient and faster, models than the back-end speech translation server system, while still be adapted for the user's domain.
Abstract translation: 一种混合语音翻译系统，其中无线使能的客户端计算设备可以在离线模式下将输入的语音话语从一种语言本地转换到另一种语言，并且在存在无线网络连接的在线模式中，远程计算机执行 翻译并经由无线网络将其发送回客户端计算设备，以便客户端计算设备进行声音输出。 客户端计算设备的用户可以在模式之间切换，也可以根据用户偏好或设置自动切换。 后端语音翻译服务器系统可以基于用户数据随时间的分析，在离线模式下适应客户端计算设备所使用的各种识别和翻译模型，从而使客户端计算设备按比例缩小但更有效率 而且比后端语音翻译服务器系统的模型更快，同时仍然适应用户的领域。
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