公开(公告)号：US12045568B1

公开(公告)日：2024-07-23

申请号：US17525510

申请日：2021-11-12

Applicant: Meta Platforms, Inc.

Inventor： Akshat Shrivastava ,  Pierce I-Jen Chuang ,  Arun Babu ,  Shrey Desai ,  Abhinav Arora ,  Alexander Kolmykov-Zotov ,  Ahmed Aly

IPC: G06F40/284 ,  G06F40/205 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22 ,  G10L15/30

CPC classification number: G06F40/284 ,  G06F40/205 ,  G06F40/30 ,  G10L15/1815 ,  G10L15/1822 ,  G10L15/22 ,  G10L15/30 ,  G10L2015/223

Abstract: In one embodiment, a method includes receiving a user input comprising input tokens from a client system, parsing the user input to determine ontology tokens and utterance tokens corresponding to the input tokens, decoding the ontology tokens and the utterance tokens to generate a span-based frame representation comprising intents, slots, and a span, wherein the ontology tokens are decoded into the intents and slots, and wherein the utterance tokens are decoded to determine the span comprising one or more tokens of the input tokens, wherein the span comprises a first index endpoint associated with a first token of the one or more tokens and a second index endpoint associated with a second token of the one or more tokens, and executing, responsive to the user input, one or more tasks based on the span-based frame representation.

公开(公告)号：US20250005283A1

公开(公告)日：2025-01-02

申请号：US18742040

申请日：2024-06-13

Applicant: Meta Platforms, Inc.

Inventor： Akshat Shrivastava ,  Pierce I-Jen Chuang ,  Arun Babu ,  Shrey Desai ,  Abhinav Arora ,  Alexander Kolmykov-Zotov ,  Ahmed Aly

IPC: G06F40/284 ,  G06F40/205 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22 ,  G10L15/30

Abstract: A method includes receiving from a client system a user input having input tokens and generating a span-based frame representation based on the input tokens. The span-based frame representation may include intents, slots, and a span. The span may include a first index endpoint associated with a first token and a second index endpoint associated with a second token. The method further includes encoding the user input, based on an encoder of a natural language understanding module, to generate a feature vector for the user input, and determining, by a length module of the natural language understanding module, a length of the span-based frame representation based on the feature vector for the user input. Generating the span-based frame representation may be further based on the length of the span-based frame representation. The method further includes, responsive to the user input, executing tasks based on the span-based frame representation.

公开(公告)号：US20220374605A1

公开(公告)日：2022-11-24

申请号：US17351501

申请日：2021-06-18

Applicant: Meta Platforms, Inc.

Inventor： Pooja Sethi ,  Denis Savenkov ,  Yue Liu ,  Alexander Kolmykov-Zotov ,  Ahmed Aly

IPC: G06F40/30

Abstract: In one embodiment, a method includes receiving a user request to automatically debug a natural-language understanding (NLU) model, accessing a plurality of predicted semantic representations generated by the NLU model, wherein the plurality of predicted semantic representations are associated with a plurality of dialog sessions, respectively, wherein each dialog session is between a user and an assistant xbot associated with the NLU model, generating a plurality of expected semantic representations associated with the plurality of dialog sessions based on an auto-correction model, wherein the auto-correction model is learned from dialog training samples generated based on active learning, identifying incorrect semantic representations of the predicted semantic representations based on a comparison between the predicted semantic representations and the expected semantic representations, and automatically correcting the incorrect semantic representations by replacing them with respective expected semantic representations generated by the auto-correction model.

公开(公告)号：US11861315B2

公开(公告)日：2024-01-02

申请号：US17351501

申请日：2021-06-18

Applicant: Meta Platforms, Inc.

Inventor： Pooja Sethi ,  Denis Savenkov ,  Yue Liu ,  Alexander Kolmykov-Zotov ,  Ahmed Aly

IPC: G06F17/00 ,  G06F40/30 ,  G06F1/3206 ,  G06F3/01 ,  G06F3/04815 ,  G06N5/02 ,  G06N5/046 ,  G06T19/00 ,  G06T19/20

CPC classification number: G06F40/30 ,  G06F1/3206 ,  G06F3/011 ,  G06F3/04815 ,  G06N5/02 ,  G06N5/046 ,  G06T19/006 ,  G06T19/20 ,  G06T2219/2004

Abstract: In one embodiment, a method includes receiving a user request to automatically debug a natural-language understanding (NLU) model, accessing a plurality of predicted semantic representations generated by the NLU model, wherein the plurality of predicted semantic representations are associated with a plurality of dialog sessions, respectively, wherein each dialog session is between a user and an assistant xbot associated with the NLU model, generating a plurality of expected semantic representations associated with the plurality of dialog sessions based on an auto-correction model, wherein the auto-correction model is learned from dialog training samples generated based on active learning, identifying incorrect semantic representations of the predicted semantic representations based on a comparison between the predicted semantic representations and the expected semantic representations, and automatically correcting the incorrect semantic representations by replacing them with respective expected semantic representations generated by the auto-correction model.

公开(公告)号：US20230245654A1

公开(公告)日：2023-08-03

申请号：US18157413

申请日：2023-01-20

Applicant: Meta Platforms, Inc.

Inventor： Akshat Shrivastava ,  Shrey Desai ,  Anchit Gupta ,  Ali Elkahky ,  Aleksandr Livshits ,  Alexander Kolmykov-Zotov ,  Ahmed Aly ,  Jinsong Yu ,  Manali Anand Naik ,  Shuhui Yang ,  Baiyang Liu ,  Surya Teja Appini ,  Tarun Vir Singh ,  Hang Su ,  Jiedan Zhu ,  Fuchun Peng ,  Shoubhik Bhattacharya ,  Kshitiz Malik ,  Shreyan Bakshi ,  Akash Bharadwaj ,  Harish Srinivas ,  Xiao Yang ,  Zhuangqun Huang ,  Gil Keren ,  Duc Hoang Le ,  Ahmed Kamal Atwa Mohamed ,  Zhe Liu ,  Pranab Mohanty

IPC: G10L15/22 ,  G10L15/18 ,  G10L15/30 ,  G10L15/06 ,  G10L15/197 ,  H04L9/40

CPC classification number: G10L15/22 ,  G10L15/1815 ,  G10L15/30 ,  G10L15/063 ,  G10L15/197 ,  H04L63/0428 ,  G10L2015/223 ,  G10L2015/086

Abstract: In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.