IP Library Granted Patent US 12,400,072
Granted Patent B2
US 12,400,072 · App. 18/156,043 · Granted Aug 26, 2025

Systems and methods for structured conversation summarization

Inventors: Victor Yee (Oakland, CA); Chien-Sheng Wu (Mountain View, CA); Na Cheng (Yarrow Point, WA); Alexander R. Fabbri (New York, NY); Zachary Alexander (Berkeley, CA); Nicholas Feinig (San Francisco, CA); Sameer Abhinkar (San Francisco, CA); Shashank Harinath (Mountain View, CA); Sitaram Asur (Newark, CA); Jacob Nathaniel Huffman (San Francisco, CA); Wojciech Kryscinski (Palo Alto, CA); Caiming Xiong (Menlo Park, CA)
Assignee: Salesforce, Inc.
G06F40/174G06F16/345
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Quick Facts
Patent No.
US 12,400,072
App. No.
18/156,043
Granted
Aug 26, 2025
Kind
B2
Abstract

Embodiments described herein provide a structured conversation summarization framework. A user interface may be provided which allows an agent to perform a conversation with a customer, for example regarding resolving a customer support issue. Utterances by both the agent and customer may be stored, and at the end of the conversation, the utterances may be used to generate a structured summary. The structured summary may include components such as a general summary, an issue summary, and a resolution summary. Using neural network models and heuristics, each component of the summary may be automatically generated.

Claims (65)

1. A method of structured summarization of user-agent interactions on a service platform, the method comprising:

receiving, via a user interface, a plurality of user utterances;

generating, by a service agent and via the user interface, a plurality of responses in response to the plurality of user utterances, respectively;

retrieving a structured summary form based on a conversation topic of the plurality of user utterances and the plurality of responses;

generating, by a summarization model trained on a dataset of dialogue data and annotated reference summaries, a summary of the plurality of user utterances and the plurality of responses;

determining, for an issue summary field on the structured summary form, a first utterance selected from the plurality of user utterances as an issue summary based on ranking similarities between the summary and a subset of user utterances selected from the plurality of user utterances, respectively;

determining, for a resolution summary field on the structured summary form, a first response selected from the plurality of responses as a resolution summary based on a subset of responses selected from the plurality of responses; and

generating an engageable user interface element including data fields of the structured summary form incorporating the issue summary and the resolution summary.

2. The method of claim 1 , wherein retrieving the structured summary form comprises:

obtaining a user selected conversation topic through the user interface; and

querying a summary form database based on the user selected conversation topic.

3. The method of claim 1 , wherein generating, by the summarization model, the summary comprises:

concatenating the plurality of user utterances and the plurality of responses into an input sequence of tokens; and

generating, by the summarization model, the summary based on the input sequence of tokens.

4. The method of claim 1 , wherein determining the first utterance as the issue summary comprises:

filtering the plurality of user utterances based on relevance into the subset of user utterances;

encoding, via a sentence Transformer model, the subset of user utterances into a first plurality of utterance representations;

encoding, via the sentence Transformer model, the summary into a summary representation;

computing a set of cosine similarities between the summary representation and the first plurality of utterance representations, respectively; and

selecting the first utterance corresponding to a greatest cosine similarity with the summary representation.

5. The method of claim 4 , further comprising:

generating, via the summarization model, the issue summary based on the first utterance.

6. The method of claim 1 , wherein determining the first response as the resolution summary comprises:

selecting the first response from the subset of responses based on lengths of responses and heuristics of past responses.

7. The method of claim 1 , wherein the subset of responses comprise a second half of the plurality of responses in time.

8. The method of claim 1 , wherein the structured summary form further comprises a field indicating whether an issue discussed during the user-agent interactions has been resolved, and wherein the field is generated using a prediction model trained on a dataset of dialogue data and annotated resolution results.

9. A system for structured summarization of user-agent interactions on a service platform, the system comprising:

a memory that stores a summarization model trained on a dataset of dialogue data and annotated reference summaries and a plurality of processor-executable instructions;

a communication interface that receives a plurality of user utterances; and

one or more hardware processors that read and execute the plurality of processor-executable instructions from the memory to perform operations comprising:

generating, via the communication interface, a plurality of responses in response to the plurality of user utterances, respectively;

retrieving a structured summary form based on a conversation topic of the plurality of user utterances and the plurality of responses;

generating, by the summarization model, a summary of the plurality of user utterances and the plurality of responses;

determining, for an issue summary field on the structured summary form, a first utterance selected from the plurality of user utterances as an issue summary based on ranking similarities between the summary and a subset of user utterances selected from the plurality of user utterances, respectively;

determining, for a resolution summary field on the structured summary form, a first response selected from the plurality of responses as a resolution summary based on a subset of responses selected from the plurality of responses; and

generating an engageable user interface element including data fields of the structured summary form incorporating the issue summary and the resolution summary.

10. The system of claim 9 , wherein retrieving the structured summary form comprises:

obtaining a user selected conversation topic through the communication interface; and

querying a summary form database based on the user selected conversation topic.

11. The system of claim 9 , wherein generating, by the summarization model, the summary comprises:

concatenating the plurality of user utterances and the plurality of responses into an input sequence of tokens; and

generating, by the summarization model, the summary based on the input sequence of tokens.

12. The system of claim 9 , wherein determining the first utterance as the issue summary comprises:

filtering the plurality of user utterances based on relevance into the subset of user utterances;

encoding, via a sentence Transformer model, the subset of user utterances into a first plurality of utterance representations;

encoding, via the sentence Transformer model, the summary into a summary representation;

computing a set of cosine similarities between the summary representation and the first plurality of utterance representations, respectively; and

selecting the first utterance corresponding to a greatest cosine similarity with the summary representation.

13. The system of claim 12 , the operations further comprising:

generating, via the summarization model, the issue summary based on the first utterance.

14. The system of claim 9 , wherein determining the first response as the resolution summary comprises:

selecting the first response from the subset of responses based on lengths of responses and heuristics of past responses.

15. The system of claim 9 , wherein the subset of responses comprise a second half of the plurality of responses in time.

16. The system of claim 9 , wherein the structured summary form further comprises a field indicating whether an issue discussed during the user-agent interactions has been resolved, and wherein the field is generated using a prediction model trained on a dataset of dialogue data and annotated resolution results.

17. A non-transitory machine-readable medium comprising a plurality of machine-executable instructions which, when executed by one or more processors, are adapted to cause the one or more processors to perform operations comprising:

receiving, via a user interface, a plurality of user utterances;

generating, via the user interface, a plurality of responses in response to the plurality of user utterances, respectively;

retrieving a structured summary form based on a conversation topic of the plurality of user utterances and the plurality of responses;

generating, by a summarization model trained on a dataset of dialogue data and annotated reference summaries, a summary of the plurality of user utterances and the plurality of responses;

determining, for an issue summary field on the structured summary form, a first utterance selected from the plurality of user utterances as an issue summary based on ranking similarities between the summary and a subset of user utterances selected from the plurality of user utterances, respectively;

determining, for a resolution summary field on the structured summary form, a first response selected from the plurality of responses as a resolution summary based on a subset of responses selected from the plurality of responses; and

generating an engageable user interface element including data fields of the structured summary form incorporating the issue summary and the resolution summary.

18. The non-transitory machine-readable medium of claim 17 , wherein retrieving the structured summary form comprises:

obtaining a user selected conversation topic through the user interface; and

querying a summary form database based on the user selected conversation topic.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 7, 2023
From: YEE, VICTOR; WU, CHIEN-SHENG; CHENG, NA; FABBRI, ALEXANDER R.; ALEXANDER, ZACHARY; FEINIG, NICHOLAS; ABHINKAR, SAMEER; HARINATH, SHASHANK; ASUR, SITARAM; HUFFMAN, JACOB NATHANIEL; KRYSCINSKI, WOJCIECH; XIONG, CAIMING
To: SALESFORCE, INC.
Reel/Frame 062902/0049 →
Continuity (1)
Related Publication 20240242022A1 · Jul 18, 2024
References Cited (14)
US 10803399B1 · Cohen · 2020 [cited by examiner]
US 11646032B2 · Balasubramaniam · 2023 [cited by examiner]
US 11823666B2 · Lavi · 2023 [cited by examiner]
US 12014144B2 · Fan · 2024 [cited by examiner]
US 20150162020A1 · Deshmukh · 2015 [cited by examiner]
US 20180260873A1 · Chandramouli · 2018 [cited by examiner]
US 20200195779A1 · Weisman · 2020 [cited by examiner]
US 20200250277A1 · Mallette · 2020 [cited by examiner]
US 20200349614A1 · Batcha · 2020 [cited by examiner]
US 20220261545A1 · Lauber · 2022 [cited by examiner]
US 20230360640A1 · Asi · 2023 [cited by examiner]
Biswas et al. “Extractive Summarization of Call Transcripts”. IEEE Access, vol. 10, 2022 (Year: 2022). [cited by examiner]
Seungone Kim, Se June Joo, Hyungjoo Chae, Chaehyeong Kim, Seung-won Hwang, Jinyoung Yeo, Mind the Gap! Injecting Commonsense Knowledge for Abstractive Dialogue Summarization, Proceedings of the 29th International Confer… [cited by applicant]
Yuejie Lei, Fujia Zheng, Yuanmeng Yan, Keqing He, Weiran Xu, A Finer-grain Universal Dialogue Semantic Structures based Model For Abstractive Dialogue Summarization, Findings of the Association for Computational Linguis… [cited by applicant]
Cited By (1)
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