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公开(公告)号:US20230237275A1
公开(公告)日:2023-07-27
申请号:US17830889
申请日:2022-06-02
Applicant: salesforce.com, inc.
Inventor: Guangsen Wang , Samson Min Rong Tan , Shafiq Rayhan Joty , Gang Wu , Chu Hong Hoi , Ka Chun Au
IPC: G06F40/35 , G06F40/40 , H04L51/02 , G06F40/186
CPC classification number: G06F40/35 , G06F40/40 , H04L51/02 , G06F40/186
Abstract: Embodiments provide a software framework for evaluating and troubleshooting real-world task-oriented bot systems. Specifically, the evaluation framework includes a generator that infers dialog acts and entities from bot definitions and generates test cases for the system via model-based paraphrasing. The framework may also include a simulator for task-oriented dialog user simulation that supports both regression testing and end-to-end evaluation. The framework may also include a remediator to analyze and visualize the simulation results, remedy some of the identified issues, and provide actionable suggestions for improving the task-oriented dialog system.
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公开(公告)号:US20220108688A1
公开(公告)日:2022-04-07
申请号:US17162624
申请日:2021-01-29
Applicant: salesforce.com, inc.
Inventor: Guangsen Wang , Chu Hong Hoi , Genta Indra Winata
IPC: G10L15/16 , G10L15/065 , G10L15/06 , G06N3/04 , G06N3/08
Abstract: Embodiments described herein provide an Adapt-and-Adjust (A2) mechanism for multilingual speech recognition model that combines both adaptation and adjustment methods as an integrated end-to-end training to improve the models' generalization and mitigate the long-tailed issue. Specifically, a multilingual language model mBERT is utilized, and converted into an autoregressive transformer decoder. In addition, a cross-attention module is added to the encoder on top of the mBERT's self-attention layer in order to explore the acoustic space in addition to the text space. The joint training of the encoder and mBERT decoder can bridge the semantic gap between the speech and the text.
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公开(公告)号:US11798534B2
公开(公告)日:2023-10-24
申请号:US17162624
申请日:2021-01-29
Applicant: salesforce.com, inc.
Inventor: Guangsen Wang , Chu Hong Hoi , Genta Indra Winata
IPC: G10L15/16 , G10L15/065 , G06N3/08 , G06N3/04 , G10L15/06
CPC classification number: G10L15/16 , G06N3/04 , G06N3/08 , G10L15/063 , G10L15/065
Abstract: Embodiments described herein provide an Adapt-and-Adjust (A2) mechanism for multilingual speech recognition model that combines both adaptation and adjustment methods as an integrated end-to-end training to improve the models' generalization and mitigate the long-tailed issue. Specifically, a multilingual language model mBERT is utilized, and converted into an autoregressive transformer decoder. In addition, a cross-attention module is added to the encoder on top of the mBERT's self-attention layer in order to explore the acoustic space in addition to the text space. The joint training of the encoder and mBERT decoder can bridge the semantic gap between the speech and the text.
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