公开(公告)号：US12175966B1

公开(公告)日：2024-12-24

申请号：US17361003

申请日：2021-06-28

Applicant: Amazon Technologies, Inc.

Inventor： Yi-An Lai ,  Yi Zhang ,  Roger Scott Jenke ,  Meghana Puvvadi ,  Shang-Wen Daniel Li ,  Peng Zhang ,  Jason P. Krone ,  Garima Lalwani ,  Niranjhana Nayar ,  Kartik Natarajan

IPC: G10L15/22 ,  G06N5/04 ,  G06N20/00 ,  G10L15/06 ,  G10L15/18 ,  H04L51/02 ,  G10L15/16

Abstract: Techniques for updating a machine learning model based on user interactions are described. In particular, in some examples, user interactions with a chatbot provide aspects of a data set to be used to train or fine-tune a ML model. In some examples, this is accomplished by collecting data from a first plurality of interactions with a machine learning (ML) model; generating a variant of the ML model using the collected data by: filtering the collected data to create a first data set, training the ML model based on the first data set to generate an adapted ML model, and fine-tuning the adapted ML model on a second data set, different than the first data set to generate the variant of the ML model.

公开(公告)号：US11580968B1

公开(公告)日：2023-02-14

申请号：US16455165

申请日：2019-06-27

Applicant: Amazon Technologies, Inc.

Inventor： Arshit Gupta ,  Peng Zhang ,  Rashmi Gangadharaiah ,  Garima Lalwani ,  Roger Scott Jenke ,  Hassan Sawaf ,  Mona Diab ,  Katrin Kirchhoff ,  Adel A. Youssef ,  Kalpesh N. Sutaria

IPC: G10L15/08 ,  G10L15/16 ,  G10L15/22 ,  H04L67/02 ,  G10L15/18 ,  G10L15/02

Abstract: Techniques are described for a contextual natural language understanding (cNLU) framework that is able to incorporate contextual signals of variable history length to perform joint intent classification (IC) and slot labeling (SL) tasks. A user utterance provided by a user within a multi-turn chat dialog between the user and a conversational agent is received. The user utterance and contextual information associated with one or more previous turns of the multi-turn chat dialog is provided to a machine learning (ML) model. An intent classification and one or more slot labels for the user utterance are then obtained from the ML model. The cNLU framework described herein thus uses, in addition to a current utterance itself, various contextual signals as input to a model to generate IC and SL predictions for each utterance of a multi-turn chat dialog.

公开(公告)号：US11568145B1

公开(公告)日：2023-01-31

申请号：US17038506

申请日：2020-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Salvatore Romeo ,  Yi Zhang ,  Garima Lalwani ,  Meghana Puvvadi ,  Rama Krishna Sandeep Pokkunuri

IPC: G06F40/289 ,  G06F40/40 ,  H04L51/04

Abstract: Systems, methods, and apparatuses for contextual natural language understanding are detailed. An exemplary method includes receiving a user utterance provided by a user within a multi-turn chat dialog between the user and a conversational agent; providing to a contextual natural language understanding framework: the user utterance, and contextual information associated with one or more previous turns of the multi-turn chat dialog, the contextual information associated with each turn of the one or more previous turns including a previous intent, a previous dialog act, and an elicited slot; and obtaining, from the contextual natural language understanding framework, an intent classification and one or more slot labels.