公开(公告)号：US20250029612A1

公开(公告)日：2025-01-23

申请号：US18356117

申请日：2023-07-20

Applicant: Amazon Technologies, Inc.

Inventor： Lei Xu ,  Aparna Elangovan ,  Rohit Paturi ,  Sundararajan Srinivasan ,  Sravan BAbu Bodapati ,  Katrin Kirchoff ,  Sarthak Handa

IPC: G10L15/26 ,  G06F40/20

Abstract: Transcript generation as part of automatic speech recognition may be guided using section types. Audio data is received for transcription. An initial transcript of the audio data may be generated and evaluated to determine a section type for the audio data. The section type may then be used to focus generation of a second version of the transcript on one speaker over another speaker.

公开(公告)号：US20250005282A1

公开(公告)日：2025-01-02

申请号：US18344764

申请日：2023-06-29

Applicant: Amazon Technologies, Inc.

Inventor： John Colton Moriarty ,  Saket Dingliwal ,  Karthik Gopalakrishnan ,  Sravan Babu Bodapati ,  Katrin Kirchhoff ,  Lei Xu

IPC: G06F40/284 ,  G06F16/34

Abstract: Domain specialty instructions may be generated for performing text analysis tasks. An input text may be received for performing a text analysis task. One or more domain entities may be extracted from the input text using a machine learning model trained to recognize entities of a domain in a given text. The one or more domain entities may be inserted as part of generating instructions to perform the text analysis task using a pre-trained machine learning model fine-tuned to the domain. The pre-trained machine learning model may be caused to perform the text analysis task using the generated instructions and a result of the text analysis task may be provided.

公开(公告)号：US20240428002A1

公开(公告)日：2024-12-26

申请号：US18339749

申请日：2023-06-22

Applicant: Amazon Technologies, Inc.

Inventor： Aparna Elangovan ,  Lei Xu ,  Devang Kulshreshtha ,  Sravan Babu Bodapati ,  Katrin Kirchhoff ,  Sarthak Handa

IPC: G06F40/35 ,  G06F40/40

Abstract: A medical audio summarization service receives a medical conversation and an indication of a user preferred summarization style selected from a plurality of available summarization styles to generate a medical summary that conforms to the user preferred summarization style. A transcript is generated via a medical audio transcription service, and the transcript is used by a natural language processing engine (including a large language model) to generate the medical summary. The large language model is trained to be used to generate medical summaries that conform to respective ones of a plurality of user preferred summarization styles. The large language model is trained using training data comprising previously generated summaries and summary interaction metadata generated from user edits and/or feedback.