Method and system for a voice assisted quality inspection

Patent metadata

Field	Value
Publication number	US-2025259626-A1
Application number	US-202519049586-A
Country	US
Kind code	A1
Filing date	Feb 10, 2025
Priority date	Feb 14, 2024
Publication date	Aug 14, 2025
Grant date	—

Abstract

The embodiments of present disclosure herein address unresolved problems of handwritten notes or digital diaries for logging defects during quality inspection. Also, these kinds of inspections in the industries are time bound. In certain sensitive inspection cases inspectors are required to use gloves while inspecting which leads to added overhead of working with gloves while noting down the defects. Sharing of these defect logs also becomes difficult as they first must be digitized to be shared across the different units in the industry. Embodiments herein provide a method and system which logs the defects identified by inspectors using inspector's voice. The system identifies defect type, location and sub-section from inspector speech and marks the defect in an orthogonal view, a two-dimensional (2D) view, a three-dimensional (3D) view of the artifact being inspected for verification. The system also allows for marking the defects as resolved during the repair or rework process.

First claim

What is claimed is:

1 . A processor-implemented method comprising:
receiving, via an Input/Output (I/O) interface, one or more voice inputs from an inspector while inspecting an artifact, wherein the artifact is a physical entity subjected to inspection; pre-processing, via one or more hardware processors, the one or more voice inputs of the inspector to remove noise using a predefined filtering technique; converting, via the one or more hardware processors, the one or more pre-processed voice inputs into a predefined language text using a predefined language translation technique to ensure uniformity, wherein the predefined language translation technique includes a universal language model, and a custom speech model; transforming, via the one or more hardware processors, the predefined language text into one or more structured defects for a structured defect log on a domain model of artifact under inspection using a large language model (LLM); analyzing, via the one or more hardware processors, the structured defect log to map a defect name, a defect type, and a defect location to each sub-section of the physical entity represented in the domain model using the large language model (LLM); and converting, via the one or more hardware processors, the analyzed one or more structured defects into a voice format to facilitate an effective communication to a user for repair and for reporting purpose.

2 . The processor-implemented method of claim 1 , wherein a voice to text conversion model is integrated with the large language model and a domain model of artifact to convert one or more defects spoken by the inspector into the one or more structured defects represented by the domain model.

3 . The processor-implemented method of claim 1 , wherein the defect type, the defect location and the sub-section of the artifact is identified from the one or more voice inputs from the inspector.

4 . The processor-implemented method of claim 1 , wherein the one or more structured defects are represented in at least one of an orthogonal view, a two-dimensional (2D) view, a three-dimensional (3D) view of the artifact being inspected for verification.

5 . A system comprising:
a memory storing instructions; one or more Input/Output (I/O) interfaces; and one or more hardware processors coupled to the memory via the one or more I/O interfaces, wherein the one or more hardware processors are configured by the instructions to:
receive one or more voice inputs from an inspector while inspecting an artifact, wherein the artifact is a physical entity subjected to inspection;
pre-process the one or more voice inputs of the inspector to remove noise using a predefined filtering technique;
convert the one or more pre-processed voice inputs into a predefined language text using a predefined language translation technique to ensure uniformity, wherein the predefined language translation technique includes a universal language model, and a custom speech model;
transform the predefined language text into one or more structured defects for a structured defect log on a domain model of artifact under inspection using a large language model (LLM);
analyze the structured defect log to map a defect name, a defect type, and a defect location to each sub-section of the physical entity represented in the domain model using the large language model (LLM); and
convert the analyzed one or more structured defects into a voice format to facilitate an effective communication to a user for repair and for reporting purpose.

6 . The system of claim 5 , wherein a voice to text conversion model is integrated with the large language model and a domain model of artifact to convert one or more defects spoken by the inspector into the one or more structured defects represented by the domain model.

7 . The system of claim 5 , wherein the defect type, the defect location and the sub-section of the artifact is identified from the one or more voice inputs from the inspector.

8 . The system of claim 5 , wherein the one or more structured defects are represented in at least one of an orthogonal view, a two-dimensional (2D) view, a three-dimensional (3D) view of the artifact being inspected for verification.

9 . One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:
receiving, via an Input/Output (I/O) interface, one or more voice inputs from an inspector while inspecting an artifact, wherein the artifact is a physical entity subjected to inspection; pre-processing the one or more voice inputs of the inspector to remove noise using a predefined filtering technique; converting the one or more pre-processed voice inputs into a predefined language text using a predefined language translation technique to ensure uniformity, wherein the predefined language translation technique includes a universal language model, and a custom speech model; transforming the predefined language text into one or more structured defects for a structured defect log on a domain model of artifact under inspection using a large language model (LLM); analyzing the structured defect log to map a defect name, a defect type, and a defect location to each sub-section of the physical entity represented in the domain model using the large language model (LLM); and converting the analyzed one or more structured defects into a voice format to facilitate an effective communication to a user for repair and for reporting purpose.

10 . The one or more non-transitory machine-readable information storage mediums of claim 9 , wherein a voice to text conversion model is integrated with the large language model and a domain model of artifact to convert one or more defects spoken by the inspector into the one or more structured defects represented by the domain model.

11 . The one or more non-transitory machine-readable information storage mediums of claim 9 , wherein the defect type, the defect location and the sub-section of the artifact is identified from the one or more voice inputs from the inspector.

12 . The one or more non-transitory machine-readable information storage mediums of claim 9 , wherein the one or more structured defects are represented in at least one of an orthogonal view, a two-dimensional (2D) view, a three-dimensional (3D) view of the artifact being inspected for verification.

Assignees

• Tata Consultancy Services Ltd

Inventors

• Sharma Himanshu
• Vishwakarma Arpit
• Malhotra Chetan Premkumar
• Basavarsu Purushottham Gautham

Classifications

• G01N21/8803

  Visual inspection (measuring projectors G01B9/08) · CPC title

• G10L21/0208

  Noise filtering · CPC title

• G10L15/22

  Procedures used during a speech recognition process, e.g. man-machine dialogue · CPC title

• G06Q50/04

  Manufacturing · CPC title

• G10L21/10

  Transforming into visible information · CPC title