TranscribeSight: Redefining ASR Evaluation for Industry 4.0 Knowledge Capture

This paper presents TranscribeSight, a benchmarking platform for systematic evaluation of automatic speech recognition (ASR) technologies in industrial knowledge management contexts. As Industry 4.0 transforms manufacturing, organisations require flexible frameworks for comparing traditional and multimodal large language model solutions. TranscribeSight provides an extensible platform integrating multidimensional evaluation methodologies, encompassing semantic preservation metrics, operational efficiency analysis, and automated qualitative assessment capabilities. The platform’s modular architecture enables integration of diverse ASR services and customisation of evaluation criteria for specific industrial requirements. We demonstrate capabilities through controlled evaluation of eight ASR services using LibriSpeech audio samples with English-language content and default API configurations, though the platform supports multilingual extension and customised configurations. The evaluation identified performance variations across services, with different technologies excelling in accuracy, semantic preservation, or operational efficiency. TranscribeSight provides a foundation for systematic, reproducible ASR assessment adapting to technological advancement and diverse operational requirements in Industry 4.0 environments.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.308
Primary Topic
Speech Recognition and Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

TranscribeSight: Redefining ASR Evaluation for Industry 4.0 Knowledge Capture

Andrew Abel, Ali Alsayegh, Tariq Masood, Laibing Jia et al.
Procedia Computer Science
Speech Recognition and Synthesis
article

TranscribeSight: Redefining ASR Evaluation for Industry 4.0 Knowledge Capture

Andrew Abel, Ali Alsayegh, Tariq Masood, Laibing Jia, Noor Ul Ain
article en

Abstract

This paper presents TranscribeSight, a benchmarking platform for systematic evaluation of automatic speech recognition (ASR) technologies in industrial knowledge management contexts. As Industry 4.0 transforms manufacturing, organisations require flexible frameworks for comparing traditional and multimodal large language model solutions. TranscribeSight provides an extensible platform integrating multidimensional evaluation methodologies, encompassing semantic preservation metrics, operational efficiency analysis, and automated qualitative assessment capabilities. The platform’s modular architecture enables integration of diverse ASR services and customisation of evaluation criteria for specific industrial requirements. We demonstrate capabilities through controlled evaluation of eight ASR services using LibriSpeech audio samples with English-language content and default API configurations, though the platform supports multilingual extension and customised configurations. The evaluation identified performance variations across services, with different technologies excelling in accuracy, semantic preservation, or operational efficiency. TranscribeSight provides a foundation for systematic, reproducible ASR assessment adapting to technological advancement and diverse operational requirements in Industry 4.0 environments.

Procedia Computer ScienceVol. 277
University of Strathclyde (GB)
Industry, innovation and infrastructure
Openalex Percentile: Top 12%
Speech Recognition and Synthesis
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