Prioritizing Speech Test Cases Article Swipe
Zhou Yang
,
Jieke Shi
,
Muhammad Hilmi Asyrofi
,
Bowen Xu
,
Xin Zhou
,
Dong‐Gyun Han
,
David Lo
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3707450
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3707450
As Automated Speech Recognition (ASR) systems gain widespread acceptance, there is a pressing need to rigorously test and enhance their performance. Nonetheless, the process of collecting and executing speech test cases is typically both costly and time-consuming. This presents a compelling case for the strategic prioritization of speech test cases, which consist of a piece of audio and the corresponding reference text . The central question we address is: In what sequence should speech test cases be collected and executed to identify the maximum number of errors at the earliest stage ? In this study, we introduce PRiOritizing sPeecH tEsT ( Prophet ) cases, a tool designed to predict the likelihood that speech test cases will identify errors. Consequently, Prophet can assess and prioritize these test cases without having to run the ASR system, facilitating large-scale analysis. Our evaluation encompasses \(6\) distinct prioritization techniques across \(3\) ASR systems and \(12\) datasets. When constrained by the same test budget, our approach identified \(15.44\%\) more misrecognized words than the leading state-of-the-art method. We select top-ranked speech test cases from the prioritized list to fine-tune ASR systems and analyze how our approach can improve the ASR system performance. Statistical evaluations show that our method delivers a considerably higher performance boost for ASR systems compared to established baseline techniques. Moreover, our correlation analysis confirms that fine-tuning an ASR system with a dataset where the model initially underperforms tends to yield greater performance improvements.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3707450
- https://dl.acm.org/doi/pdf/10.1145/3707450
- OA Status
- hybrid
- Cited By
- 4
- References
- 72
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405185384
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4405185384Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3707450Digital Object Identifier
- Title
-
Prioritizing Speech Test CasesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-09Full publication date if available
- Authors
-
Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi, Bowen Xu, Xin Zhou, Dong‐Gyun Han, David LoList of authors in order
- Landing page
-
https://doi.org/10.1145/3707450Publisher landing page
- PDF URL
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https://dl.acm.org/doi/pdf/10.1145/3707450Direct link to full text PDF
- Open access
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YesWhether a free full text is available
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-
hybridOpen access status per OpenAlex
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https://dl.acm.org/doi/pdf/10.1145/3707450Direct OA link when available
- Concepts
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Computer science, Prioritization, Test (biology), Speech recognition, Process (computing), Artificial intelligence, Paleontology, Operating system, Economics, Biology, Management scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
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2025: 2, 2024: 2Per-year citation counts (last 5 years)
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72Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2076646346, https://openalex.org/W3095160926, https://openalex.org/W3195391869, https://openalex.org/W3217530062, https://openalex.org/W3128630643, https://openalex.org/W3160567372, https://openalex.org/W3036601975, https://openalex.org/W2899067106, https://openalex.org/W3209984917, https://openalex.org/W4372259817, https://openalex.org/W4392903872, https://openalex.org/W3181966798, https://openalex.org/W2963341956, https://openalex.org/W3139294479, https://openalex.org/W4247348948, https://openalex.org/W3042703469, https://openalex.org/W3090943961, https://openalex.org/W4311165731, https://openalex.org/W2008955157, https://openalex.org/W4284682233, https://openalex.org/W2994987245, https://openalex.org/W4221159558, https://openalex.org/W2064675550, https://openalex.org/W3209059054, https://openalex.org/W4224214784, https://openalex.org/W4285490473, https://openalex.org/W2995181338, https://openalex.org/W2954629067, https://openalex.org/W3030983164, https://openalex.org/W3015537910, https://openalex.org/W2792106437, https://openalex.org/W1579799841, https://openalex.org/W2922015121, https://openalex.org/W2804337238, https://openalex.org/W3120991880, https://openalex.org/W2972551158, https://openalex.org/W2537284459, https://openalex.org/W3100180738, https://openalex.org/W2001496424, https://openalex.org/W1509837333, https://openalex.org/W3176989815, https://openalex.org/W1494198834, https://openalex.org/W2982138961, https://openalex.org/W3206378830, https://openalex.org/W4225878270, https://openalex.org/W4313547593, https://openalex.org/W571237954, https://openalex.org/W2963327228, https://openalex.org/W2108687396, https://openalex.org/W6739901393, https://openalex.org/W2399979888, https://openalex.org/W3092424727, https://openalex.org/W1984985727, https://openalex.org/W4225584758, https://openalex.org/W2957905354, https://openalex.org/W3105249702, https://openalex.org/W4286530321, https://openalex.org/W4313563661, https://openalex.org/W4226216828, https://openalex.org/W4220722393, https://openalex.org/W2014515160, https://openalex.org/W2943181041, https://openalex.org/W4378418579, https://openalex.org/W3007157104, https://openalex.org/W3096150021, https://openalex.org/W2888954148, https://openalex.org/W4285056112, https://openalex.org/W4283661468, https://openalex.org/W4237364687, https://openalex.org/W2489487449, https://openalex.org/W1881549354, https://openalex.org/W2592980454 |
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