Browse State-of-the-Art › Spoken Command Recognition
Spoken Command Recognition
5 papers with code · 1 benchmark · 0 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| Speech Command v2 (4 rows) | SSAST-FRAME | SSAST: Self-Supervised Audio Spectrogram Transformer | code | Syntology ran 11 of 16 samples · 5 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
No dataset record in the archive lists this task.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
5 shown of 5 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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26 Apr 2022 4 repositories listedSelf-supervised learning (SSL) learns knowledge from a large amount of unlabeled data, and then transfers the knowledge to a specific problem with a limited number of labeled data.
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19 Oct 2021 3 repositories listed Syntology ran 11 of 16 samples · 5 unverifiedHowever, pure Transformer models tend to require more training data compared to CNNs, and the success of the AST relies on supervised pretraining that requires a large amount of labeled data and a complex training…
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21 Oct 2020 2 repositories listedWe introduce COLA, a self-supervised pre-training approach for learning a general-purpose representation of audio.
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11 Mar 2022 1 repository listedThis work focuses on designing low complexity hybrid tensor networks by considering trade-offs between the model complexity and practical performance.
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Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command Recognition8 Oct 2021 1 repository listedIn this study, we propose a novel adversarial reprogramming (AR) approach for low-resource spoken command recognition (SCR), and build an AR-SCR system.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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