Papers › Wav2KWS: Transfer Learning from Speech Representations for Keyword Spotting
Wav2KWS: Transfer Learning from Speech Representations for Keyword Spotting
D.J SEO, H.S OH, Y.C JUNG
With the expanding development of on-device artificial intelligence, voice-enabled devices such as smart speakers, wearables, and other on-device or edge processing systems have been proposed. However, building or obtaining large training datasets that are essential for robust keyword spotting (KWS) remains cumbersome. To address this problem, we propose a deep neural network that can rapidly establish a high-performance KWS system from arbitrary keyword instruction sets. We use an encoder pretrained with a large-scale speech corpus as the backbone network and then design an effective transfer network for KWS. To demonstrate the feasibility of the proposed network, various experiments were conducted on Google Speech Command Datasets V1 and V2. In addition, to verify the applicability of the network for different languages, we conducted experiments using three different Korean speech command datasets. The proposed network outperforms state-of-the-art deep neural networks in both experiments. Furthermore, the proposed network can understand real human voice even when trained with synthetic text-to-speech data.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Keyword Spotting | Google Speech Commands | Wav2KWS | Google Speech Commands V1 12 | 97.9 | #3 of 42 | Archive leaderboard | report |
| Keyword Spotting | Google Speech Commands | Wav2KWS | Google Speech Commands V2 12 | 98.5 | #3 of 42 | Archive leaderboard | report |
| Keyword Spotting | Google Speech Commands | Wav2KWS | Google Speech Commands V2 20 | 97.8 | #3 of 42 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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