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However,\u00a0this method suffers from high computational cost since the excessive parameters in the Transformer model and the computational burden of global attention, which limit its applicability in a resource-constrained KWS scenario. To overcome this issue, we propose a novel Swin-Transformer based\u00a0KWS method. In this approach, first extract dynamic features using Temporal Convolutional Network (TCN)\u00a0from input Mel-Frequency Cepstral Coefficients (MFCCs). Then, the Swin-Transformer is employed to capture hierarchical multi-scale features, where a window attention is designed\u00a0to grasp dynamic time\u2013frequency features. Furthermore, to enhance the extraction of contextual information from the spectrogram, a frame-level shifted window attention mechanism is proposed to enhance the inter-window interaction,\u00a0thus extracting more contextual information from the spectrogram. Experimental results on the speech command V1 dataset verify the effectiveness of the proposal, which achieves a recognition accuracy of 98.01% with less model parameters, outperforming existing KWS methods.<\/jats:p>","DOI":"10.1007\/s44196-024-00448-1","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T06:25:12Z","timestamp":1711520712000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Speech Keyword Spotting Method Based on Swin-Transformer Model"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5346-8796","authenticated-orcid":false,"given":"Chengli","family":"Sun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bikang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feilong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Leng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiaosheng","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,3,27]]},"reference":[{"key":"448_CR1","unstructured":"Chengli Sun. 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