{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T17:13:25Z","timestamp":1780420405050,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T00:00:00Z","timestamp":1781913600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,21]]},"DOI":"10.1145\/3812836.3814790","type":"proceedings-article","created":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:54:53Z","timestamp":1780419293000},"page":"379-384","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Hardware-Software co-design of FETA: a Flexible Low Power AI accelerator for Time-series signals"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0306-6566","authenticated-orcid":false,"given":"Nazareno","family":"Sacchi","sequence":"first","affiliation":[{"name":"CSEM, Neuchatel, Switzerland"},{"name":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3490-0998","authenticated-orcid":false,"given":"St\u00e9phane","family":"Devise","sequence":"additional","affiliation":[{"name":"CSEM, Neuchatel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9203-4425","authenticated-orcid":false,"given":"R\u00e9gis","family":"Cattenoz","sequence":"additional","affiliation":[{"name":"CSEM, Neuchatel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4651-0677","authenticated-orcid":false,"given":"Taekwang","family":"Jang","sequence":"additional","affiliation":[{"name":"ETH Z\u00fcrich, Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,20]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474365"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3223444"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5772\/intechopen.107726"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/OJSSCS.2023.3312354"},{"key":"e_1_3_2_1_5_1","first-page":"622","volume-title":"37.8 a 13.5 \u03bcw 35-keyword end-to-end keyword spotting system featuring personalized on-chip training in 28nm cmos,\" in 2025 IEEE International Solid-State Circuits Conference (ISSCC)","author":"Lee H.-J.","year":"2025","unstructured":"H.-J. Lee, K. Pyo, T. Jang, M. Seok, and S. Cho, \"37.8 a 13.5 \u03bcw 35-keyword end-to-end keyword spotting system featuring personalized on-chip training in 28nm cmos,\" in 2025 IEEE International Solid-State Circuits Conference (ISSCC), vol. 68. IEEE, 2025, pp. 620\u2013622."},{"key":"e_1_3_2_1_6_1","article-title":"Low-power learnable digital audio feature extractor for always-on keyword spotting in edge devices","author":"Shen C.","year":"2025","unstructured":"C. Shen, J. Hu, W. L. Goh, Y. S. Chong, A. T. Do, and Y. Gao, \"Low-power learnable digital audio feature extractor for always-on keyword spotting in edge devices,\" IEEE Transactions on Circuits and Systems I: Regular Papers, 2025.","journal-title":"IEEE Transactions on Circuits and Systems I: Regular Papers"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2023.3339528"},{"key":"e_1_3_2_1_8_1","volume-title":"d. Blanken and C. Frenkel, \"Chameleon: A matmul-free temporal convolutional network accelerator for end-to-end few-shot and continual learning from sequential data,\" arXiv preprint arXiv:2505.24852","author":"D.","year":"2025","unstructured":"D. d. Blanken and C. Frenkel, \"Chameleon: A matmul-free temporal convolutional network accelerator for end-to-end few-shot and continual learning from sequential data,\" arXiv preprint arXiv:2505.24852, 2025."},{"key":"e_1_3_2_1_9_1","volume-title":"Hello edge: Keyword spotting on microcontrollers,\" arXiv preprint arXiv:1711.07128","author":"Zhang Y.","year":"2017","unstructured":"Y. Zhang, N. Suda, L. Lai, and V. Chandra, \"Hello edge: Keyword spotting on microcontrollers,\" arXiv preprint arXiv:1711.07128, 2017."},{"key":"e_1_3_2_1_10_1","volume-title":"Streaming keyword spotting on mobile devices,\" arXiv preprint arXiv:2005.06720","author":"Rybakov O.","year":"2020","unstructured":"O. Rybakov, N. Kononenko, N. Subrahmanya, M. Visontai, and S. Laurenzo, \"Streaming keyword spotting on mobile devices,\" arXiv preprint arXiv:2005.06720, 2020."},{"key":"e_1_3_2_1_11_1","volume-title":"Keyword transformer: A self-attention model for keyword spotting,\" arXiv preprint arXiv:2104.00769","author":"Berg A.","year":"2021","unstructured":"A. Berg, M. O'Connor, and M. T. Cruz, \"Keyword transformer: A self-attention model for keyword spotting,\" arXiv preprint arXiv:2104.00769, 2021."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"J. Xiao X. Zhang S. Zhu Z. Yang M. Du C. Ji Y. Long X. Chen X. Miao L. Zhou et al. \"14.8 kasp: A 96.8% 10-keyword accuracy and 1.68 \u03bcj\/classification keyword spotting and speaker verification processor using adaptive beamforming and progressive wake-up \" in 2024 IEEE International Solid-State Circuits Conference (ISSCC) vol. 67. IEEE 2024 pp. 268\u2013270.","DOI":"10.1109\/ISSCC49657.2024.10454492"},{"key":"e_1_3_2_1_13_1","volume-title":"ETSI","author":"European Telecommunications Standard Institute","year":"2003","unstructured":"European Telecommunications Standard Institute, \"Speech processing, transmission and quality aspects (stq); distributed speech recognition; front-end feature extraction algorithm; compression algorithms,\" Aurora Standard, ETSI ES 201 108 V1.1.3, ETSI, Sep. 2003, (2003-09)."},{"key":"e_1_3_2_1_14_1","first-page":"3","volume-title":"IEEE","author":"J.-H.","year":"2023","unstructured":"J.-H. SeoI, H. Yang, R. Rothe, Z. Fan, Q. Zhang, H.-S. Kim, D. Blaauw, and D. Sylvester, \"A 1.5 \u03bcw end-to-end keyword spotting soc with content-adaptive frame sub-sampling and fast-settling analog frontend,\" in 2023 IEEE International Solid-State Circuits Conference (ISSCC). IEEE, 2023, pp. 1\u20133."},{"key":"e_1_3_2_1_15_1","first-page":"3","volume-title":"IEEE","author":"Kim K.","year":"2022","unstructured":"K. Kim, C. Gao, R. Gra\u00e7a, I. Kiselev, H.-J. Yoo, T. Delbruck, and S.-C. Liu, \"A 23\u03bcw solar-powered keyword-spotting asic with ring-oscillator-based time-domain feature extraction,\" in 2022 IEEE International Solid-State Circuits Conference (ISSCC), vol. 65. IEEE, 2022, pp. 1\u20133."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2020.2968800"},{"key":"e_1_3_2_1_17_1","volume-title":"Harnessing the redshift of generative ai with effective hardware-software co-design,\" arXiv preprint arXiv:2504.06531","author":"Yazdanbakhsh A.","year":"2025","unstructured":"A. Yazdanbakhsh, \"Beyond moore's law: Harnessing the redshift of generative ai with effective hardware-software co-design,\" arXiv preprint arXiv:2504.06531, 2025."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3225363"},{"key":"e_1_3_2_1_19_1","volume-title":"A dataset for limited-vocabulary speech recognition,\" arXiv preprint arXiv:1804.03209","author":"Warden P.","year":"2018","unstructured":"P. Warden, \"Speech commands: A dataset for limited-vocabulary speech recognition,\" arXiv preprint arXiv:1804.03209, 2018."},{"key":"e_1_3_2_1_20_1","volume-title":"Integer quantization for deep learning inference: Principles and empirical evaluation,\" arXiv preprint arXiv:2004.09602","author":"Wu H.","year":"2020","unstructured":"H. Wu, P. Judd, X. Zhang, M. Isaev, and P. Micikevicius, \"Integer quantization for deep learning inference: Principles and empirical evaluation,\" arXiv preprint arXiv:2004.09602, 2020."},{"key":"e_1_3_2_1_21_1","unstructured":"S. Migacz \"8-bit inference with tensorrt \" in GPU technology conference vol. 2 no. 4 2017 p. 5."},{"key":"e_1_3_2_1_22_1","volume-title":"Real world preasymptotics, epistemology, and applications,\" arXiv preprint arXiv:2001.10488","author":"Taleb N. N.","year":"2020","unstructured":"N. N. Taleb, \"Statistical consequences of fat tails: Real world preasymptotics, epistemology, and applications,\" arXiv preprint arXiv:2001.10488, 2020."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1088\/1742-5468\/ab3985"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/BFb0103945"},{"key":"e_1_3_2_1_25_1","first-page":"753","volume-title":"Theoretical analysis of domain adaptation with optimal transport,\" in Joint European Conference on Machine Learning and Knowledge Discovery in Databases","author":"Redko I.","year":"2017","unstructured":"I. Redko, A. Habrard, and M. Sebban, \"Theoretical analysis of domain adaptation with optimal transport,\" in Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, 2017, pp. 737\u2013753."},{"key":"e_1_3_2_1_26_1","first-page":"4","volume-title":"Circuits and Systems (ICECS). IEEE","author":"Sacchi N.","year":"2024","unstructured":"N. Sacchi, E. Azarkhish, F. Caruso, R. Cattenoz, P. Jokic, S. Emery, and T. Jang, \"A study on mram across memory hierarchies for edge kws adaptive power cycling,\" in 2024 31st IEEE International Conference on Electronics, Circuits and Systems (ICECS). IEEE, 2024, pp. 1\u20134."},{"key":"e_1_3_2_1_27_1","volume-title":"IEEE","author":"Sacchi N.","year":"2026","unstructured":"N. Sacchi, R. Cattenoz, P. Jokic, S. Emery, and T. Jang, \"Hardware-algorithm co-design of a cordic-based nonlinear unit for low-power edge rnn inference,\" in 2026 31st IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2026."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASSP.1976.1162854"},{"key":"e_1_3_2_1_29_1","volume-title":"Hardware implementations for voice activity detection: Trends, challenges and outlook,\" IEEE transactions on circuits and systems I: regular papers","author":"Yadav S.","unstructured":"S. Yadav, P. A. D. Legaspi, M. S. Oude Alink, A. B. Kokkeler, and B. Nauta, \"Hardware implementations for voice activity detection: Trends, challenges and outlook,\" IEEE transactions on circuits and systems I: regular papers, vol. 70, no. 3, pp. 1083\u20131096, 2022."},{"issue":"12","key":"e_1_3_2_1_30_1","first-page":"1077","article-title":"The sleep heart health study: design, rationale, and methods","volume":"20","author":"Quan S. F.","year":"1997","unstructured":"S. F. Quan, B. V. Howard, C. Iber, J. P. Kiley, F. J. Nieto, G. T. O'Connor, D. M. Rapoport, S. Redline, J. Robbins, J. M. Samet et al., \"The sleep heart health study: design, rationale, and methods,\" Sleep, vol. 20, no. 12, pp. 1077\u20131085, 1997.","journal-title":"Sleep"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocy064"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2023.3236566"},{"key":"e_1_3_2_1_33_1","first-page":"14","volume-title":"IEEE","author":"Horowitz M.","year":"2014","unstructured":"M. Horowitz, \"1.1 computing's energy problem (and what we can do about it),\" in 2014 IEEE international solid-state circuits conference digest of technical papers (ISSCC). IEEE, 2014, pp. 10\u201314."},{"key":"e_1_3_2_1_34_1","first-page":"14","volume-title":"System latency guidelines then and now-is zero latency really considered necessary?\" in International Conference on Engineering Psychology and Cognitive Ergonomics","author":"Attig C.","year":"2017","unstructured":"C. Attig, N. Rauh, T. Franke, and J. F. Krems, \"System latency guidelines then and now-is zero latency really considered necessary?\" in International Conference on Engineering Psychology and Cognitive Ergonomics. Springer, 2017, pp. 3\u201314."}],"event":{"name":"MobiSys Workshop '26: 24th Annual International Conference on Mobile Systems, Applications and Services Workshops","location":"University of Cambridge Cambridge United Kingdom","acronym":"MobiSys Workshop '26","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the 24th Annual International Conference on Mobile Systems, Applications and Services Workshops"],"original-title":[],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:56:11Z","timestamp":1780419371000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3812836.3814790"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,20]]},"references-count":34,"alternative-id":["10.1145\/3812836.3814790","10.1145\/3812836"],"URL":"https:\/\/doi.org\/10.1145\/3812836.3814790","relation":{},"subject":[],"published":{"date-parts":[[2026,6,20]]},"assertion":[{"value":"2026-06-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}