{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T19:44:21Z","timestamp":1730231061349,"version":"3.28.0"},"reference-count":41,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T00:00:00Z","timestamp":1685836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T00:00:00Z","timestamp":1685836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,4]]},"DOI":"10.1109\/icassp49357.2023.10095360","type":"proceedings-article","created":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T17:28:30Z","timestamp":1683307710000},"page":"1-5","source":"Crossref","is-referenced-by-count":0,"title":["ERSAM: Neural Architecture Search for Energy-Efficient and Real-Time Social Ambiance Measurement"],"prefix":"10.1109","author":[{"given":"Chaojian","family":"Li","sequence":"first","affiliation":[{"name":"Georgia Institute of Technology,Atlanta,GA"}]},{"given":"Wenwan","family":"Chen","sequence":"additional","affiliation":[{"name":"Rice University,Houston,TX"}]},{"given":"Jiayi","family":"Yuan","sequence":"additional","affiliation":[{"name":"Rice University,Houston,TX"}]},{"given":"Yingyan Celine","family":"Lin","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology,Atlanta,GA"}]},{"given":"Ashutosh","family":"Sabharwal","sequence":"additional","affiliation":[{"name":"Rice University,Houston,TX"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"article-title":"Predicting on the edge: Identifying where a larger model does better","year":"2022","author":"narayan","key":"ref35"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01453-z"},{"article-title":"Depthshrinker: A new compression paradigm towards boosting real-hardware efficiency of compact neural networks","year":"2022","author":"fu","key":"ref34"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053167"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/IWAENC.2018.8521242"},{"key":"ref14","article-title":"Countnet: Estimating the number of concurrent speakers using supervised learning","volume":"27","author":"stoter","year":"2018","journal-title":"IEEE\/ACM TASLP"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2015.7178964"},{"article-title":"A fast knowledge distillation framework for visual recognition","year":"2021","author":"shen","key":"ref31"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683438"},{"article-title":"Distilling the knowledge in a neural network","year":"2015","author":"hinton","key":"ref11"},{"article-title":"Hw-nas-bench: Hardware-aware neural architecture search benchmark","year":"2021","author":"li","key":"ref33"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58571-6_41"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2019-1873"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2568027"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.670020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3758\/s13428-020-01393-5"},{"year":"0","key":"ref39","article-title":"Snapdragon Profiler"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/MDM.2015.41"},{"year":"0","key":"ref38","article-title":"Performance measurement"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2020-1781"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1111\/desc.12172"},{"article-title":"Darts: Differentiable architecture search","year":"2018","author":"liu","key":"ref24"},{"article-title":"Proxylessnas: Direct neural architecture search on target task and hardware","year":"2018","author":"cai","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2020-3132"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2020-1315"},{"article-title":"Dna: Differentiable network-accelerator co-search","year":"2020","author":"zhang","key":"ref20"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053074"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"article-title":"On the opportunities and risks of foundation models","year":"2021","author":"bommasani","key":"ref28"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2020-1233"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00157"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01099"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403331"},{"article-title":"Once-for-all: Train one network and specialize it for efficient deployment","year":"2019","author":"cai","key":"ref9"},{"year":"0","key":"ref4","article-title":"Pixel 3"},{"key":"ref3","article-title":"wav2vec 2.0: A framework for self- supervised learning of speech representations","volume":"33","author":"baevski","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/asi1010008"},{"year":"0","key":"ref5","article-title":"Speech Recognition on Android with Wav2Vec2"},{"article-title":"Musan: A music, speech, and noise corpus","year":"2015","author":"snyder","key":"ref40"}],"event":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2023,6,4]]},"location":"Rhodes Island, Greece","end":{"date-parts":[[2023,6,10]]}},"container-title":["ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10094559\/10094560\/10095360.pdf?arnumber=10095360","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T19:00:35Z","timestamp":1700506835000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10095360\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,4]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/icassp49357.2023.10095360","relation":{},"subject":[],"published":{"date-parts":[[2023,6,4]]}}}