{"title":"Sound recognition with spiking silicon cochlea and Hidden Markov Models","authors":"D. Jackel, R. Moeckel, Shih-Chii Liu","doi":"10.5167/UZH-47180","DOIUrl":"https://doi.org/10.5167/UZH-47180","url":null,"abstract":"In this paper we explore the capabilities of a sound recognition system that combines both a novel bio-inspired custom silicon cochlea chip and a classical Hidden Markov Model (HMM). The cochlea chip front-end produces a form of representation that is analogous to the spike outputs of the biological cochlea. The system is trained with either of 2 target sounds (a clap or a bass drum) in the presence of different levels of white noise or colored noise. We provide experimental results that show 1) the system is able to detect a clap or a bass drum sound even if the amplitude of the target sound was not part of the training set and 2) the performance of the system in detecting a target sound in the presence of white noise or colored noise is around 90% for signal-to-noise ratios down to at least 0.8.","PeriodicalId":214725,"journal":{"name":"6th Conference on Ph.D. Research in Microelectronics & Electronics","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123330087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}