{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T13:10:44Z","timestamp":1740057044747,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>We evaluate back-off n-gram and recurrent neural network language models for an automatic speech recognition system for medical applications. We also propose an effective and simple multi-domain recurrent neural network architecture which enables training a joint model for all domains. The multi-domain recurrent neural network model outperforms all other compared models.<\/jats:p>","DOI":"10.3233\/978-1-61499-442-8-149","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":0,"title":["Multi-Domain Recurrent Neural Network Language Model for Medical Speech Recognition"],"prefix":"10.3233","author":[{"family":"Tilk Ottokar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Alum&auml;e Tanel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Human Language Technologies &amp;ndash; The Baltic Perspective"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:28:19Z","timestamp":1740054499000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-441-1&spage=149&doi=10.3233\/978-1-61499-442-8-149"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-442-8-149","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2014]]}}}