@inbook{6b499b4dce5e43babcc9a3576b95d180,
title = "Keyword Spotting Out of Continuous Speech",
abstract = "Successful Automatic Speech Recognition (ASR) technology has been a research aspiration for the past five decades. Ideally, computers would be able to transform any type of human speech into an accurate textual transcription. Today{\textquoteright}s ASR technology generates fairly good results using structured speech with relatively low Signal to Noise Ratios (SNR), but performance degrades when using spontaneous speech in real-life noisy environments (Murveit et al. 1992; Young 1996; Furui 2003; Deng and Huang 2004). Performance that is acceptable for commercial applications can be achieved using large training corpora of speech and text. However, there are still problems that need to be resolved.",
keywords = "Keyword Spotting (KWS), Large Speech Database, Large Training Corpus, Large Vocabulary Continuous Speech Recognition (LVCSR), Research Aspiration",
author = "Ami Moyal and Vered Aharonson and Ella Tetariy and Michal Gishri",
note = "Publisher Copyright: {\textcopyright} 2013, The Author(s).",
year = "2013",
doi = "10.1007/978-1-4614-6489-1\_1",
language = "English",
series = "SpringerBriefs in Speech Technology",
publisher = "Springer Science and Business Media B.V.",
pages = "1--6",
booktitle = "SpringerBriefs in Speech Technology",
}