Two important features of any deployable speech recognition system are the capability to detect if the input speech does not contain any of the recognizer keywords, and spot a keyword embedded in other speech or extraneous sounds. As a result, utterance verification (or non-keyword rejection) is becoming increasingly important as speech recognition systems continue to migrate from the laboratory to actual applications. In this paper we present a framework and a method for vocabulary independent utterance verification in subword based speech recognition. The verification process is cast as a statistical hypothesis test, where vocabulary independence is accomplished through a two stage verification process: subword level verification followed by string level verification. Experimental results show that this vocabulary independent discriminative utterance verification method significantly outperforms a baseline method commonly used in wordspotting tasks.
Bibliographic reference. Sukkar, Rafid A. / Lee, Chin-Hui / Juang, Bling-Hwang (1995): "A vocabulary independent discriminatively trained method for rejection of non-keywords in sub word based speech recognition", In EUROSPEECH-1995, 1629-1632.