| other,12-1-N03-1001,bq | classification </term> that does not require <term> | manual transcription | </term> of <term> training data </term> . The | #2217 This paper describes a method for utterance classification that does not require manual transcription of training data. |
| other,29-2-N03-1001,bq | word-trigram recognition </term> requiring <term> | manual transcription | </term> . In our method , <term> unsupervised | #2252 The method combines domain independent acoustic models with off-the-shelf classifiers to give utterance classification performance that is surprisingly close to what can be achieved using conventional word-trigram recognition requiring manual transcription . |
| tech,4-3-N03-1001,bq | transcription </term> . In our method , <term> | unsupervised training | </term> is first used to train a <term> phone | #2259 In our method, unsupervised training is first used to train a phone n-gram model for a particular domain; the output of recognition with this model is then passed to a phone-string classifier. |
| tech,32-3-N03-1001,bq | <term> model </term> is then passed to a <term> | phone-string classifier | </term> . The <term> classification accuracy | #2287 In our method, unsupervised training is first used to train a phone n-gram model for a particular domain; the output of recognition with this model is then passed to a phone-string classifier . |
