| lr,19-5-C90-3063,bq | that were randomly selected from the <term> | corpus | </term> . The results of the experiment show | #16689 An experiment was performed to resolve references of the pronoun it in sentences that were randomly selected from thecorpus. |
| lr-prod,26-4-H90-1060,bq | </term> from the <term> DARPA Resource Management | corpus | </term> . This <term> performance </term> is | #17099 With only 12 training speakers for SI recognition, we achieved a 7.5% word error rate on a standard grammar and test set from the DARPA Resource Management corpus. |
| lr,16-6-H90-1060,bq | adaptation ( SA ) </term> using the new <term> SI | corpus | </term> and a small amount of <term> speech | #17136 Second, we show a significant improvement for speaker adaptation (SA) using the new SI corpus and a small amount of speech from the new (target) speaker. |
| lr,12-4-C92-1055,bq | possible variations between the <term> training | corpus | </term> and the real tasks are also taken | #17893 To make the proposed algorithm robust, the possible variations between the training corpus and the real tasks are also taken into consideration by enlarging the separation margin between the correct candidate and its competing members. |
| lr,6-1-H92-1003,bq | recently collected <term> spoken language | corpus | </term> for the <term> ATIS ( Air Travel Information | #18532 This paper describes a recently collected spoken language corpus for the ATIS (Air Travel Information System) domain. |
| lr,3-3-H92-1026,bq | process </term> in a novel way . We use a <term> | corpus | of bracketed sentences </term> , called a | #18946 We use acorpus of bracketed sentences, called a Treebank, in combination with decision tree building to tease out the relevant aspects of a parse tree that will determine the correct parse of a sentence. |
| lr-prod,1-1-H92-1074,bq | <term> CSR ( Connected Speech Recognition ) | corpus | </term> represents a new <term> DARPA speech | #19533 The CSR (Connected Speech Recognition) corpus represents a new DARPA speech recognition technology development initiative to advance the state of the art in CSR. |
| lr,1-2-H92-1074,bq | of the art in <term> CSR </term> . This <term> | corpus | </term> essentially supersedes the now old | #19554 Thiscorpus essentially supersedes the now old Resource Management (RM) corpus that has fueled DARPA speech recognition technology development for the past 5 years. |
| lr-prod,7-2-H92-1074,bq | now old <term> Resource Management ( RM ) | corpus | </term> that has fueled <term> DARPA speech | #19565 This corpus essentially supersedes the now old Resource Management (RM) corpus that has fueled DARPA speech recognition technology development for the past 5 years. |
| lr-prod,2-3-H92-1074,bq | for the past 5 years . The new <term> CSR | corpus | </term> supports research on major new problems | #19583 The new CSR corpus supports research on major new problems including unlimited vocabulary, natural grammar, and spontaneous speech. |
| lr-prod,7-4-H92-1074,bq | paper presents an overview of the <term> CSR | corpus | </term> , reviews the definition and development | #19609 This paper presents an overview of the CSR corpus, reviews the definition and development of the CSR pilot corpus, and examines the dynamic challenge of extending the CSR corpus to meet future needs. |
| lr-prod,17-4-H92-1074,bq | definition and development of the <term> CSR pilot | corpus | </term> , and examines the dynamic challenge | #19620 This paper presents an overview of the CSR corpus, reviews the definition and development of the CSR pilot corpus, and examines the dynamic challenge of extending the CSR corpus to meet future needs. |
| lr-prod,29-4-H92-1074,bq | dynamic challenge of extending the <term> CSR | corpus | </term> to meet future needs . <term> Language | #19631 This paper presents an overview of the CSR corpus, reviews the definition and development of the CSR pilot corpus, and examines the dynamic challenge of extending the CSR corpus to meet future needs. |
| lr,52-3-A94-1011,bq | , and does not require a <term> pre-tagged | corpus | </term> to fit . One of the distinguishing | #19998 A novel method for adding linguistic annotation to corpora is presented which involves using a statistical POS tagger in conjunction with unsupervised structure finding methods to derive notions of noun group, verb group, and so on which is inherently extensible to more sophisticated annotation, and does not require a pre-tagged corpus to fit. |
| lr-prod,15-3-H94-1014,bq | word </term><term> Wall Street Journal text | corpus | </term> . Using the <term> BU recognition system | #21261 The models were constructed using a 5K vocabulary and trained using a 76 million word Wall Street Journal text corpus. |
