{"id":162085,"date":"2007-09-01T00:00:00","date_gmt":"2007-09-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/context-constrained-generalized-posterior-probability-for-verifying-phone-transcriptions\/"},"modified":"2018-10-16T20:08:57","modified_gmt":"2018-10-17T03:08:57","slug":"context-constrained-generalized-posterior-probability-for-verifying-phone-transcriptions","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/context-constrained-generalized-posterior-probability-for-verifying-phone-transcriptions\/","title":{"rendered":"Context Constrained-Generalized Posterior Probability for Verifying Phone Transcriptions"},"content":{"rendered":"

A new statistical confidence measure, Context Constrained Generalized Posterior probability (CC-GPP), is proposed for verifying phone transcriptions in speech databases. Different from generalized posterior probability (GPP), CC-GPP is computed by considering string hypotheses that bear a focused phone with partially matched left and right contexts. Parameters used for CC-GPP include context window length, a minimal number of matched context phones, and verification thresholds. They are determined by minimizing verification errors in a development set. Evaluated on a test set of 500 sentences that consist of 2.1% phone errors, CCGPP achieves 99.6% accuracy and 78.7% recall when 90% of the phones are accepted.<\/p>\n","protected":false},"excerpt":{"rendered":"

A new statistical confidence measure, Context Constrained Generalized Posterior probability (CC-GPP), is proposed for verifying phone transcriptions in speech databases. Different from generalized posterior probability (GPP), CC-GPP is computed by considering string hypotheses that bear a focused phone with partially matched left and right contexts. Parameters used for CC-GPP include context window length, a minimal 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