{"id":{"repo_id":"vcu","oai_identifier":"oai:scholarscompass.vcu.edu:etd-1190"},"canonical_url":"https://search.dev.ndltd.org/etd/vcu/oai:scholarscompass.vcu.edu:etd-1190","repository":{"repo_id":"vcu","name":"Virginia Commonwealth University","base_url":"https://scholarscompass.vcu.edu/do/oai/"},"display":{"title":"Real-Time Fundamental Frequency Estimation Algorithm for Disconnected Speech","abstract":"A new algorithm is presented for real-time fundamental frequency estimation of speech signals. This method extends and alters the YIN algorithm, which uses the autocorrelation-based difference function, by adding features to reduce latency, correct predictable errors, and make it structurally appropriate for real-time processing scenarios. The algorithm is shown to reduce the error rate of its predecessor while demonstrating latencies sufficient for real-time processing. 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This method extends and alters the YIN algorithm, which uses the autocorrelation-based difference function, by adding features to reduce latency, correct predictable errors, and make it structurally appropriate for real-time processing scenarios. The algorithm is shown to reduce the error rate of its predecessor while demonstrating latencies sufficient for real-time processing. The results indicate that the algorithm can be realized as a real-time estimator of spoken pitch and pitch variation, which has applications including diagnosis and biofeedback-based therapy of many speech disorders."]},{"key":"dc:title","label":"Title","values":["Real-Time Fundamental Frequency Estimation Algorithm for Disconnected Speech"]}]}],"canonical_facts":{"dc:contributor":["Kayvan Najarian"],"dc:creator":["Skjei, Thomas"],"dc:date.available":["2016-05-09T07:00:00Z"],"dc:description.abstract":["A new algorithm is presented for real-time fundamental frequency estimation of speech signals. This method extends and alters the YIN algorithm, which uses the autocorrelation-based difference function, by adding features to reduce latency, correct predictable errors, and make it structurally appropriate for real-time processing scenarios. The algorithm is shown to reduce the error rate of its predecessor while demonstrating latencies sufficient for real-time processing. 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