Real-Time Fundamental Frequency Estimation Algorithm for Disconnected Speech

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. 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.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2011

Author dc:creator

• Skjei, Thomas

Contributors dc:contributor

• Kayvan Najarian

• Signal Processing
• Speech Processing
• Computer Sciences
• Physical Sciences and Mathematics

Statement dc:rights

• © The Author

Identifier

https://scholarscompass.vcu.edu/etd/191

OAI identifier oai:identifier

oai:scholarscompass.vcu.edu:etd-1190