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Revised catalogue specifications of speech corpora with user-friendly visualization and search system.

, , , , , and . O-COCOSDA, page 1-5. IEEE, (2014)

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End-of-Utterance Prediction by Prosodic Features and Phrase-Dependency Structure in Spontaneous Japanese Speech., , and . INTERSPEECH, page 1681-1685. ISCA, (2017)Extending Search System based on Interactive Visualization for Speech Corpora., , , , , and . LREC, European Language Resources Association (ELRA), (2018)Analysis of prosodic features for end-of-utterance prediction in spontaneous Japanese., and . DiSS-LPSS, page 97-100. ISCA, (2010)Towards Automatic Transformation between Different Transcription Conventions: Prediction of Intonation Markers from Linguistic and Acoustic Features., , , and . LREC, page 311-315. European Language Resources Association (ELRA), (2014)AWA Long-Term Recorded Speech Corpus And Robust Speaker Recognition Method For Session Variability., , , and . O-COCOSDA, page 15-20. IEEE, (2018)A Prediction Model for End-of-Utterance Based on Prosodic Features and Phrase-Dependency in Spontaneous Japanese., , and . APSIPA, page 1782-1786. IEEE, (2018)Comparative evaluations of robust and accurate F0 estimates in reverberant environments., , and . ICASSP, page 4569-4572. IEEE, (2008)Revised catalogue specifications of speech corpora with user-friendly visualization and search system., , , , , and . O-COCOSDA, page 1-5. IEEE, (2014)An Investigation of Prosodic Features Related to Next Speaker Selection in Spontaneous Japanese Conversation., , and . O-COCOSDA, page 1-5. IEEE, (2019)A fundamental frequency estimation method for noisy speech based on instantaneous amplitude and frequency., , and . INTERSPEECH, page 2439-2442. ISCA, (2001)