A Novel Scheme to Classify Read and Spontaneous Speech
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48312-7_3
Reference15 articles.
1. Asami, T., Masumura, R., Masataki, H., Sakauchi, S.: Read and spontaneous speech classification based on variance of GMM supervectors. In: Fifteenth Annual Conference of the International Speech Communication Association (2014)
2. Batliner, A., Kompe, R., Kießling, A., Nöth, E., Niemann, H.: Can you tell apart spontaneous and read speech if you just look at prosody? In: Speech Recognition and Coding, pp. 321–324. Springer (1995). https://doi.org/10.1007/978-3-642-57745-1_47
3. Bradlow, A.R.: ALLSSTAR: archive of L1 and L2 scripted and spontaneous transcripts and recordings. https://speechbox.linguistics.northwestern.edu/ (2023)
4. Bredin, H., et al.: pyannote.audio: neural building blocks for speaker diarization. In: ICASSP 2020, IEEE International Conference on Acoustics, Speech, and Signal Processing. Barcelona, Spain (2020)
5. Dellwo, V., Leemann, A., Kolly, M.J.: The recognition of read and spontaneous speech in local vernacular: the case of zurich german. J. Phonetics 48, 13–28 (2015). https://doi.org/10.1016/j.wocn.2014.10.011, https://www.sciencedirect.com/science/article/pii/S009544701400093X, the Impact of Stylistic Diversity on Phonetic and Phonological Evidence and Modeling
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