
@Article{Hallgren:2012,
  author =       {Kevin A. Hallgren},
  title =        {Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial},
  journal =      {Tutor Quant Methods Psychol.},
  year =         2012,
  volume =    8,
  number =    1,
  pages =     {23--34}}


@Article{Koo/Li:2016,
  author =       {Terry K. Koo and Mae Y. Li},
  title =        {A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research},
  journal =      {Journal of Chiropractic Medicine},
  year =         2016,
  volume =    15,
  pages =     {155--163}}

@Article{Shrout/Fleiss:1979,
  author =       {P. E. Shrout and J. L. Fleiss},
  title =        {Intraclass correlations: uses in assessing rater reliability},
  journal =      {Psychological Bulletin},
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@inproceedings{coutinho-etal-2016-assessing,
    title = "Assessing the Prosody of Non-Native Speakers of {E}nglish: Measures and Feature Sets",
    author = {Coutinho, Eduardo  and
      H{\"o}nig, Florian  and
      Zhang, Yue  and
      Hantke, Simone  and
      Batliner, Anton  and
      N{\"o}th, Elmar  and
      Schuller, Bj{\"o}rn},
    booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
    month = may,
    year = 2016,
    address = "Portoro{\v{z}}, Slovenia",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L16-1211",
    pages = "1328--1332",
    abstract = "In this paper, we describe a new database with audio recordings of non-native (L2) speakers of English, and the perceptual evaluation experiment conducted with native English speakers for assessing the prosody of each recording. These annotations are then used to compute the gold standard using different methods, and a series of regression experiments is conducted to evaluate their impact on the performance of a regression model predicting the degree of naturalness of L2 speech. Further, we compare the relevance of different feature groups modelling prosody in general (without speech tempo), speech rate and pauses modelling speech tempo (fluency), voice quality, and a variety of spectral features. We also discuss the impact of various fusion strategies on performance.Overall, our results demonstrate that the prosody of non-native speakers of English as L2 can be reliably assessed using supra-segmental audio features; prosodic features seem to be the most important ones."}



@Misc{audformat-package,
  howpublished = {https://github.com/audeering/audformat/issues/102}}

@Misc{cronbach-alpha-wikipedia,
  howpublished = {https://en.wikipedia.org/wiki/Cronbach%27s_alpha}}

@Misc{congeneric-reliability-wikipedia,
  howpublished = {https://de.wikipedia.org/wiki/Kongenerische_Reliabilit%C3%A4t}}

@Misc{Hilsdorf,
  author =    {Max Hilsdorf},
  title =     {Cronbach’s Alpha: Theory and Application in Python},
  howpublished = {Towards Data Science: https://towardsdatascience.com/cronbachs-alpha-theory-and-application-in-python-d2915dd63586}}
