Our work builds directly on that of others. The main references for tools currently included and/or data currently used to perform tests are:

  • Bergelson, E., Warlaumont, A., Cristia, A., Casillas, M., Rosemberg, C., Soderstrom, M., Rowland, C., Durrant, S. & Bunce, J. (2017). Starter-ACLEW. Databrary. Retrieved October 1, 2018 from
  • Eyben, F. Weninger, F., Gross, F. & B. Schuller. (2013). Recent developments in opensmile, the munich open-source multimedia feature extractor. Proceedings of the 21st ACM international conference on Multimedia, 835–838.
  • Eyben, F., Weninger, F., Squartini, S., & Schuller, B. (2013, May). Real-life voice activity detection with lstm recurrent neural networks and an application to hollywood movies. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 483-487). IEEE.
  • Räsänen, O., Seshadri, S., & Casillas, M. (2018, June). Comparison of Syllabification Algorithms and Training Strategies for Robust Word Count Estimation across Different Languages and Recording Conditions. In Interspeech 2018.
  • Sadjadi, S.O. & Hansen, J.H.L. (2013). Unsupervised Speech Activity Detection using Voicing Measures and Perceptual Spectral Flux. IEEE Signal Processing Letters, 20(3), 197-200.
  • VanDam, M., & Tully, T. (2016, May). Quantity of mothers’ and fathers’ speech to sons and daughters. Talk presented at the 171st Meeting of the Acoustical Society of America, Salt Lake City, UT.
  • Vijayasenan, D. & Valente, F. (2012) Diartk: An open source toolkit for research in multistream speaker diarization and its application to meetings recordings. Thirteenth Annual Conference of the International Speech Communication Association, 2012.
  • Wang, Y., Neves, L., & Metze, F. (2016, March). Audio-based multimedia event detection using deep recurrent neural networks. In Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on (pp. 2742-2746). IEEE. pdf
  • Young, S., Evermann, G., Gales, M., Hain, T. , Kershaw, D., Liu, X., Moore, G., Odell, J., Ollason, D., Povey,D. et al. (2002) The HTK book. Cambridge University Engineering Department.
  • Ziaei, A. Sangwan, A., & Hansen, J.H.L. (2016). Effective word count estimation for long duration daily naturalistic audio recordings. Speech Communication, 84, 15-23.
  • Bredin, H. (2017). A toolkit for reproducible evaluation, diagnostic, and error analysis of speaker diarization systems,