Variabilité inter et intra locuteurs de mesures spectrales et prosodiques en parole lue

@article{Gendrot2018VariabilitIE,
  title={Variabilit{\'e} inter et intra locuteurs de mesures spectrales et prosodiques en parole lue},
  author={C{\'e}dric Gendrot and Gabriele Chignoli and Nicola Audibert and C{\'e}cile Fougeron},
  journal={XXXIIe Journ{\'e}es d’{\'E}tudes sur la Parole},
  year={2018}
}
variabilité intra locuteurs 

Figures and Tables from this paper

References

SHOWING 1-9 OF 9 REFERENCES

Parole de locuteur : performance et confiance en identification biométrique vocale. (Speaker in speech : performance and confidence in voice biometric identification)

  • J. Kahn
  • Computer Science, Philosophy
  • 2011
Ce travail de these explore l’usage biometrique de la parole dont les applications sont tres nombreuses (securite, environnements intelligents, criminalistique, surveillance du territoire ou

Reconnaissance Automatique de la Parole Du signal à son interprétation

La reconnaissance automatique de la parole donne aujourd'hui lieu a un ensemble important d'applications de nature et de difficulte tres variees, concernant quotidiennement des millions de personnes

Eta Squared, Partial Eta Squared, and Misreporting of Effect Size in Communication Research

Communication researchers, along with social scientists from a variety of disciplines, are increasingly recognizing the importance of reporting effect sizes to augment significance tests. Serious

Dynamic features of speech and the characterization of speakers: Toward a new approach using formant frequencies

Why dynamic features of speech should provide an important source of speaker-distinguishing information and a new direction for the development of a technique for characterizing individual speakers which uses regression to parameterize formant frequency contours are outlined.

Investigations into prosodic syllable contour features for speaker recognition

It is shown that the performance of prosodic syllable contour features is especially affected by the segmentation and the quality of the pitch tracking algorithm and that the features are highly gender dependent.

R: A language and environment for statistical computing.

Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice

The case for automatic higher-level features in forensic speaker recognition

An overview of automatic higher-level systems and potential advantages, as well as issues, for their use in the forensic context are discussed.