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In one group, the gender of each participant was known, and in the other group, the gender of speakers was not identifiable.
In our experiments, and by considering the gender of speakers, as it can be inferred from Table 5 (without a LM, i.e., experiments that numbered by subscript ), we can notice that female speakers give better system overall accuracy.
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In the first two columns of the Table 8, the experimental results with acoustic models adapted to the male and female gender of speaker evaluated on the whole test data set are presented.
Over the last decade, significant attention has been drawn to the gender ratio of speakers at conferences, with ongoing efforts for meetings to better reflect the gender representation in the field.
In preparation for the 2015 conference, therefore, the organizers again presented to the program committee statistics on the gender breakdown of speakers at the preceding meetings.
Experiments Exp. 6 to Exp. 9 are set up by varying the gender of the speakers in training and testing data.
My colleagues and I noted the gender of the speaker and audience (listener), whether the speaker or the audience laughed, and what was said immediately before laughter occurred.
As a result, when I hear a voice I can determine the sex, age, and gender of the speaker, but I cannot determine who the person speaking is.
"We showed that we can determine pretty reliably the gender of a speaker from low-quality sound we managed to recover from a tissue box," says Dr. Michael Rubinstein.
The gender of the speaker is one of the influential sources of speech variability.
The first columns in the tables denote the index of the speech signals where "Female" and "Male" indicate the gender of the speaker who pronounced the desired speech.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com