testAudioData {voiceR}

voiceR test Audio Data

Description

A test audio features data.frame, obtained by using autoExtract() on the extended version of testAudioList, found <a href="https://osf.io/zt5h2/?view_only=348d1d172435449391e8d64547716477">here</a>.

Format

'testAudioData' A data.frame containing 90 observations and 11 variables, which is the result of applying the autoExtract() function to the extended version of the data found on testAudioList. This data.frame contains several voice features for 90 audio files, which correspond to 15 English-speaking participants. Participants first completed a Baseline Voice Task in which they were instructed to read two predefined phrases ((1) Bar: "I go to the bar", (2) Beer: "I drink a beer") aloud in their normal (neutral) voice. Participants were then instructed to read the predefined phrases in either a happy or a sad voice. The experimenter requested each emotion one at a time and in a random sequence to counter-order effects. Participants were then asked to describe their experience of mimicking the stated phrases for each of the specified emotional states. Thus the data contains 6 observations per participant: two observations for the neutral state, two for the happy simulated state, and two for the sad simulated state. Below we also provide information about the columns this data.frame contains:

ID

Participant identifier

Condition

refers to the intention or emotional aspect that the speaker is conveying: Happy, or Sad. This component makes reference to the main point that we want to compare in our data; in the voiceR package the main comparison component is called Condition, because it usually refers to experimental conditions.

Dimensions

Phrase participants read: (1) Bar: "I go to the bar"; (2): Beer: "I drink a beer"

duration

Total duration in seconds.

voice_breaks_percent

Proportion of unvoiced frames.

RMS_env

Root mean square of the amplitude envelope.

mean_loudness

Average subjective loudness in sone.

mean_F0

Average fundamental frequency in Hertz.

sd_F0

Standard deviation of the fundamental frequency in Hertz.

mean_entropy

Average Wiener entropy. A value of 0 indicates a pure tone, while a value of 1 indicates white noise.

mean_HNR

Average Harmonics-to-Noise Ratio.

Examples

data(testAudioData)