all_data

송지원

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggplot2)
library(readxl)

파일 불러오기

all_data<-read.table("all_data.txt", header=TRUE)
data<-all_data
head(data)

##   filename phoneme duration item height  voice position speed subj
## 1   tack_f       T   45.338 tack    low -voice    final  fast   F1
## 2   tack_f     AE1  150.627 tack    low -voice    final  fast   F1
## 3   tack_f       K   88.059 tack    low -voice    final  fast   F1
## 4  tack_f1       T   47.490 tack    low -voice    final  fast   F1
## 5  tack_f1     AE1  148.429 tack    low -voice    final  fast   F1
## 6  tack_f1       K  110.553 tack    low -voice    final  fast   F1

속도별 모음의 길이

vowel<-data %>% filter(phoneme == "AE1"|phoneme =="EH1"|phoneme =="IH1") %>% group_by(speed,voice) %>% summarise(vowel_duration=mean(duration))

## `summarise()` regrouping output by 'speed' (override with `.groups` argument)

그래프 그리기

ggplot(data=vowel, aes(x=speed, y=vowel_duration, fill=voice))+geom_col(position="dodge")+scale_x_discrete(limits=c("fast","habitual","slow"))

속도별 종성의 길이

coda<-data %>% filter(phoneme == "K"|phoneme =="G") %>% group_by(speed,voice) %>% summarise(coda_duration=mean(duration))

## `summarise()` regrouping output by 'speed' (override with `.groups` argument)

그래프 그리기

ggplot(data=coda, aes(x=speed, y=coda_duration, fill=voice))+geom_col(position="dodge")+scale_x_discrete(limits=c("fast","habitual","slow"))

위치별 모음의 길이

vowel_position<-data %>% filter(phoneme == "AE1"|phoneme =="EH1"|phoneme =="IH1") %>% group_by(position,voice) %>% summarise(vowel_duration=mean(duration))

## `summarise()` regrouping output by 'position' (override with `.groups` argument)

그래프 그리기

ggplot(data=vowel_position, aes(x=position, y=vowel_duration, fill=voice))+geom_col(position="dodge")+scale_x_discrete(limits=c("initial","mid","final"))

위치별 종성의 길이

coda_position<-data %>% filter(phoneme == "K"|phoneme =="G") %>% group_by(position,voice) %>% summarise(coda_duration=mean(duration))

## `summarise()` regrouping output by 'position' (override with `.groups` argument)

그래프 그리기

ggplot(data=coda_position, aes(x=position, y=coda_duration, fill=voice))+geom_col(position="dodge")+scale_x_discrete(limits=c("initial","mid","final"))

변수명 변경

data<-rename(data, vowel_height=height)

모음의 높이에 따른 모음의 길이

vowel_height<-data %>% filter(phoneme == "AE1"|phoneme =="EH1"|phoneme =="IH1") %>% group_by(vowel_height,voice) %>% summarise(vowel_duraiton=mean(duration))

## `summarise()` regrouping output by 'vowel_height' (override with `.groups` argument)

그래프 그리기

ggplot(data=vowel_height, aes(x=vowel_height, y=vowel_duraiton, fill=voice))+geom_col(position="dodge")+scale_x_discrete(limits=c("high","low","mid"))

모음의 높이에 따른 종성의 길이

coda_height<-data %>% filter(phoneme == "K"|phoneme =="G") %>% group_by(vowel_height,voice) %>% summarise(coda_duration=mean(duration))

## `summarise()` regrouping output by 'vowel_height' (override with `.groups` argument)

그래프 그리기

ggplot(data=coda_height, aes(x=vowel_height, y=coda_duration, fill=voice))+geom_col(position="dodge")+scale_x_discrete(limits=c("high","low","mid"))