28 lines
1.1 KiB
Bash
28 lines
1.1 KiB
Bash
#!/bin/bash
|
|
|
|
# Prepare hypothesis file based on column 2
|
|
cut -f2 'wikiniews_results.tsv' > hypothesis.txt
|
|
# Prepare reference file based on column 3
|
|
cut -f3 'wikiniews_results.tsv' > reference.txt
|
|
|
|
# awk transfer txt to .trn
|
|
awk 'BEGIN{FS=OFS="\t"}{print $0,"(sp1_"NR")"}' < reference.txt > reference.trn
|
|
awk 'BEGIN{FS=OFS="\t"}{print $0,"(sp1_"NR")"}' < hypothesis.txt > hypothesis.trn
|
|
|
|
# use sclite to calculate WER, actually we need only lines starting with 'Scores'
|
|
sclite -f 0 -r reference.trn trn -h hypothesis.trn trn -e utf-8 -i rm -o all stdout | grep "Scores:" > wer_results.txt
|
|
|
|
cat wer_results.txt | awk '{print ( ($7 + $8 + $9) / ($7 + $8 + $6) ) * 100;}' >> wer_per_line.txt
|
|
awk '{getline l < "wer_per_line.txt"; print $0"\t"l} ' wikiniews_results.tsv > wikinews_results.tsv
|
|
|
|
# calculate mean WER for all records
|
|
awk '{sum += $1; n++} END { print sum / n; }' < wer_per_line.txt > wer.txt
|
|
|
|
# calculate SSR
|
|
awk '{if ($1 == 0) acc += 1;} END { print ( acc / NR) * 100; }' < wer_per_line.txt > srr.txt
|
|
|
|
rm wer_per_line.txt
|
|
rm hypothesis.txt
|
|
rm reference.txt
|
|
rm wer_results.txt
|