Skip to main content
. 2022 May 4;37(18):e144. doi: 10.3346/jkms.2022.37.e144

Table 3. Accuracy according to cloud-based speech recognition open application programming interface.

Characteristics Total words Naver Google Amazon Naver vs. Google Naver vs. Amazon Google vs. Amazon
Total 7,319 5,493 (75.1) 3,726 (50.9) 4,237 (57.9) < 0.001 < 0.001 < 0.001
Class
Department 276 145 (52.5) 141 (51.1) 128 (46.4) 0.320 0.140 0.630
Symptom, disease 1,343 1,060 (78.9) 718 (53.5) 869 (64.7) < 0.001 0.005 0.008
Organ, location 1,935 1,627 (84.1) 1,104 (57.1) 1,410 (72.9) < 0.001 0.003 0.700
Test 1,160 799 (68.9) 601 (51.8) 587 (50.6) 0.140 0.190 0.930
Treatment 1,251 944 (75.5) 522 (41.7) 605 (48.4) 0.110 0.060 0.780
Medication 1,139 840 (73.7) 569 (50.0) 589 (51.7) 0.330 0.330 0.980
Specific name of a medication 215 79 (36.7) 71 (33.0) 49 (22.8) 0.005 0.760 0.010
Word length
1 1,108 894 (80.7) 542 (48.9) 658 (59.4) < 0.001 0.030 0.002
2 3,695 3,049 (82.5) 1,874 (50.7) 2,387 (64.6) < 0.001 < 0.001 < 0.001
3 1,468 955 (65.1) 749 (51.0) 740 (50.4) 0.290 0.100 0.540
4 659 408 (61.9) 337 (51.1) 305 (46.3) 0.900 0.080 0.090
5 325 171 (52.6) 183 (56.3) 119 (36.6) 0.430 0.110 0.010
6 61 15 (24.6) 39 (36.9) 27 (44.3) 0.250 0.670 0.460
7 1 1 (100.0) 1 (100.0) 1 (100.0) - - -
8 2 1 (50.0) 1 (50.0) 0 - - -
Non-Korean terms 459 269 (58.6) 163 (35.5) 142 (30.9) 0.990 0.100 0.090

Data are presented as number (%).