Improving Loanword Identification in Low-Resource Language with Data Augmentation and Multiple Feature Fusion

Table 6

Loanword identification results on different features (Turkish and Chinese loanword identification as examples).

Donor	Feature(s)	Loanword identification results (%)
				R	R (+)	F1	F1 (+)
Turkish	+fusion	74.14	74.95	73.28	74.16	73.71	74.55
	+pronun	73.96	74.68	73.02	73.94	73.49	74.31
	+pos	72.54	73.36	72.25	73.07	72.39	73.21
	+fusion, pronun	73.40	74.20	72.64	73.40	73.02	73.80
	+fusion, pos	74.63	75.42	73.70	74.52	74.16	74.97
	+pronun, pos	74.25	75.06	73.45	74.24	73.85	74.65
	+all	75.24	76.09	74.36	75.14	74.80	75.61
Chinese	+fusion	73.15	73.94	71.74	72.56	72.44	73.24
	+pronun	72.76	73.52	71.32	72.16	72.03	72.83
	+pos	71.30	72.09	70.58	71.25	70.94	71.67
	+fusion, pronun	72.43	73.25	71.02	71.84	71.72	72.54
	+fusion, pos	73.61	74.40	72.26	73.02	72.93	73.70
	+pronun, pos	73.25	74.03	71.97	72.89	72.60	73.46
	+all	74.30	75.07	72.88	73.95	73.58	74.51