This study applied an innovative approach to design MMRT word lists from familiar and homogeneous monosyllables, in which the familiarity, homogeneity, and phonemic balance of the six 25-item and nine 50-item word lists were strictly controlled. These word lists exhibit interlist equivalence with respect to their psychometric functions and five psychometric characteristics; moreover, their interitem and intersubject variability are lower than those of previously reported lists. Future clinical experiments should examine whether such a design approach can improve the reliability and diagnostic sensitivity of word recognition tests for hearing-impaired listeners.

Speech audiometric tests have been widely used for advanced hearing diagnoses and in rehabilitation. However, there are no standardised speech tests for more than 90% of the world's population, who do not speak English. A major problem in the design of a speech audiometric test is that the selection of test materials is subject to multiple criteria, and its complexity rises dramatically as the structure of test items changes from phonemic or monosyllabic forms to disyllabic or polysyllabic forms. A genetic algorithm is presented that can automatically select a set of disyllabic words from a large Mandarin corpus. The selection accords with the following principal criteria for the items constituting a speech discrimination test: similarity in structure, familiarity to the subjects, and a phonemically balanced composition. The performance of the genetic algorithm was evaluated by computation of the distance between a target vector, specifying the desired distribution of initial and final syllables and tone patterns for daily disyllabic word usage, and the vector derived by the search results of the algorithm. The use of the genetic algorithm was illustrated by its application to the selection of test lists from two Mandarin corpora. The results showed that, for a given corpus, at least 12 disyllabic word lists with a distance of less than 20 could be generated within 72 h. The genetic algorithm performed an efficient, robust and low-complexity search of the problem space and can be easily modified to adapt to the material selection of other languages.

The psychometric functions of the 700 most frequently occurring Mandarin monosyllables (whose cumulative usage was 98.38% in 1,125 distinct monosyllables) were evaulated. Twenty normal-hearing subjects were asked to hear and to repeat the 700 monosyllables which were randomly presented at the level from 0 to 55 dB HL in 5-dB step. The psychometric functions for each of the 700 monosyllables were fit with third-degree polynomials. The fitted curves were used to calculate five psychometric characteristics: (1) the threshold at 0% correct; (2) the threshold at 50% correct; (3) the instantaneous slope at 50% correct; (4) the linear slope from 20% to 80% correct; and (5) the intelligibility at the highest presentation level. The mean values of such five psychometric characteristics for 700 monosyllables are 1.1 dBHL, 12.1 dBHL, 4.5 %/dB, 4.1% %/dB, and 93.4%, respectively. With the psychometric characteristics, the 700 monosyllables can be used to create word recognition test lists for different purposes, such as constructing test lists with different homogeneity, different familiarity, or different difficulty; and the recognition performance of test lists will be predictable. Futhermore, the research results also indicated that there is no significant correlation between the psychometric characteristics and the occurring frequences of monosyllables.