PRESTO: Perceptually robust English sentence test: Open-set—Design, philosophy, and preliminary findings

Traditional clinical word recognition tests (e.g., SPIN and HINT) do not reflect variability in real world environments. These tests are often constructed with predictable short sentences spoken by a small number of talkers without dialect variation; thus, individual differences are difficult to uncover. To compensate for these shortcomings, PRESTO uses materials taken from the TIMIT database in order to incorporate variation in talkers, dialects, and number of words in a sentence. Familiarity and lexical frequency, syntactic structure, and semantic content are also considered. To provide normative data, normal-hearing young listeners performed an open-set identification task with the PRESTO materials in open field with six-talker babble mixed at different signal-to-noise ratios and also with no additional background noise. The HINT sentences were also used with the same listeners to assess the validity of PRESTO. Results indicate that listeners perform near ceiling for both the PRESTO and HINT materials in ideal listening conditions. However, under degraded listening conditions, the PRESTO shows much greater variability. Preliminary results from a clinical population also indicate that the more challenging PRESTO lists reveal individual differences among patients which are not apparent from scores on the HINT. [NIDCD T32-DC00012.]