  A practical speech audiometry tool is the digits-in-noise (DIN) test for
hearing screening of populations of varying ages and hearing status. The test
is usually conducted by a human supervisor (e.g., clinician), who scores the
responses spoken by the listener, or online, where a software scores the
responses entered by the listener. The test has 24 digit-triplets presented in
an adaptive staircase procedure, resulting in a speech reception threshold
(SRT). We propose an alternative automated DIN test setup that can evaluate
spoken responses whilst conducted without a human supervisor, using the
open-source automatic speech recognition toolkit, Kaldi-NL. Thirty
self-reported normal-hearing Dutch adults (19-64 years) completed one
DIN+Kaldi-NL test. Their spoken responses were recorded, and used for
evaluating the transcript of decoded responses by Kaldi-NL. Study 1 evaluated
the Kaldi-NL performance through its word error rate (WER), percentage of
summed decoding errors regarding only digits found in the transcript compared
to the total number of digits present in the spoken responses. Average WER
across participants was 5.0% (range 0 - 48%, SD = 8.8%), with average decoding
errors in three triplets per participant. Study 2 analysed the effect that
triplets with decoding errors from Kaldi-NL had on the DIN test output (SRT),
using bootstrapping simulations. Previous research indicated 0.70 dB as the
typical within-subject SRT variability for normal-hearing adults. Study 2
showed that up to four triplets with decoding errors produce SRT variations
within this range, suggesting that our proposed setup could be feasible for
clinical applications.
