Publication Details
Measuring Speech Recognition And Understanding Performance in Air Traffic Control Domain Beyond Word Error Rates
SHETTY, S.
KLEINERT, M.
OHNEISER, O.
EHR, H.
Motlíček Petr, doc. Ing., Ph.D. (DCGM)
Prasad Amrutha (DCGM)
WINDISCH, C.
and others
word error rate, command recognition rate, language
understanding, air traffic control, ATC, unclassified word rate
Applying Automatic Speech Recognition (ASR) in the
domain of analogue voice communication between air traffic controllers
(ATCo) and pilots has more end user requirements than
just transforming spoken words into text. It is useless for, e.g.,
readback error detection support, if word recognition is perfect,
as long as the semantic interpretation is wrong. For an ATCo it is
of almost no importance if the words of a greeting are correctly
recognized. A wrong recognition of a greeting should, however, not
disturb the correct recognition of, e.g., a descend command.
More important is the correct semantic interpretation. What, however,
is the correct semantic interpretation especially when ATCos
or pilot, deviate more of less from published standard phraseology?
For comparing performance of different speech recognition
applications, 14 European partners from Air Traffic Management
(ATM) domain have recently agreed on a common set of rules, i.e.,
an ontology on how to annotate the speech utterances of an ATCo
on semantic level. This paper first presents the new metric of unclassified
word rate, extends the ontology to pilot utterances, and
introduces the metrics of command recognition rate, command
recognition error rate, and command recognition rejection rate.
This enables the comparison of different speech recognition and
understanding instances on semantic level. The implementation
used in this paper achieves a command recognition rate better
than 96% for Prague Approach, even if word error rate is above
2.5% based on more than 12,000 ATCo commands recorded in
both operational and lab environment. This outperforms previous
published rates by 2% absolute.
@inproceedings{BUT176486,
author="HELMKE, H. and SHETTY, S. and KLEINERT, M. and OHNEISER, O. and EHR, H. and MOTLÍČEK, P. and PRASAD, A. and WINDISCH, C.",
title="Measuring Speech Recognition And Understanding Performance in Air Traffic Control Domain Beyond Word Error Rates",
booktitle="Proceedings of 11th SESAR Innovation Days 2021",
year="2021",
pages="1--8",
address="Belgie",
url="https://www.fit.vut.cz/research/publication/12684/"
}