IEC TR 63558:2025
(Main)Automatic speech recognition: Classification according to acoustic and linguistic indicators in real-life applications
Automatic speech recognition: Classification according to acoustic and linguistic indicators in real-life applications
IEC TR 63558:2025 describes the factors related to classification of the real-life environment according to acoustic indicators and linguistic indicators. The set of factors can be used to describe complexities of use scenarios, from level 1 to 4, and can be helpful when setting up the testing environment.
This document applies for evaluating automatic speech recognition technology which is widely used for smart equipment, such as smart speakers
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Standards Content (Sample)
IEC TR 63558 ®
Edition 1.0 2025-01
TECHNICAL
REPORT
Automatic speech recognition: Classification according to acoustic and
linguistic indicators in real-life applications
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IEC TR 63558 ®
Edition 1.0 2025-01
TECHNICAL
REPORT
Automatic speech recognition: Classification according to acoustic and
linguistic indicators in real-life applications
INTERNATIONAL
ELECTROTECHNICAL
COMMISSION
ICS 33.160.01 ISBN 978-2-8327-0129-4
– 2 – IEC TR 63558:2025 © IEC 2025
CONTENTS
FOREWORD . 3
INTRODUCTION . 5
1 Scope . 6
2 Normative references . 6
3 Terms and definitions . 6
4 Use of automatic speech recognition (ASR) system . 7
5 Needs for standards when using ASR . 7
6 Definition and classification of factors affecting speech recognition . 8
6.1 General . 8
6.2 Acoustic indicators . 8
6.2.1 Signal-to-noise ratio (SNR) . 8
6.2.2 Reflections . 8
6.2.3 Reverberation . 9
6.2.4 Data compression . 9
6.3 Linguistic indicators . 9
6.3.1 Unrestrained syntactical structure . 9
6.3.2 Vocabulary list size . 9
6.3.3 Homonyms . 9
6.3.4 Multilingual words . 9
6.3.5 Speaking speed . 9
6.3.6 Accent . 10
6.3.7 Speaking behavior . 10
7 Existing International Standards . 10
7.1 Inside IEC . 10
7.2 In ISO/IEC Joint Technical Committee 1 . 10
8 Potential items in TC 100 . 10
Annex A (informative) A sample of an indicator set for classification . 11
Bibliography . 13
Table A.1 – Acoustic indicators and classification . 11
Table A.2 – Linguistic indicators and classification . 12
INTERNATIONAL ELECTROTECHNICAL COMMISSION
____________
AUTOMATIC SPEECH RECOGNITION:
CLASSIFICATION ACCORDING TO ACOUSTIC AND
LINGUISTIC INDICATORS IN REAL-LIFE APPLICATIONS
FOREWORD
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IEC TR 63558 by IEC technical committee 100: Audio, video and multimedia systems and
equipment. It is a Technical Report.
The text of this Technical Report is based on the following documents:
Draft Report on voting
100/4214/DTR 100/4263/RVDTR
Full information on the voting for its approval can be found in the report on voting indicated in
the above table.
The language used for the development of this Technical Report is English.
– 4 – IEC TR 63558:2025 © IEC 2025
This document was drafted in accordance with ISO/IEC Directives, Part 2, and developed in
accordance with ISO/IEC Directives, Part 1 and ISO/IEC Directives, IEC Supplement, available
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• reconfirmed,
• withdrawn, or
• revised.
INTRODUCTION
With the development of network and information technology, people are relying more and more
on smart equipment, such as smart speakers, smart service robots and so on. Speech
recognition technology is the main means to realize man-machine communication. Speech
recognition is the process of converting a voice into digital data. Popular use in recent years
has pushed improvements in its algorithm and increased accuracy. But the performance of
different speech recognition solutions differs greatly and is sometimes a source of confusion
for users. The factors used to evaluate the performance of speech recognition technology need
more discussion.
This document mainly aims to set up a set of parameters which can be used to reflect the
complexity of real-life applications, by means of a classification using scenarios.
– 6 – IEC TR 63558:2025 © IEC 2025
AUTOMATIC SPEECH RECOGNITION:
CLASSIFICATION ACCORDING TO ACOUSTIC AND
LINGUISTIC INDICATORS IN REAL-LIFE APPLICATIONS
1 Scope
This document describes the factors related to classification of the real-life environment
according to acoustic indicators and linguistic indicators. The set of factors can be used to
describe complexities of use scenarios, from level 1 to 4, and can be helpful when setting up
the testing environment.
This document applies for evaluating automatic speech recognition technology which is widely
used for smart equipment, such as smart speakers.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following
addresses:
• IEC Electropedia: available at https://www.electropedia.org/
• ISO Online browsing platform: available at https://www.iso.org/obp
3.1
automatic speech recognition
ASR
process of converting human voice signals into digital data
NOTE The output of the speech recognition process is a unique series of data, which can match a predefined word
set then make the machine "understand" the meaning of speaker.
3.2
word set
all the words which can be processed by the speech recognition system
NOTE A word set may contain several languages.
3.3
discrete speech recognition
speaker pronounces each word separately, inserting pauses between each one
EXAMPLE When the sentence "Good to know" is pronounced as [gud], [tu] and [neu], just like three separate words,
this way of speaking is regarded as separated word speech. For a beginner learning a foreign language, this way of
speaking is
...
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