Regional Meeting for Central and Eastern Europe
organized by International
“eAccessibility in Television Broadcasting in
Central and Eastern Europe”
(HRT Academy, Zagreb, Croatia) – 3-4 December 2013)
Subtitling (captioning)
Gion Linder
Head of subtitling SWISS TXT
Chairman Eurovision Access
Services Experts Group
gion.linder@swisstxt.ch
Zagreb, Croatia, 4 December 2013
Topics
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What are subtitles?
Target groups
Legal issues
Technology
Input technologies
Content access
Reception of subtitles
Subtitling market
Quality
Profession subtitler/respeaker
Subtitles on all devices
Added values
International
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What are subtitles?
Subtitles are is a textual version of the dialog or commentary
… [in audiovisual media]. (Wikipedia)
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Intra- / interlingual subtitles
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Closed / open subtitles
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Target groups
Hearing impaired
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Deaf
Hard of hearing
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(WHO: 5% or 360’000’000)
age-related
profound
Late deafened
Deaf children
Foreign language comprehension
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Learners
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Legal issues (1/2)
There would be no such service without legislation
(except the US)
Fields:
• Only broadcast or online as well?
• Subtitles, signed programs,
clean audio
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Legal issues (2/2)
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European directives
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EU encourages member states
National legislation
Voluntary service
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Technology
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Server
Transmission system
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DVB, Teletext or online
Exchange format: STL  EBU TT
Equipment providers
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Screen (Sysmedia)
FAB
Softel
Cavena (Scantitling)
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Input technologies (1/10)
Keyboard
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Ordinary Keyboard
Stenotype
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Short key systems
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e.g. Norway
Fast typers
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only in the UK and US (and Italy)
e.g. Austria
Dual keyboards
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Input technologies (2/10)
Voice recognition
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Respeaking
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Dragon and IBM
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Respeaking with correction
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Available in English, French, German, Spanish,
Italian and Dutch
France (correct sentences vs. delay)
Automatic voice recognition
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Input technologies (3/10)
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Input technologies (4/10)
Automatic subtitling
= recognition + creation of subtitles
• for live programs, with subsequent
correction, alignment service
• Problems that might occur
• Challenges
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Input technologies (5/10)
Automatic subtitling
NER value from different providers
Prepared
Spontaneous
German
87.5
81.1
90.3
83.1
94.9
82.9
French
93.6
91.5
94.4
Italian
93.0
92.3
90.8
86.9
86.6
85.0
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analyzed with NERstar
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Input technologies (6/10)
Automatic subtitling - Difficulties
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Spoken vs. written language
Different from standard language
Background music/noise
Big variation within a program
Wrong recognized words
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Input technologies (7/10)
Savas project
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EU funded, 2 years
6 languages: German, French, Italian,
Spanish, Portuguese and Basque
Goal: live subtitling of news programs
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Input technologies (8/10)
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Input technologies (9/10)
Automatic subtitling - Conclusions
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Not all kind of programs suit
Standard language
Without spontaneous speech
Homogenous program format
Noise and background sound
standardized
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Input technologies (10/10)
Automatic subtitling
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Possible area of use
Local programs
Automatic recognition with postponed
correction
Subtitles available on the internet and
HbbTV
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Content access
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Prerecorded programs
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Access to content as early as possible
Convert to low res (+ meta data)
Distribution
Attach to data base or copy on MXF
Live programs
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Access to news desk
Access to prerecorded videos
Near live: access to audio at least
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Reception of subtitles (1/5)
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Display on screen
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Common sense
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2 lines, on the bottom
Double height
Only bright colors
Duration chps or wpm
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Reception of subtitles (2/5)
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Processing live subtitles
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Scrolling vs. blocks
Time spent on images
Hearing
Hard-of-Hearing
Deaf
Blocks
33.3%
33.2%
31.7%
Scrolling
11.7%
11.4%
14.3%
Source: Pablo Romero-Fresco
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Reception of subtitles (3/5)
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Reception of subtitles (4/5)
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Reception of subtitles (5/5)
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Subtitling market
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Prerecorded programs
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Hard competition
Easy to enter the market
Live programs
Follow the value chain
Costs for a broadcaster
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Different ways to fulfill: With or without
an own staff
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Quality (1/7)
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Definition of quality
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Pretty easy for prerecorded programs
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Correctly, regarding content and grammar
Word order and key words
Verbatim as long as possible
Description of non visible sounds
Linguistic nuances, ambiguities, irony
In sync and frame accurate
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Easy language?
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Quality (2/7)
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Definition of quality
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For live programs
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Verbatim vs. slight synthesis
Scrolling vs. block
Real live vs. postponed editing (delay!)
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Quality (3/7)
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Quality assessment
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For live programs
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Word error rate
NER model
Assessment in the UK
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So far: WER
New: NER model
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90 minutes per year per channel
News, entertainment and sports
Supervision by Roehampton University
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Quality (4/7)
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Quality (5/7)
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NER model: error examples
Serious
he’s having problems with the cheques instead of

he’s having problems with the Czechs
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Normal
he’s a buy you a bull asset instead of

he’s a valuable asset
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Minor
imon brown has been appointed new chairman of Rolls
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Royce instead of
Simon Brown has been appointed new chairman of Rolls
Royce
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Quality (6/7)
NERstar tool
• All you need:
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video, subtitle, transcript
Calculates the NERvalue and the delay
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Quality (7/7)
NER model
• British Ofcom plans:
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6 videos, 5 minutes each for news,
entertainment and sports
Supervising Roehampton university
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Profession subtitler
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Ordinary subtitler
Respeaker
In the future only corrector?
Precarious work situation
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Subtitles on all devices
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From linear to non linear
New format  EBU TT
On all devices?
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On
On
On
On
the own webpage?
HbbTV?
TV service providers like Zattoo?
mobile devices?
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Added values
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Subtitles may improve
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the search in the own archives
the search for video search engines
Subtitles may be useful
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for recognition software
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International
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Awareness
EBU: Eurovision Access services
experts group
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Knowledge exchange
Interfere when necessary
ITU: Focus Group
Other stakeholders
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Thank you!
gion.linder@swisstxt.ch
Geneva, Switzerland, 24 October 2013
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