1 00:00:00,000 --> 00:00:05,495 [LTA music] 2 00:00:08,653 --> 00:00:13,280 We are talking about speech-to-text interpreter. 3 00:00:13,360 --> 00:00:15,240 We talked about hearing aids. 4 00:00:15,320 --> 00:00:20,775 We talked about the importance to have good internet connection. 5 00:00:21,181 --> 00:00:23,118 The importance to have maybe 6 00:00:23,160 --> 00:00:26,460 the speech-to-text interpreter in front of you. 7 00:00:27,238 --> 00:00:29,831 The importance of good acoustic. 8 00:00:30,549 --> 00:00:34,924 Anything [else] that you think might be important? 9 00:00:36,609 --> 00:00:37,740 Yeah, light. 10 00:00:38,489 --> 00:00:45,485 Just for this my picture is a lot darker than the 2 of yours. 11 00:00:45,859 --> 00:00:49,700 But I still think that my facial expressions are there. 12 00:00:49,950 --> 00:00:52,146 The light means a lot. 13 00:00:52,395 --> 00:00:56,112 I have also been FaceTiming with people with hearing loss 14 00:00:56,331 --> 00:00:58,304 and they said: “Could you [move] a little, 15 00:00:58,360 --> 00:01:02,395 because you have some light coming in behind you?” 16 00:01:02,579 --> 00:01:05,579 And that would disturb the lip-reading. 17 00:01:05,704 --> 00:01:09,039 Marcel, would you like to add something? 18 00:01:09,351 --> 00:01:11,611 Yes, for me is the same. 19 00:01:11,736 --> 00:01:17,756 Light is very important to see the face for the non-verbal communication 20 00:01:17,840 --> 00:01:20,431 but also for reading the lips. 21 00:01:23,583 --> 00:01:30,000 There is something that I don’t like, but yours is working fine, 22 00:01:30,557 --> 00:01:33,991 and that is the “electronic background” behind. 23 00:01:34,116 --> 00:01:38,259 Because sometimes the faces are a little bit moving 24 00:01:38,384 --> 00:01:42,600 or you cannot see very good the faces. 25 00:01:42,940 --> 00:01:46,986 This makes the lip-reading more difficult. 26 00:01:47,828 --> 00:01:50,159 We call it “visual noise”. 27 00:01:51,408 --> 00:01:57,470 Maybe to have not this background maybe, but like a “video” background. 28 00:01:58,063 --> 00:02:00,064 No, not a video, thank you! 29 00:02:00,470 --> 00:02:02,069 It moves too much. 30 00:02:02,506 --> 00:02:04,198 It’s very disturbing. 31 00:02:04,759 --> 00:02:06,767 So that is “visual noise”. 32 00:02:07,360 --> 00:02:13,761 Before you said that subtitles must be word-by-word subtitles: 33 00:02:13,948 --> 00:02:15,387 that is very important. 34 00:02:15,790 --> 00:02:21,401 You know, in LTA project, we also care about accessibility, 35 00:02:22,368 --> 00:02:28,771 for persons who need more simplified subtitles. 36 00:02:29,614 --> 00:02:31,754 What do you recommend about it? 37 00:02:32,285 --> 00:02:37,614 Do you prefer more simplified subtitles, or less simplified subtitles? 38 00:02:37,739 --> 00:02:42,692 And why do you think, and in what situation do you think 39 00:02:42,911 --> 00:02:48,836 easy-subtitles should be a plus for some persons? 40 00:02:49,179 --> 00:02:54,000 Well, I like to have what happens in the room interpreted to me. 41 00:02:54,248 --> 00:03:00,000 But I don’t want so much: to have interpreted what it’s meant. 42 00:03:01,242 --> 00:03:03,250 That is for my brain to do that. 43 00:03:03,531 --> 00:03:06,221 Again, some people might need that. 44 00:03:06,439 --> 00:03:12,000 For a conference, for instance, it would be nice that you tick the box 45 00:03:12,593 --> 00:03:15,795 of what kind of accessibility you need. 46 00:03:16,076 --> 00:03:18,966 Do you need verbatim? Or do you need easy-to-read? 47 00:03:19,110 --> 00:03:23,459 Because it may not be the same interpreter that we should use. 48 00:03:23,680 --> 00:03:27,214 Yeah. Can I give you an example? 49 00:03:27,370 --> 00:03:30,000 When you look to the Teletubbies, 50 00:03:30,531 --> 00:03:35,152 on the television, that is a program for small kids. 51 00:03:35,797 --> 00:03:39,304 There, the spoken language is in very simple words. 52 00:03:39,710 --> 00:03:45,354 Then, it’s also important that each word is typed. 53 00:03:45,947 --> 00:03:48,146 But when you are working 54 00:03:48,552 --> 00:03:51,738 in an academic meeting or in other meeting, 55 00:03:54,169 --> 00:03:57,107 and there are a lot of difficult words, 56 00:03:58,387 --> 00:04:02,570 then it is also important that each word is typed. 57 00:04:02,724 --> 00:04:08,308 Personally, I don’t like so much to have them simpler. 58 00:04:08,775 --> 00:04:12,326 Maybe when the speech goes so fast 59 00:04:12,825 --> 00:04:17,353 that you don’t know what the client is saying, 60 00:04:17,600 --> 00:04:22,070 you say: “Ok, what are we doing? Do we make it more summarized?” 61 00:04:23,131 --> 00:04:29,029 or “Do we make more short breaks for the interpreter?” 62 00:04:29,341 --> 00:04:31,047 That is also an option. 63 00:04:32,514 --> 00:04:37,515 And of course this is related to the time of meeting. 64 00:04:40,012 --> 00:04:44,532 Is it a very short meeting with the interpreter? 65 00:04:45,686 --> 00:04:48,164 Then for me it’s not a big problem, 66 00:04:48,445 --> 00:04:54,000 when it is not so accurate, 67 00:04:54,325 --> 00:04:57,104 or there are more spelling mistakes. 68 00:04:59,413 --> 00:05:04,953 But at work settings, I thing also for students at education settings, 69 00:05:05,140 --> 00:05:11,127 it is very important that you have a good quality of the speech-to-text. 70 00:05:14,216 --> 00:05:19,002 People with learning difficulties or with language difficulties, 71 00:05:19,376 --> 00:05:22,031 if you work for them, of course: 72 00:05:22,184 --> 00:05:29,200 then is fine to have the subtitles or the speech-to-text 73 00:05:29,356 --> 00:05:31,200 in more easier language. 74 00:05:32,009 --> 00:05:38,128 But when the presentation is not in easy language, 75 00:05:38,752 --> 00:05:42,781 then it is a very difficult question. 76 00:05:43,153 --> 00:05:51,370 It is up to the speech-to-text interpreter to make the language easier in the text. 77 00:05:52,150 --> 00:05:54,356 Personally, I don't like it. 78 00:05:54,544 --> 00:05:56,071 I also don't like 79 00:05:56,258 --> 00:06:04,281 when sign language interpreters make it easier for the Deaf person. 80 00:06:06,775 --> 00:06:11,238 I think it's not the job or the role of the interpreter. 81 00:06:12,518 --> 00:06:16,797 That is a bit of a personal opinion. 82 00:06:18,000 --> 00:06:23,296 I think the message from a speaker, 83 00:06:25,481 --> 00:06:30,842 we should not have interpreted what that person thinks about this topic. 84 00:06:31,060 --> 00:06:35,019 We should be informed of what is a person saying 85 00:06:35,425 --> 00:06:37,259 and then we should manage 86 00:06:37,360 --> 00:06:41,225 to understand what is the meaning in this topic. 87 00:06:41,691 --> 00:06:44,002 Some years ago back at a conference, 88 00:06:44,158 --> 00:06:49,528 I had some speech-to-text and I was all the time on the screen informed: 89 00:06:49,682 --> 00:06:51,330 “They are talking about…” 90 00:06:52,048 --> 00:06:56,560 And I was thinking: “Yeah, but what are they saying about that topic?” 91 00:06:56,716 --> 00:07:00,848 In during the breaks afterwards, if I want to go to the speaker 92 00:07:00,960 --> 00:07:02,159 and ask a question, 93 00:07:02,316 --> 00:07:06,840 I’m not able to ask qualified questions, because I don’t really know 94 00:07:07,225 --> 00:07:09,809 what the person was saying about the topic. 95 00:07:09,965 --> 00:07:12,397 All I could address would be to say: 96 00:07:12,553 --> 00:07:14,709 “So, you were talking about that topic?” 97 00:07:14,925 --> 00:07:17,334 Yeah, how interesting is that. 98 00:07:17,552 --> 00:07:19,946 And this is a problem I think. 99 00:07:20,102 --> 00:07:22,669 Sometimes this is our situation 100 00:07:22,825 --> 00:07:27,101 and all the people may think that we don’t really understand anything. 101 00:07:28,318 --> 00:07:29,761 That is important, 102 00:07:29,880 --> 00:07:35,475 that we still get our brains to work at that high intellectual level, 103 00:07:35,753 --> 00:07:37,067 that we are able to. 104 00:07:37,660 --> 00:07:42,762 We talked about the working settings. 105 00:07:44,167 --> 00:07:50,604 In what other environments do you think that real-time subtitles should be provided 106 00:07:50,760 --> 00:07:56,356 so that people who use hearing aids can have full accessibility? 107 00:07:57,916 --> 00:08:02,981 I think that is very important also to talk about education settings. 108 00:08:03,387 --> 00:08:10,469 Aida can say something more about the primary school and secondary school. 109 00:08:10,906 --> 00:08:15,973 But we see also more and more lifetime education 110 00:08:16,472 --> 00:08:18,691 at work, in your free time. 111 00:08:19,562 --> 00:08:26,014 And that is also fine that you have the possibility to hire 112 00:08:26,080 --> 00:08:28,170 a speech-to-text interpreter. 113 00:08:32,349 --> 00:08:37,976 Here is the same question and discussion as we had before. 114 00:08:38,195 --> 00:08:44,085 Is the training course about motors of cars 115 00:08:44,241 --> 00:08:47,645 or very technical aspects? 116 00:08:48,579 --> 00:08:52,563 Or a training course about the history of Denmark? 117 00:08:52,969 --> 00:09:01,145 Then, it is also needed different types of speech-to-text interpreters. 118 00:09:02,206 --> 00:09:08,341 The one speech-to-text interpreter that have more feeling for technical stuff 119 00:09:08,528 --> 00:09:09,913 related in cars, 120 00:09:10,350 --> 00:09:16,906 and the other maybe have more feelings for history. 121 00:09:18,683 --> 00:09:23,608 But some speech-to-text interpreter can do both very well. 122 00:09:25,075 --> 00:09:26,671 Maybe most of the times. 123 00:09:27,045 --> 00:09:31,200 That is also related to the personal interests 124 00:09:31,320 --> 00:09:32,754 of speech-to-text interpreters. 125 00:09:32,940 --> 00:09:36,183 But for example when you go to a training course 126 00:09:36,464 --> 00:09:39,151 at the university or in high-school, 127 00:09:40,117 --> 00:09:44,032 also there it is a little bit the same than in work settings. 128 00:09:44,187 --> 00:09:45,568 How is the room? 129 00:09:45,818 --> 00:09:48,815 Are the people sitting in a circle? 130 00:09:49,189 --> 00:09:51,009 How big is the group? 131 00:09:51,259 --> 00:09:53,520 Are there 10 people talking? 132 00:09:53,832 --> 00:09:59,109 This is different than 100 people sitting in a theatre setting. 133 00:10:00,000 --> 00:10:03,766 And also there, for me is important the light, 134 00:10:04,016 --> 00:10:07,139 the acoustics, no background noises, 135 00:10:07,398 --> 00:10:10,423 if I can see the speakers very well. 136 00:10:11,203 --> 00:10:15,615 Is it needed that I use the neckloop system, 137 00:10:15,788 --> 00:10:21,148 so that I give the speaker, or the teacher, a special mic? 138 00:10:23,177 --> 00:10:25,400 Then we have the speech-to-text interpreter. 139 00:10:25,480 --> 00:10:29,523 Then it is important to say that the transcript 140 00:10:29,844 --> 00:10:35,871 that the speech-to-text interpreter makes is only for the student, 141 00:10:37,338 --> 00:10:41,086 and is not for all the students in the classroom. 142 00:10:42,206 --> 00:10:46,262 The speech-to-text interpreter makes it only for the student. 143 00:10:46,730 --> 00:10:50,945 That is possible in the Netherlands, 144 00:10:51,507 --> 00:10:54,381 but for example in the Scandinavian countries 145 00:10:54,627 --> 00:10:59,053 it is not possible to share the transcript. 146 00:10:59,209 --> 00:11:03,802 Or that the interpreter gives the transcript 147 00:11:03,989 --> 00:11:06,207 of the meeting to the client. 148 00:11:06,362 --> 00:11:11,786 That also happens in work settings and in other meetings. 149 00:11:12,317 --> 00:11:15,390 I think that Aida maybe can say something about 150 00:11:15,858 --> 00:11:20,822 speech-to-text interpreters at the secondary and the primary schools. 151 00:11:22,975 --> 00:11:28,892 I have worked as a consultants for school children with hearing loss 152 00:11:29,297 --> 00:11:31,547 included in local settings. 153 00:11:32,952 --> 00:11:40,303 It is still not used that we introduce speech-to-text to these kids. 154 00:11:40,490 --> 00:11:48,181 And if you look to Great Britain, they have puppet theatre with subtitles. 155 00:11:49,335 --> 00:11:52,264 For instance, Little Red Riding Hood. 156 00:11:52,389 --> 00:11:55,731 They would put up a picture of Little Red Riding Hood 157 00:11:55,887 --> 00:11:59,335 and then it would be written what is she saying. 158 00:12:00,000 --> 00:12:02,335 You can actually practice reading. 159 00:12:02,482 --> 00:12:05,868 To read with inderstanding. 160 00:12:07,303 --> 00:12:11,414 It can be done, but it is still not introduced here. 161 00:12:11,570 --> 00:12:17,313 The typical thing is not until a young person goes into university, 162 00:12:17,360 --> 00:12:19,672 then they are introduced to speech-to-text, 163 00:12:20,110 --> 00:12:23,389 which is very strange. Really, really strange. 164 00:12:23,576 --> 00:12:25,855 And they have never heard of it until then. 165 00:12:26,167 --> 00:12:30,080 I’m quite convinced that it should be introduced 166 00:12:30,160 --> 00:12:35,727 because it is a good mean for these kids to have it. 167 00:12:36,944 --> 00:12:41,211 It is sometimes used if a film is being shown, 168 00:12:41,367 --> 00:12:46,986 to have the subtitles put on, if they’re available. 169 00:12:47,298 --> 00:12:50,773 And then you mentioned Marcel to have the transcript. 170 00:12:51,865 --> 00:12:55,480 That is not possible in the Scandinavian countries. 171 00:12:55,560 --> 00:12:59,784 You can, in the Netherlands, have the transcript from a meeting. 172 00:13:00,408 --> 00:13:04,134 I think in the UK they can pay to have the transcript, 173 00:13:04,200 --> 00:13:06,134 where you can have it for free. 174 00:13:06,381 --> 00:13:10,207 But that is also a legal thing in the Scandinavian countries, 175 00:13:10,332 --> 00:13:15,114 so that the interpreter cannot risk to be taken to court 176 00:13:15,270 --> 00:13:17,832 for something being said in a meeting. 177 00:13:18,110 --> 00:13:20,632 It depends on what kind of meeting it is, of course. 178 00:13:20,788 --> 00:13:24,982 I do appreciate when I work in international settings. 179 00:13:25,169 --> 00:13:27,677 There I can have a transcript after a meeting, 180 00:13:28,051 --> 00:13:31,361 so that I can run through all the different topics again. 181 00:13:31,611 --> 00:13:34,760 Because I still do concentrate in more ways 182 00:13:34,880 --> 00:13:37,235 than somebody who has a typical hearing. 183 00:13:37,672 --> 00:13:38,720 Sure. 184 00:13:39,500 --> 00:13:44,000 So to fill the gaps that maybe you could have 185 00:13:44,780 --> 00:13:46,218 during the meeting. 186 00:13:46,402 --> 00:13:47,705 Yeah, quite. 187 00:13:48,797 --> 00:13:52,298 And what other settings do you think 188 00:13:52,860 --> 00:13:56,233 should provide a speech-to-text interpreter? 189 00:13:57,510 --> 00:13:59,329 We talked about school now. 190 00:13:59,672 --> 00:14:04,475 It is good to say something about cultural life. 191 00:14:06,316 --> 00:14:08,785 The film for example in the Netherlands. 192 00:14:09,035 --> 00:14:15,176 When you go to the cinema, all the movies from abroad have subtitles. 193 00:14:15,488 --> 00:14:21,617 But all the movies in the Dutch language have no subtitling. 194 00:14:21,992 --> 00:14:28,635 Sometimes, there are special film meetings 195 00:14:30,000 --> 00:14:33,311 with subtitling, but they are very limited. 196 00:14:33,534 --> 00:14:36,370 The same happens in the theatre. 197 00:14:36,557 --> 00:14:40,647 In the theatre, the plays are without subtitles. 198 00:14:40,803 --> 00:14:44,576 Also musicals are without subtitles. 199 00:14:45,076 --> 00:14:49,157 Only the operas have subtitles, 200 00:14:49,200 --> 00:14:56,369 but they are in the top of the theatre, in the top of the stage. 201 00:14:56,771 --> 00:14:59,650 There, you can read the speech-to-text. 202 00:14:59,837 --> 00:15:03,930 Some years ago, Aida and I were in Oslo, 203 00:15:04,180 --> 00:15:06,490 in the beautiful theatre. 204 00:15:06,989 --> 00:15:10,357 The Opera House in Oslo, maybe you know that? 205 00:15:10,544 --> 00:15:17,285 There you can read the subtitles in the back of the chair before you. 206 00:15:17,566 --> 00:15:20,617 Then you can have 2 options: 207 00:15:20,929 --> 00:15:23,054 to have the subtitles in English, 208 00:15:26,487 --> 00:15:29,392 or in Norwegian. 209 00:15:31,322 --> 00:15:35,568 But maybe in Denmark there are other possibilities? 210 00:15:36,972 --> 00:15:39,875 No, we don’t have that. 211 00:15:40,093 --> 00:15:45,083 But we do have in the opera the subtitles. 212 00:15:45,239 --> 00:15:47,329 They are just above the stage. 213 00:15:47,480 --> 00:15:52,620 I think in opera, when they sing the same text for a very long time, 214 00:15:52,839 --> 00:15:55,371 it is not so hard with operas. 215 00:15:55,963 --> 00:15:59,324 We are better now with films in Danish, 216 00:15:59,792 --> 00:16:07,160 because film producers here receive support 217 00:16:07,347 --> 00:16:08,707 from the Danish state. 218 00:16:09,423 --> 00:16:13,877 If they do not provide subtitles, then they would not have the support. 219 00:16:15,593 --> 00:16:19,870 That’s a financial thing, and is apparently a good way to do it. 220 00:16:20,151 --> 00:16:20,964 Yeah. 221 00:16:21,775 --> 00:16:24,529 But also here you see a lot of differences. 222 00:16:24,811 --> 00:16:25,978 In Sweden, 223 00:16:26,290 --> 00:16:31,161 all the films in the Swedish language are with subtitles. 224 00:16:31,752 --> 00:16:35,480 In the United Kingdom you see that musicals 225 00:16:35,560 --> 00:16:39,346 and a lot of places are with subtitles. 226 00:16:39,564 --> 00:16:42,000 Not all, but a lot of. 227 00:16:42,080 --> 00:16:47,202 For example, in big theatres in London, but also all over the country, 228 00:16:47,514 --> 00:16:53,224 there are a lot of situations where speech-to-text is included. 229 00:16:53,755 --> 00:16:56,385 To summarize a little bit. 230 00:16:56,603 --> 00:16:58,692 This is our final question. 231 00:16:59,004 --> 00:17:02,379 Since the necessity to provide real-time subtitles 232 00:17:02,691 --> 00:17:06,876 for persons who use hearing aids is a topic that, 233 00:17:07,313 --> 00:17:11,398 as we have seen, is not discussed very often. 234 00:17:11,617 --> 00:17:15,103 What is your final recommendation? 235 00:17:17,256 --> 00:17:22,835 Maybe to say something about settings, 236 00:17:23,116 --> 00:17:26,364 also for personal situations. 237 00:17:26,705 --> 00:17:35,542 At parties, but also not nice settings, when you need to go to a funeral, 238 00:17:35,729 --> 00:17:38,133 or you need to go to the hospital. 239 00:17:38,289 --> 00:17:42,360 In that kind of “personal” moment, 240 00:17:42,480 --> 00:17:46,047 you can also use a speech-to-text interpreter. 241 00:17:46,231 --> 00:17:50,651 Personally, I don’t do that so much and I am a little bit doubting. 242 00:17:50,901 --> 00:17:53,206 Some people like to do that. 243 00:17:54,610 --> 00:17:58,398 Sometimes it can be a little bit complicated. 244 00:17:58,928 --> 00:18:01,199 When you go to a marriage, 245 00:18:02,198 --> 00:18:06,000 or a party from a friend of yours, 246 00:18:06,130 --> 00:18:11,277 and you take a speech-to-text interpreter with you. 247 00:18:11,527 --> 00:18:17,585 Then, it is very important that you contacted before your friend 248 00:18:17,741 --> 00:18:23,736 [and ask] if it is OK that you bring the speech-to-text interpreter with you. 249 00:18:24,000 --> 00:18:27,289 For example, when I have a birthday party 250 00:18:27,695 --> 00:18:30,319 in my family, I never do that. 251 00:18:30,504 --> 00:18:35,555 And when I do that, they look a little bit: 252 00:18:36,460 --> 00:18:41,424 “Oh, what is happening to you? What is this person doing?” 253 00:18:42,235 --> 00:18:46,121 Then it is very important a good introduction 254 00:18:46,402 --> 00:18:48,556 of the speech-to-text interpreter. 255 00:18:48,743 --> 00:18:54,573 Also in work settings is very important that I, 256 00:18:54,760 --> 00:18:58,227 as a hard of hearing person, but also the speech-to-text interpreter, 257 00:18:58,758 --> 00:19:02,632 explain what he or she is doing. 258 00:19:03,787 --> 00:19:06,454 So that there’s no misunderstanding 259 00:19:06,641 --> 00:19:11,169 about the role of the speech-to-text interpreter. 260 00:19:11,479 --> 00:19:17,791 But maybe Aida uses for personal settings sometimes the speech-to-text interpreter? 261 00:19:19,334 --> 00:19:20,966 No. No, I don’t. 262 00:19:21,153 --> 00:19:24,579 I use what I can get on my TV, 263 00:19:25,047 --> 00:19:28,951 and I also use it now when I watch YouTube films. 264 00:19:29,260 --> 00:19:32,547 I really appreciate that it is there now. 265 00:19:33,920 --> 00:19:37,782 I’m looking forward every time and really enjoyed when it is there. 266 00:19:38,188 --> 00:19:39,600 About going to a party, 267 00:19:39,720 --> 00:19:44,494 an old friend of mine went to her son’s 50th birthday. 268 00:19:45,053 --> 00:19:46,483 And she was very worried. 269 00:19:47,294 --> 00:19:51,960 She said: “I will try to have a speech-to-text interpreter with me.” 270 00:19:52,080 --> 00:19:55,367 And of course the son said: “Yes, this is a very good idea.” 271 00:19:55,929 --> 00:19:58,900 And it was such a great idea. 272 00:19:59,088 --> 00:20:03,342 Everyone around the table where she sat really enjoyed it, 273 00:20:03,498 --> 00:20:06,000 and they were also having some fun with this. 274 00:20:07,182 --> 00:20:11,192 She wrote me the next day and said when she came home, 275 00:20:11,317 --> 00:20:14,334 that she could not fall asleep because she was so happy. 276 00:20:14,400 --> 00:20:18,947 It was a long time ago that she had “heard” so much 277 00:20:19,103 --> 00:20:22,601 and really have been part of the party. 278 00:20:22,879 --> 00:20:25,861 She was so happy that she had tried it. 279 00:20:26,048 --> 00:20:28,037 This is a good thing, 280 00:20:28,120 --> 00:20:31,379 and I think this is also important that elderly people 281 00:20:32,003 --> 00:20:37,249 actually find out that this is possible and they can do it. 282 00:20:37,623 --> 00:20:39,516 But I have another thing, 283 00:20:39,560 --> 00:20:43,701 because with the European Federation of Hard of Hearing I have travelled a lot. 284 00:20:44,159 --> 00:20:46,633 At the gate when they call people out 285 00:20:46,758 --> 00:20:50,878 and say which [one] in the plane should come up first. 286 00:20:51,003 --> 00:20:54,893 Then I always walk up and then it’s not me. 287 00:20:55,954 --> 00:20:59,390 They have so many big screens and it takes nothing. 288 00:20:59,546 --> 00:21:02,701 I mean, they can pre-type these sentences 289 00:21:02,857 --> 00:21:06,761 and show it on a screen and then just add the numbers. 290 00:21:08,037 --> 00:21:12,000 There is a huge thing in transport, I think. 291 00:21:13,122 --> 00:21:16,512 Airports, trains, buses, whatever, 292 00:21:16,886 --> 00:21:22,319 where we can also have good use of speech-to-text. 293 00:21:23,724 --> 00:21:28,006 Piero, I’d like to say something more about work settings. 294 00:21:28,692 --> 00:21:34,230 It’s good to know that I have only one speech-to-text interpreter with me. 295 00:21:34,636 --> 00:21:37,753 Is the meeting for 2 hours? It’s also one. 296 00:21:37,910 --> 00:21:41,779 But if the meeting [lasts] 6 hours, I have also one. 297 00:21:42,000 --> 00:21:44,920 For a very limited time, [I have] 2 with me. 298 00:21:45,199 --> 00:21:48,144 So that means that at the coffee break, 299 00:21:48,362 --> 00:21:50,110 or at the lunch break, 300 00:21:50,362 --> 00:21:55,940 also the interpreter has coffee break and lunch break. 301 00:21:57,156 --> 00:22:00,855 That is fine, but on the other hand not fine. 302 00:22:00,980 --> 00:22:06,142 Because in the coffee break there is a lot of background sounds. 303 00:22:06,673 --> 00:22:09,907 Then sometimes it is very difficult for me 304 00:22:10,344 --> 00:22:13,311 to participate [in this] part of the meeting. 305 00:22:13,652 --> 00:22:16,622 Because then the lunch time 306 00:22:16,902 --> 00:22:20,180 without the support of the speech-to-text interpreter 307 00:22:20,554 --> 00:22:24,132 costs me more energy than the whole meeting, 308 00:22:26,162 --> 00:22:34,275 because I need to concentrate so much to listen, to look. 309 00:22:34,742 --> 00:22:41,266 Because the hearing aids are not able to reduce 310 00:22:41,640 --> 00:22:43,640 all the background noises. 311 00:22:43,950 --> 00:22:49,871 Some hearing aids programs are able to focus on the other speakers, 312 00:22:50,245 --> 00:22:56,226 and haven't the possibility to reduce the background noises. 313 00:22:57,880 --> 00:23:00,207 There is a limitation in that. 314 00:23:01,393 --> 00:23:07,027 Sometimes in the [advertisement] of a new hearing aid, 315 00:23:07,401 --> 00:23:10,556 they present them as wonderful, 316 00:23:10,710 --> 00:23:16,120 so that you can hear effectively also in noisy room. 317 00:23:16,276 --> 00:23:17,868 Maybe sometimes. 318 00:23:18,149 --> 00:23:23,020 But in most of the times is an hard work for the hearing aids, 319 00:23:23,080 --> 00:23:25,344 but also for the hard of hearing person. 320 00:23:26,218 --> 00:23:29,463 But the problem is also that the background noise 321 00:23:29,682 --> 00:23:32,788 at coffee breaks will be other people talking. 322 00:23:33,100 --> 00:23:34,997 And other people's voices. 323 00:23:35,185 --> 00:23:42,676 And speech sounds is the same frequencies that we are using. 324 00:23:42,894 --> 00:23:49,472 Then some will maybe recommend you to use your smartphone 325 00:23:49,659 --> 00:23:53,440 and some app that could translate 326 00:23:53,770 --> 00:23:56,016 or write what people are saying. 327 00:23:56,328 --> 00:24:01,413 But that microphone is just as vulnerable as the microphones in your hearing aids. 328 00:24:02,942 --> 00:24:09,216 Sometimes we escape to the back kitchen or something to have quiet around us 329 00:24:09,341 --> 00:24:11,142 and be able to talk. 330 00:24:13,015 --> 00:24:19,224 So, in conclusion: more speech-to-text interpreters for every situation. 331 00:24:19,879 --> 00:24:21,752 -Yes. -That’s the key. 332 00:24:22,969 --> 00:24:25,019 Yeah, that is the key. 333 00:24:25,861 --> 00:24:30,560 That there is a good access to speech-to-text interpreters 334 00:24:30,640 --> 00:24:32,468 so that we are then enough. 335 00:24:33,933 --> 00:24:35,385 But it’s also important 336 00:24:35,440 --> 00:24:40,849 that the speech-to-text interpreters are educated very well 337 00:24:41,721 --> 00:24:43,591 in the technical stuff. 338 00:24:43,840 --> 00:24:48,440 Some speech-to-text interpreters use the Velotype, or the steno machine, 339 00:24:48,560 --> 00:24:52,178 or type in a keyboard. 340 00:24:55,203 --> 00:24:59,600 Then is good that the speech-to-text interpreters have 341 00:24:59,720 --> 00:25:05,259 also the knowledge about the technique. 342 00:25:05,570 --> 00:25:10,927 But sometimes the machine or the keyboard is broken, 343 00:25:12,768 --> 00:25:15,923 or there is no good Internet connection. 344 00:25:17,574 --> 00:25:21,909 Sometimes there are some technical difficulties. 345 00:25:23,656 --> 00:25:28,953 Hopefully in the future Automatic Speech Recognition will be better. 346 00:25:29,546 --> 00:25:37,278 Yeah, maybe. But it is also important to train the Automatic Speech Recognition. 347 00:25:37,528 --> 00:25:41,629 Thank you, Aida and Marcel for joining. 348 00:25:42,347 --> 00:25:47,290 Thank you very much for all your interesting points of view. 349 00:25:48,015 --> 00:25:56,105 [LTA music] 350 00:25:58,523 --> 00:26:00,941 LTA. LiveTextAccess. 351 00:26:01,721 --> 00:26:04,220 Universitat Autònoma de Barcelona. 352 00:26:05,250 --> 00:26:08,436 SDI - Internationale Hochschule. 353 00:26:09,466 --> 00:26:12,964 Scuola Superiore per Mediatori Linguistici. 354 00:26:14,181 --> 00:26:15,900 ZDFDigital. 355 00:26:17,055 --> 00:26:20,241 The European Federation of Hard of Hearing People - EFHOH. 356 00:26:21,333 --> 00:26:22,423 VELOTYPE. 357 00:26:23,359 --> 00:26:24,704 SUB-TI ACCESS. 358 00:26:25,796 --> 00:26:30,761 European Certification and Qualification Association - ECQA. 359 00:26:34,163 --> 00:26:37,911 Co-funded by the Erasmus+ Programme of the European Union. 360 00:26:40,064 --> 00:26:41,565 Erasmus+ Project: 361 00:26:42,314 --> 00:26:53,989 2018-1-DE01-KA203-004218. 362 00:26:55,300 --> 00:26:58,835 The information and views set on this presentation 363 00:26:59,053 --> 00:27:00,897 are those of the authors 364 00:27:01,053 --> 00:27:04,707 and do not necessarily reflect the official opinion 365 00:27:04,863 --> 00:27:06,145 of the European Union. 366 00:27:07,299 --> 00:27:11,044 Neither the European Union institutions and bodies 367 00:27:11,637 --> 00:27:14,199 nor any person acting on their behalf 368 00:27:14,823 --> 00:27:17,541 may be held responsible for the use 369 00:27:17,791 --> 00:27:21,164 which may be made of the information contained here.