Why Automated Subtitles Can Never Beat Human Subtitles
Subtitling has been helping us communicate with each other, present our unique ideas, open doors to unfamiliar cultures around the world, be on top of global news, and promote diversity (professionally and personally). Today, if a brand puts out a video on its social platforms, a considerable section of its audience depends on the subtitles to understand their message. So, what happens when there are errors in their subtitles?
While #SubtitleFails has helped all of us accept and laugh at the errors in our subtitles, it raises an important question – how much are we willing to invest in subtitling our visual content?
The art of subtitling has found great utility and a special place in the global marketplace today. Filmmakers use subtitles to increase their reach among the foreign audience – a great example being this year’s Oscar winner Parasite, a Korean movie.
Video content creators, on platforms like YouTube, add subtitles to reach their foreign fans and increase their local search rankings. Trainers and training companies use subtitles in their videos to help them train their foreign clients’ teams. Global brands use subtitles for all the videos that are part of their hiring, onboarding, induction, training, liaising, legal, business, and marketing processes.
Whether one should utilize a machine or a human for subtitling their content, is a matter of debate. Machine or automated subtitles are quick and require less monetary investment. On the other hand, utilizing human subtitling experts might need some more time and monetary investment on your part. But what about the quality of subtitles? In this article, I will discuss why choosing human subtitling experts or a human subtitling company, will pay off. Also, I’ve got some great examples of videos, movies, shows, and more where human subtitling saved the day!
To subtitle or not to subtitle.
Sometimes choosing not to subtitles specific segments of a movie, show or a video can have a significant impact. The other day I was watching a Netflix Original show Emily in Paris, where the protagonist Emily bags her dream job as a marketing executive for a famous brand in France. Since she cannot speak French, there are many instances where her colleagues say something in French, and she doesn’t understand them.
If you watch it with subtitles, you’ll realize that there are no subtitles for when Emily’s colleagues talk to her in French. Now, why is that? The creators of the show wanted the viewers to feel the same confusion that Emily felt when she failed to understand French. A machine would have been unable to make this distinction and would have created subtitles for all languages. Netflix’s subtitling experts understood the context of the show and created subtitles that had the desired effect on viewers – one which the show’s creators were aiming for.
Subtitling movies, shows, and other video content that has characters speaking multiple languages is a huge challenge. When there is more than one language involved, machine or automated translation becomes difficult. Your team must identify different language blocks and put them through the correct translation systems to get subtitles. Add to this the fact that the machine will fail to understand the context. So, you can expect some errors in translation.
On the other hand, subtitling experts will ensure that they understand the context and translate the dialogues to match it. For instance, the Hindi movie Chennai Express has characters talking in both Hindi and Tamil. Since it was a romantic-comedy movie, the experts used subtitles to convey the humor to English-speaking viewers.
Getting the cultural nuances right
Subtitling isn’t just about translating the dialogues and adding them to the final version. It is a process that demands a lot of involvement on the part of the subtitling experts. They must put themselves in the target viewers’ shoes and create subtitles that’ll make sense to them. For instance, if a character in an American show uses the word ‘cookie’, machine translation will identify that word and keep it in the UK subtitles. However, an expert will know that a ‘cookie’ in the UK is called a ‘biscuit.’
Similarly, if an Indian character says ‘as high as the Himalayas’, the expert might translate it to ‘as high as the Eiffel Tower’ for the French audience. These little details add a lot to the viewing experience.
Literally? No thanks.
Every language and culture has many phrases that we’ve come to use to express certain emotions or ideas. In the USA, ‘you bet’ is a way of saying ‘definitely’ or ‘sure.’ Similarly, ‘beats me’ can be used to say ‘I don’t know’ or ‘I don’t understand.’ Machines cannot understand the context and hence, end up translating the dialogues literally.
When the American movie Avengers: Infinity War released in Korea, all Avenger fans waited patiently to catch their favourite movie. However, they were so disappointed with the quality of the subtitles that they started a petition. Apart from the literal translation of swear words used by the movie’s characters, Doctor Strange’s popular ‘end game’ dialogue was translated into Korean as ‘we’re doomed.’
Machine or automated subtitles miss out on a lot of technicalities that are essential to the viewing experience. For instance, many compound words are absent in machine translation systems. Compound words can either be hyphenated (like mother-in-law), open (like ice cream) or closed (like volleyball).
Similarly, machine systems translate every word from the source language – even when they are unnecessary. Human subtitling experts, on the other hand, identify the unnecessary, repeated words and don’t translate them to maintain the optimal length of the subtitles.
The impact your movie, show, or video has on a foreign audience depends mostly on the quality of subtitles. They are an essential component of the viewing experience, and that’s why popular brands, OTT platforms (like Netflix, Disney + Hotstar, Amazon Prime Video), etc. trust human subtitling services or experts to translate visual content into the viewer’s context.