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Netflix’s idea for Automated Subtitle Translation Related: What is NAT (Network Address Translation) in WebRTC and How Does It Work?īut, how are you going to teach your AI/ML model this nuance? Transcribing the text is one thing, but, translating it considering cultural differences, usage of speech is a completely different ball game and I am glad that big research teams like the ones at Netflix are taking a stab at it. The Cambridge dictionary defines it as follows Is he telling the other person to go beat/hit something? NO! He’s telling the other person to go away or go do something else. What does this seemingly innocent four-word sentence mean? Suppose a character says to another – “Hey you – beat it!” What can go wrong with Machine Translation? Machine Translation is also a huge research topic and is really hard and we’ll see why. You could have an awesome algorithm that can transcribe speech really well and then a person comes along with a speech impairment like a lisp and it can confuse the algorithm. The first (transcribing) has challenges in understanding the way different people speak the same language.

translation (from English to Spanish or Hindi)īoth present huge technical challenges.

English words being spoken into English text to be printed on the screen) The main thing that you need to consider is that there are two main jobs that need to be accomplished for automated subtitling But, accents and dialects will play a massive role when it comes to training and testing such ML models. I purposely did not say “language”, because I feel it is better to have a different model per language.

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You need to have your software trained extremely well to distinguish accents and dialects. I see a similar problem when it comes to automated subtitling.

Their sample set was completely biased because of their accents + pronunciations, and as a result, it failed in real-world testing. Get this – for some odd reason, the R&D group had used their own voice samples to train the model and had overlooked a simple fact – the entire team was made of researchers from China who had come over to the US to study and work. The team could not understand what went wrong, until they realized the obvious. When they took used model for live testing on their actual customers, it performed horribly. The professor was explaining how a research group at a certain mobile giant (struggling badly now) built ML models using several thousands of hours of speech. When I read about Netflix using AI for creating subtitles, it reminded me of a class I took on Pattern Recognition while I was in grad school.

Is Netflix the only ones in the Automated Subtitling game?.

Netflix’s idea for Automated Subtitle Translation.

What can go wrong with Machine Translation?.

What’s involved in Automated Subtitling?.

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