Automated Speech Recognition and Translation Engines

Since the dawn of media accessibility, the captions you’ve come to know and love have all been expertly crafted by professional captioners. Between a college education in their language of choice and years of additional training and practice, captioners bring experience, knowledge, and passion to their craft every single day. In recent years, however, the media accessibility industry has begun to see machines rising up, with tools like automated speech recognition and translation engines, to take the title of “Best Newcomer.” Let’s break down the differences.

Human Captioning vs. Translation Engines

Recently, the capacity for technological advancements in artificial intelligence and machine learning has risen exponentially. ASR (automated speech recognition) has been a major breakthrough in the live transcription space. ASR transcription utilizes machine learning algorithms to identify spoken word and instantaneously caption them, all automatically. With this technology being relatively new on the scene, there are still a lot of issues with accuracy. Typically, artificial intelligences work better when they have a lot of information to take in at once. Therefore, in order to get an accurate transcription of the audio, an ASR engine takes as much audio to parse and contextualize as possible, which results in the captions populating in large, slow chunks. Additionally, ASR solutions are a long way from matching the accuracy of human transcribers. Although newer engines can adequately parse the audio, their major drawback lies in their ability to understand context, profanity, and phonetics. The trap that most users fall into is not realizing that these ASR solutions require significant work to set up and keep running. ASR itself cannot set up filters, manage connections, and create dictionaries without some human intervention to provide guidance.

Do Robots Dream of Electric Language?

In the space of translation, things get a little more murky. On one hand, nothing can beat the nuance of a trained translator who is fluent in both the parent and destination languages. On the other hand, it can get cumbersome (and tiresome) if you require immediate-yet-imperfect translations, or need your content translated live into multiple languages. That’s where the advantages of translation engines come into play. Gone are the days where content creators would have to line up multiple translator pairs or scour the internet for certified captioners available in a specific language. Translation engines have been progressing rapidly in recent times, and the modern translators are a far cry from the dicey results from Babel Fish®. Nowadays, these solutions are easy to scale and consolidate to a single source-language captioner. Automated translation still misses a lot of nuance, and can still be inaccurate if not given sufficient context, but translation is leaps and bounds ahead of speech recognition in the technological world. Just like with ASR, these systems tend to work better when combined with a human translator in the loop. As these systems tend to work best as text-to-text translators, having a trained captioner on the back-end creating high-quality captions for the machine to work with can greatly improve the end product.

Coexisting in Harmony

This is where Captionmax comes in. Using our trained team of experts, we’re able to harness the scalable, low-cost power of these automated speech recognition and translation engine tools while having human involvement to alleviate the drawbacks and issues with accuracy. By having professionally-trained captioners manage the solutions from behind the curtain, we can deliver high-quality multi-language realtime subtitling and live captioning at a very affordable price. With an expert human behind the wheel of these ASR solutions, the drawbacks of information ingestion, filtering, and systems management become minimized. Even though it may sound like a relatively simple plug-and-play solution, using any sort of translation engine or managed ASR solution requires a lot of work to get it running. It all comes down to the human captioners giving these machines the best possible environments to succeed.

It’s far more productive (and fun!) to think of this technology as another tool in a captioner’s belt, rather than the near-supernova hovering on the horizon. Remember our kindergarten manual? “Things are better when we work together;” this mantra works equally well for both your work team projects and our managed ASR solutions.

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