Jeff Kofman, is the Founder & CEO of Trint, after a 30-year profession with ABC, CBS and CBC News, Jeff got bored with hitting the wall of manual transcription and watching every story unnecessarily stop in its tracks. In 2014, Jeff and a team of developers leveraged AI to do the heavy lifting, and Trint was born.

Today Trint is an AI-powered SaaS platform that goes beyond transcription to spice up every stage of the content creation workflow.

From transcription to editorial tools, real time collaboration to export and publishing – making every step easier for newsrooms, podcasters, local businesses and global organizations to share stories faster and easier than ever.

You had a distinguished 30-year profession with ABC, CBS and CBC News, what were a number of the issues that you simply encountered with traditional manual transcription?

I lived the pain of manual transcription every single day as a journalist. Long before I had the concept of inventing and constructing Trint, I wondered why there wasn’t a greater way.

Manual transcription was all the time the bottleneck in my workflow as a TV reporter. I’d do my interviews, take heed to a news conference, read my research, have a look at my footage and THEN… my producer and I’d disappear into the Black Hole of Transcription.

I can’t write my TV news story until I even have precise transcripts of the quotes or soundbites I would like to make use of. I want to know what they said and the way long that soundbite runs. That meant sitting in a screening room or at our desks with headphones on, hitting PLAY then PAUSE. Then type some words. Then PLAY. PAUSE. And repeat. It could take hours. So tedious. So essential.

Trint launched in 2014, are you able to discuss how the concept was born?

I never imagined I’d be a tech guy. It was never in my life plan. It happened by probability.

I had an off-the-cuff conversation with some software developers who had done some rudimentary experiments with audio and text (not transcription) in 2013.

I innocently asked: why can’t I take advantage of automated speech-to-text to transcribe my interviews.

I remember one among the blokes asking me: why would you ought to try this?

I answered: because manual transcription is the pain point in my work as a reporter, I detest it.

We kept in contact and did some experiments. It quickly became clear that we had invented the long run. I left my job as London Correspondent for ABC News a yr later and we began constructing Trint.

What were a number of the challenges of launching a transcription service in those early days?

Automated transcription is a discrete problem. Individuals who don’t live the workflow of reporters and content creators do not know how they create stories. I remember meeting some very wealthy angel investors within the early days they usually just couldn’t grasp why reporters like me need transcripts. It took plenty of explaining to get them to know how a reporter works.

I feel that’s easier today. We’re all content creators.

What are the several machine learning algorithms which can be currently used at Trint?

We now have an excellent smart bunch of engineers and data scientists which can be all the time tinkering with whatever they may be hands on with and wherever their imaginations can take them. As you’ll understand, our focus is on how automated transcription can speed up workflows for our media customers, which suggests we all the time work around speech, speakers, languages and acoustics. NLP and speech processing algorithms are a part of our day-to-day, but we are going to investigate any creative ways to make use of AI to assist journalists extract information from videos, audios and pictures. Wealthy transcription lets us give more context to their content, makes all of it more searchable, and ultimately lets them find the moments that actually matter and get them out to their audiences as quickly as possible.

What languages are currently offered, and are there any differences in transcription quality between the several languages?

We provide about 45 languages which you can transcribe and are all the time adding more. Some are in “beta” and others which can be loads more mature, which depends upon the scale of coaching data sets that help construct the models. We continuously measure the accuracy of our models for every language to continuously develop our models and to enhance their performance.

We’re all the time what recent models have gotten available to see if we will bring them into our secure ASR processing environment.

But it surely’s not only concerning the languages we transcribe – our customers can even have that transcript translated into almost any language.

Outside of transcription, Trint is an AI-powered SaaS platform that’s designed to enhance content creation workflow, are you able to discuss a number of the other tools which can be offered?

Although at the guts of Trint is our AI-powered transcription, what we obsess about is why those transcriptions are useful to our users, and the way we may help them get value as quickly and simply as possible. Which means having a deep understanding of their workflows, so we will try to make every step as seamless as possible.

Ultimately, we would like them to capture any press conference, interview or event anywhere, at any time, in any language and make use of it because it happens. Which means making it easy for them or their team to confirm and use the live transcription because it happens – verifying, sharing and translating key quotes seconds after they’re spoken.

Our mobile app implies that can occur even if you happen to only have a phone on you, and ensures the whole lot is securely transmitted to your team even when the connection is patchy.

Our Story Builder is designed to let you discover the important thing moments in all of your content and switch them right into a recent narrative that may be exported to other key tools in your content production workflow. Whether that’s a rough cut for video editing, a podcast transcript or an article. If it’s essential use the text of the audio as captions, our collaborative editor may help there too.

You furthermore may have a podcast that you simply personally host called StoryTech, which looks at how technology shapes stories. Could you elaborate on what this podcast is, what listeners should expect, and why they need to tune in?

StoryTech is absolutely the intersection of my two careers: a reporter and a tech inventor. It looks at how technology and innovation shape the way in which stories are told.

The early episodes have a look at how CGI was used to bring down the ice wall in Game of Thrones, and the way the invention of the 35mm Leica camera within the Nineteen Twenties led to the spread of photojournalism and the creation of LIFE magazine.

I’m fascinated by the impact of innovation on storytelling. That’s what StoryTech is about.

What’s your vision for the long run of Trint?

That’s the challenge every innovator is wrestling with today. How does the fast pace of innovation open opportunities for my product?

Our customers desire a product that creates easy, intuitive efficiencies that fit seamlessly into their workflow. Which means going far beyond transcription.

Trint will leverage AI to do things that were unimaginable just a number of years ago: discover voices, faces, sentiment, context, facts and falsehoods. It will occur in any language – translating from that language because it’s spoken. The secret is to do that and so rather more in a way that integrates into other products to create one painless workflow.

I don’t see Trint replacing reporters, writers and content creators. It’s about liberating them from the drudgery of their work and allowing them to focus their time on creativity. It’s exciting to try to assume the long run. I’m not gonna lie: it’s also daunting.