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BlogArchive

An archive of our blog content on AI & technology as well as practical ideas and tips on how AI can help with localization and distribution. 

Papercup Blog Archive

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To train evermore sophisticated speech models, quality data is crucial. Here's how, at Papercup, we embrace this challenge head on 

Here's how we handle large-scale speech data 

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What is a large language model? Like autocomplete on steroids. Product manager Daniel Lawrie explains LLMs revolutionary capabilities. 

Large language models: revolutionizing AI dubbing and beyond

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Curious about how we create kids' voices using artificial intelligence? Find out how our technology handles the challenge. 

Breaking new ground: AI voices and AI dubbing for kid’s content

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Discover how Papercup uses and acquires data in the world of generative AI. Learn about our data practices and why data is crucial for AI dubbing.

How data is used in AI dubbing...

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Will AI replace voice actors? No. The voice acting industry is more likely to harness it to augment its existing role rather than automate it away.

Will AI replace voice actors?

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Automating translation of emotion across languages: a closer look under the hood

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Compare AI dubbing and traditional dubbing to find the best voiceover solution for your content and create global hits.

AI dubbing vs. traditional dubbing: when to use different localization methods

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What are AI voices? Here's how they're made, who uses them for what, and how Papercup's sound so lifelike.

What are AI voices and how do they work?

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There's a lot of buzz around voice cloning, what does it actually mean? Here’s how voice clones are created and when they should be used.

Decoding voice cloning for AI dubbing: the most common questions answered

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Creating realistic computer-generated voices is the ultimate goal of speech technology. Here's what researchers must tackle to achieve C-3PO level synthetic speech.

Teaching computers to speak: the prosody problem

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A lookback at 2023 – the year generative AI exploded, major shifts in the digital and streaming worlds, and some key Papercup milestones. 

2023 – a look back at a year of generative AI, digital and streaming media 

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Good dubbing is accurate, conveys lifelike emotion and be easily understood by its audience. Bad dubbing? The exact opposite. 

Crafting AI voices that exceed audience expectations 

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Find our how generative AI can be a force for good in the media and entertainment industry by augmenting creative capabilities, rather than eclipsing them.

CGI and VFX transformed media; now generative AI is doing the same

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What is a large language model? Training data? What's a human-in-the-loop? Answers to all of the above in this glossary of key AI terms.

Generative AI – a must-have speech technology glossary

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How to utillize machine learning capabilities to develop valuable products with real-world use cases. 

Building machine learning products: lessons from Papercup's product team

The ongoing translator shortage is lengthening timelines and production costs, and traditional studio dubbing can't localize content at scale.

Why now is the time to adopt AI dubbing

Since its launch in 2021, Meta has positioned itself as a new pioneer for the digital age. Zuckerberg’s recent announcement that Meta is working on speech-to-speech AI translation is an exciting development. However, it's best to be realistic about what can be achieved and grounded about timelines. Here, we take a look at current possibilities in the world of technology-based translation - including what works well, what’s still forthcoming, and where care is needed to produce quality results.

Why Meta’s speech-to-speech translation ambitions are far from today’s reality

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Today we’re excited to announce our $20m in Series A financing. This takes our total to date to $30.5m, making us one of the most funded AI dubbing companies globally. 

We've Raised a $20m Series A

Traditional dubbing is highly complex. With the ongoing translator shortage, companies are looking to machine learning to streamline the process.

Translator talent crunch leads to investment in machine learning

AI was used to recreate Anthony Bourdain's voice in Morgan Neville's new documentary "Roadrunner" and the debate on the ethics of it are raging. Here's why...

The ethics of Anthony Bourdain's Deepfake voice

Jesse Shemen, Papercup CEO and co-founder, explains why he founded the company, the problem he was trying to solve and how AI dubbing can help companies improve their ROI and unlock new revenue streams. 

Q&A with Jesse Shemen, Papercup CEO and co-founder on future of synthetic media

Amazon's large-scale, data-driven study finds that human dubbing artists prioritize expressive, natural-sounding language over lip syncing.

Lip sync not a dubbing priority, Amazon study finds

The all-important questions to ask an AI dubbing provider to ensure that your video content is flawlessly translated 

Ask these questions to find the best AI dubbing platform  

Advances in deep fake technology are enabling the creation of hyper-realistic digital effects. It's an area where ethics are still playing catch up.

Fall’s ‘F-bomb’ saga: Can deep-fake AI preserve audience trust?

AI is changing publishing, media, marketing, advertising, movies, and journalism as we know it. Is no creative industry safe anymore? Or can advancement in AI actually benefit the creative industry and work in partnership with humans?

AI and its impact on journalism up to now

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For the uninitiated, the world of AI voice generation can be hard to navigate, so here are 7 of the best speech generation products making waves in the space.

7 of the best AI voice generation platforms

From Netflix’s personalized thumbnails to deepfake Luke Skywalker, AI and machine learning are changing the way the film and television industry operates. While the industry has been slow to embrace this technology, the leading media giants are increasingly embedding AI into their operations, proving that AI and creative ventures can go hand-in-hand. Let’s look at some of the most exciting uses of AI in film and television today:

5 examples of AI disrupting the film and television industry

Few machine learning-centric startups have become as ubiquitous as Zoom, Notion or Slack. If the AI and machine learning industry is to be worth the $15 trillion it’s predicted to be by 2030, we only have another decade left to hit that goal!

Papercup blog archive

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