The Stripe of Automatic Speech Recognition (ASR)

What is AssemblyAI?

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AI-as-a-Service in an audio friendly world - powering Automatic Speech Recognition (ASR)

Can I just say, I really like this startup? But there are so many A.I. startups now where I feel that way. This article first appear on my Artificial Intelligence Survey.

JULY 14TH, 2022 4:15 PM MONTREAL, CANADA

The speech to text AI startups, AssmeblyAI has now raised $64 million, according to Crunchbase.

AssemblyAI today announced that it raised $30 million in a Series B round led by Insight Partners with participation from Y Combinator and Accel. To date, AssemblyAI has raised $64 million, which founder and CEO?Dylan Fox?tells TechCrunch is being invested in growing the company’s research and engineering teams and data center capacity AI model training.

On LinkedIn, Dylan says he talks about t #ai, #startups, #deeplearning, #speechtotext, and #speechrecognition - that sounds about right.

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Origin Story

Fox founded AssemblyAI after a 2-year stint at Cisco, where he worked on machine learning for collaboration products. Prior to that, he started YouGive1, an organization that worked with companies to reward customers with product offers in exchange for nonprofit donations.

Here is?all they achieved in 2021.

AssembyAI has a great future with audio.

AssemblyAI is all about leveraging the same AI technology used to create popular AI models like?DALL-E 2, GPT-3, and?Google’s LaMDA model, to create State-of-the-Art AI models for transcribing, understanding, and analyzing audio and video data – including?Transformers,?Large Language Models, massive?GPU clusters, and large datasets.

First-of-their kind audio-first social networks, like Twitter Spaces and Clubhouse, have started popping up everywhere, including Substack’s App and?LinkedIn Audio Events.?There’s an API for that.

Smaller companies struggle to keep up, which is why many turn to “AI-as-a-service” vendors that handle the challenging work of creating models and charge for access to them through an API. One such vendor is?AssemblyAI, which focuses specifically on speech-to-text and text analysis services.

Automatically convert audio and video files and live audio streams to text with AssemblyAI's Speech-to-Text APIs. Do more with Audio Intelligence - summarization, content moderation, topic detection, and more. Powered by cutting-edge AI models.

The Stripe for Text to Speech

Four months ago, they announced our?$28M Series A led by Accel, with participation from Y Combinator, the Stripe founders – John and Patrick Collison, Nat Friedman, and Daniel Gross.

Now there’s yet another round. They are moving fast.

Democratizing Text to Speech

Their goal is to expose this progress to every developer and product team on the internet – via a simple set of APIs. As we continue to research and train State-of-the-Art AI models for ASR and NLP tasks (like speech recognition, summarization, language identification, and many other tasks), we will continue to expose these AI models to developers and product teams via simple APIs – available for free.

Over the past 6 months just in 2022 they’ve already launched ASR support for?15 new languages?– including Spanish, German, French, Italian, Hindi, and Japanese, released major improvements to our?Auto Chapters and Summarization models, Real-Time ASR models, Content Moderation models, and?countless other product updates.

They were founded in 2017.

“I was looking for speech recognition and natural language processing (NLP) APIs for past projects, and started AssemblyAI after seeing how limited, and low-accuracy, the available options were back in 2017,” Fox told TechCrunch in an email interview. “The company’s goal is to research and deploy cutting-edge AI models for NLP and speech recognition, and expose those models to developers in very simple software development kits and APIs that are free and easy to integrate.” - Dylan Fox

ASR stands for automatic speed recognition.

I consider AssemblyAI a rather promising AI startup.

With this new funding, they will be able to accelerate their product roadmap, build out better AI infrastructure to accelerate our AI research and inference engines, and grow our AI research team – which today include researchers from DeepMind, Google Brain, Meta AI, BMW, and Cisco.

The API for ASR

AssemblyAI has the go-to solution for analyzing speech, offering ultra-simple API access for transcribing, summarizing and otherwise figuring out what’s going on in thousands of audio streams at a time.

Their value proposition to me is really strong. Think about it, AssemblyAI offers AI-powered, API-based services in over 80 languages for automatic transcription, topic detection, and content moderation as well as “auto chapters,” which breaks down audio and video files into “chapters” with summaries for each. Using the platform, developers can call various APIs to perform tasks like “identify the speakers in this conversation” or “check this podcast for prohibited content” at a relatively low cost, starting at $0.00025 per audio-second.?

• Automatic transcription
• Topic detection
• Content moderation
• Auto Chapters
• Speaker identification
• Super cheap: $0.00025 per audio-second. That’s $.90 for 1 hour.

Super Minimalistic APIs

AssemblyAI offers a handful of different APIs that you can call extremely simply (a line or two of code) to perform tasks like “check this podcast for prohibited content,” or “identify the speakers in this conversation,” or “summarize this meeting into less than 100 words.”

So Many Use Cases

But Fox says AssemblyAI continues to grow at a fast clip, fueled by the pandemic, and — by extension — the rise of remote work. Audio and video is being incorporated into an expanding number of products, he notes, like videoconferencing and even?dating apps. That’s led product teams to look for ways to build additive, high-value features on top of audio and video data.

Thanks for reading!

I have a special summer discount going for my AI Supremacy Newsletter, help me get to 100 paid subscribers.

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What do you think of their unique value proposition, product market fit and future potential?

Respond in a comment below.