Microsoft Azure Speech-to-Text API Alternative

Azure making you blue?

Move to Deepgram, where creating great speech-to-text is our primary business. Find out how easy it is to switch.

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deepgram vs microsoft azure stt

COMPARE CAPABILITIES

All the features. Better performance. Lower cost.

Features and Capabilities
Deepgram
Microsoft Azure STT
Batch processing (1hr of audio)
20 seconds
1443 seconds
Streaming processing lag
<300 ms
N/A
Deep Search (audio)
Diarization (separate per speaker)
Up to 10
Up to 2
Audio streams
Unlimited
100
Tailored Speech Model
separate acoustic and language model training
Noise Reduction
Custom Vocabulary (keyword boosting)
Redaction
Punctuation
Profanity Filter
Numeral Formatting
Language Detection

Faster Transcriptions

Stop settling for less data because transcriptions are too slow.

With our End-to-End Deep Learning Neural Network, you can transcribe 1000 hours of audio in 8 hours — or you can spend 400 hours transcribing with Azure. And with Deepgram, you never need to sacrifice accuracy for speed.

Higher Accuracy

Higher accuracy than Azure out of the box.

Our real-world tests with customers show that our base models beat azure out of the box, but for us, that’s only the beginning. Deepgram lets you customize a model to recognize your unique branded terms, industry lingo, and audio environment — giving you 90%+ accuracy within weeks.

Lower Cost

Built for lower TCO

One of the many advantages of an End-to-End Deep Learning Neural Network is not being stuck with slow, resource-hungry legacy speech models. Instead of single streaming on CPUs, we can multi-stream on GPUs. Simply put: we’re built to be cheaper so you can go big.

sitting on stacks of money

Switching to Deepgram is easy.

Fast and Easy to Implement

APIs, SDKs, and docs, Yes!

Implementing Deepgram is fast and easy with our APIs, SDKs, detailed guides, and clear documentation.  Our customers rank us excellent in implementation and support.  Go ahead. Take it for a spin and get $150 in credits.

Meet innovators who’ve made the switch.

With Deepgram’s accurate and fast speech-to-text solution, We’re the Google Analytics of podcasts.”

Matt Drengler, Director of Partnerships, Podsights

Deepgram engines have outperformed any of the others that we have tried or looked into. Our accuracy levels are greater than 90% on virtually everything that we do.”

Dennis Evanson, Head of Compliance and Quality Assurance, Randall-Reilly

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