Aiding businesses in transcribing spoken words to text.

Generated by ChatGPT

Deepgram’s Automatic Speech Recognition (ASR) is an AI-based tool that helps businesses of all sizes quickly and accurately transcribe voice data into text.

The tool is designed to be used at scale, meaning that it can efficiently handle large volumes of audio data with speed and accuracy. Deepgram’s ASR is powered by deep learning models that are trained on large amounts of audio data.

This technology allows the tool to accurately recognize spoken words in any language and in any environment, including noisy and low-quality audio. Deepgram’s ASR also uses a variety of techniques, such as dynamic time-warping, to improve accuracy and reduce transcription errors.

Additionally, the tool can be customized to suit the needs of individual businesses, enabling them to quickly and accurately transcribe audio data into text with minimal effort.

Deepgram was manually vetted by our editorial team and was first featured on February 14th 2023.
Featured banner
Promote this AI Claim this AI

Would you recommend Deepgram?

Help other people by letting them know if this AI was useful.

Tammy Ying
· Sep 4, 2023
Accuracy really poor - much better off using Speechmatics or AssemblyAI

19 alternatives to Deepgram for Audio transcription

Pros and Cons


Transcribes large volume of data
High-speed transcription
Precise transcription
Transcribes any language
Handles low-quality audio
Dynamic time-warping technique
Customizable for businesses
Economical transcription
Helps build voice applications
Deep learning model
Trained on large datasets
Minimal effort required


Limited to voice transcriptions
Might struggle with accents
Potential transcription errors
Requires customization for accuracy
Not suited for low-quality audio
Limited language recognition
Highly data dependent
May struggle with noise interference


What is Deepgram's Automatic Speech Recognition (ASR)?
How does Deepgram's ASR work?
What is meant by 'at scale' in context of Deepgram's ASR?
What makes Deepgram's ASR efficient?
What technology is used in Deepgram's ASR?
Can Deepgram's ASR recognize any language?
What techniques does Deepgram's ASR use to improve accuracy?
Is it possible to customize Deepgram's ASR?
How does Deepgram's ASR handle noisy and low-quality audio?
How does Deepgram's ASR aid businesses?
What is dynamic time-warping in context of Deepgram's ASR?
How accurate is Deepgram's ASR?
What is the limit on the volume of audio data Deepgram's ASR can handle?
Can individual businesses mold Deepgram's ASR according to their needs?
What is meant by 'voice data'?
How does Deepgram's ASR reduce transcription errors?
How does Deepgram's ASR convert voice data into text?
How quick can Deepgram's ASR transcribe audio data?
Does deep learning models improve the performance of Deepgram's ASR?
What is the rate of economical transcription at scale with Deepgram's ASR?

If you liked Deepgram


+ D bookmark this site for future reference
+ ↑/↓ go to top/bottom
+ ←/→ sort chronologically/alphabetically
↑↓←→ navigation
Enter open selected entry in new tab
⇧ + Enter open selected entry in new tab
⇧ + ↑/↓ expand/collapse list
/ focus search
Esc remove focus from search
A-Z go to letter (when A-Z sorting is enabled)
+ submit an entry
? toggle help menu
0 AIs selected
Clear selection