Deepgram Reviews

I use Deepgram for audio transcriptions and speech recognition. I am working on a feedback survey app where users provide verbal feedback that Deepgram transcribes into text. 

We receive the results and implement features like punctuation and Smart Format.

Deepgram has significantly improved our transcription process in terms of speed and accuracy. It has allowed us to efficiently convert verbal feedback into text, enabling quicker analysis and implementation of new features. 

Integrating Deepgram has streamlined our workflow, enhancing productivity and delivering more accurate transcription results.

We previously used IBM Watson, which was slow and had limitations in accurately transcribing words. After evaluating OpenAI's Whisper model, we discovered Deepgram, which incorporates Whisper and adds the powerful Nova model.

Deepgram's latency is impressively low, around 0.5 to 1 second, making it a superior choice.

Live transcription could be improved. Sometimes, Deepgram's WebSocket is disposed of due to redundancy issues. Enhanced stability in live transcription would be beneficial.

I have been using Deepgram for one and a half years.

Initially, we encountered some stability issues, but Deepgram has since improved its architecture. With the addition of hooks for status updates, the accuracy has improved to approximately 90 to 95%, which is better than other models we've tested.

It's scalable. Our platform handles 50 to 60 users simultaneously without compromising accuracy. For instance, a 20-minute audio file was transcribed within a second, demonstrating its ability to handle large volumes of audio data effectively.

My experience with customer service and support has been positive. They are responsive and helpful, and they provide timely resolutions to any issues.

We previously used IBM Watson, but it didn't deliver appropriate results. We searched for alternatives and found OpenAI's Whisper model, which was initially slow. After thorough analysis, we discovered Deepgram. It proved to be superior, leading to our decision to migrate. We used a detailed spreadsheet to compare various models before making the switch.

Thanks to clear documentation, the initial setup was very easy. If you have prerequisite knowledge of the programming language you're using, it’s straightforward to follow the documentation and implement it into your system. When I started, I closely followed the documentation, which made the process very manageable.

Deployment model: We last deployed it on the Google Cloud Platform (GCP).

The implementation was done in-house.

Our ROI has increased due to enhanced transcription accuracy and speed, leading to more efficient workflows and better user satisfaction.

The pricing is moderate. While live transcription may incur some charges when the connection is open, they become minimal over time. So, it's a balanced option—neither cheap nor overly expensive.

Yes, besides IBM Watson, we evaluated OpenAI's Whisper model.

Deepgram is highly recommended. Users don’t need to do anything special before using it, as the documentation is comprehensive. I am a Node.js developer and have used Deepgram packages for Node.js. Understanding your programming language is key, whether it's Node.js, Python, or others.

AI Features:

I have integrated various AI models into our application. Deepgram's sentiment analysis feature allows us to create graphs and analyses to determine if words are positive, negative, or neutral. This helps us summarize feedback and derive actionable insights.

My ratings:

I would rate it an eight out of ten. The live transcription feature needs improvement as the WebSocket sometimes gives errors or breaks down during live streams.

I run Deepgram on my local system to transcribe videos.

The speed of the solution for transcribing videos is good.

I need to transcribe my videos to text chat, but there are some issues when I run Deepgram. The solution does not properly identify the number of speakers. For example, Deepgram only identifies two speakers out of three or four speakers in some videos.

The solution also makes some spelling and English grammar mistakes. Deepgram does not properly identify some specific words in a sentence.

I have been using Deepgram for one to two months.

We haven't faced any breakdowns or bugs with the solution.

My team consists of two members who use Deepgram.

The solution’s technical support is average. I talked to the technical support team regarding an issue where the solution couldn't identify the exact number of speakers. The support team asked me to use certain parameters, but the results were inaccurate. I used all the parameters suggested by the support team, but the speakers were still not identified clearly. However, other services could properly identify the speakers of the videos.

The solution’s pricing is cheap.

I chose to use Deepgram after researching it on Google and finding some good feedback that the solution had good APIs. It's easy for a new user to learn to use the solution.

I would not recommend Deepgram to other users because it does not properly identify video communication. If you compare it with the other APIs, you can easily find that they do not properly identify some words, exclamatory signs, full stops, etc. These are small mistakes the tool is not properly identifying. Also, the solution does not properly identify the speakers. Users should check other APIs before choosing Deepgram.

Overall, I rate the solution a six out of ten.

We use the solution for TTS (Text-to-Speech) and STT (Speech-to-Text) purposes.

The solution's Speech-to-Text conversion feature is really awesome.

Deepgram is currently restricted to only the English variants, but it should include other languages, such as German or French.

I have been using Deepgram for five to six months.

Deepgram is a stable solution.

The Deepgram cloud can handle large volumes of audio data. Around three to four people use the solution in our organization.

The solution’s initial setup is easy.

Deepgram is a cheap solution. We can create an account for $200, which we can initially use for the Deepgram services.

I have used Deepgram with Twilio for the calling system. I would recommend Deepgram to users who want to use it for speech-to-text purposes.

Overall, I rate the solution an eight out of ten.