AssemblyAI - Speech to Text API Reviews & Product Details

I work as a Dietician and Nutritionist, manage a homeopathy clinic, create health education content for social media, and also prepare educational and awareness material. What I like best about AssemblyAI is that it helps convert spoken content into text in a simple and organized way. It reduces the time spent manually reviewing recordings and makes it easier to work with audio content in a written format. The generated transcripts are usually easy to review, edit, and use further for different types of content. I have used it when working with health education recordings, informational audio content, and other spoken material that needs to be reviewed in written form.

One thing I find useful is that it supports both streaming and pre-recorded audio transcription. This gives flexibility depending on the type of content being processed. The transcription quality has been good during my use, and the generated text is usually easy to review and work with. Features such as speech to text, language detection, transcript generation, and audio processing help reduce the time that would otherwise be spent manually typing or reviewing recordings.

Another useful part is that the generated transcript can be reviewed, edited, and used further for educational articles, awareness content, notes, and other written material. This is helpful when working on health topics that need to be converted from audio into a written format. I also like that the platform keeps the transcription workflow organized and makes it easier to process recorded content when needed. Performance has been smooth during my use, and transcript generation is generally completed quickly. I do not use it every day, but I use it whenever I need transcripts from recorded content. Overall, AssemblyAI helps make audio-to-text conversion more organized, efficient, and easier to manage as part of my content creation workflow. Review collected by and hosted on G2.com.

When testing different transcription settings and models, it can take a little time to understand which option is best for a particular type of audio. More guidance during selection would make the process easier. Also, The transcript quality is generally good, but background noise, overlapping speech, or unclear recordings can still require some manual cleanup. This is not frequent, but it can happen with real-world audio. Review collected by and hosted on G2.com.

What I like best about AssemblyAI - Speech to Text API is its high transcription accuracy and developer-friendly integration. The API delivers reliable results even with different accents and noisy audio, which is very important for real-world applications. I also appreciate the fast processing speed and features like automatic punctuation, speaker diarization, and summarization, which save a lot of development time.

Another major advantage is how easy it is to integrate into apps. The documentation is clear, and the API works smoothly with modern tech stacks. It has significantly improved my workflow by automating transcription and reducing manual effort. Overall, it’s a powerful and scalable solution for building AI-based audio applications. Review collected by and hosted on G2.com.

One downside of AssemblyAI - Speech to Text API is that pricing can become expensive at scale, especially for apps with high audio usage. While the accuracy is generally strong, it can still struggle with heavy background noise, multiple speakers talking simultaneously, or strong regional accents.

Additionally, some advanced features may require extra configuration and are not always straightforward for beginners. Real-time transcription latency can also vary depending on audio quality and network conditions. Overall, while it’s a powerful tool, optimizing cost and handling edge cases can require extra effort. Review collected by and hosted on G2.com.

I like how easily the AssemblyAI - Speech to Text API can be used and applied in real-life scenarios. Despite not being a coder, setting it up was very easy for me, which was the game-changing aspect. I wasn't initially aware of how to use an API or handle many calls simultaneously, but with AssemblyAI, I was able to set up the whole thing on my own and use it quite efficiently. Review collected by and hosted on G2.com.

I use AssemblyAI - Speech to Text API to get the transcription and OpenAI API for analysis of that transcription, and I feel the same thing can be added in AssemblyAI. It can be very helpful where it gives me the capability to ask questions directly from the transcription. They can add a model which analyzes the transcripts and then gives me the analysis based on the prompt I give; that would be game-changing. Review collected by and hosted on G2.com.

AssemblyAI’s Speech-to-Text API was quick for our team to integrate, and it delivers accurate transcription results even with long audio files and conversations involving multiple speakers. The documentation is easy to understand, and the setup process was smooth end to end. Features such as speaker identification, summarization, and real-time transcription saved us a lot of development time because we didn’t have to build those capabilities ourselves. In regular use, the API feels fast, reliable, and straightforward to work with. It also scales well, which makes it a good fit for both small projects and larger production applications. Review collected by and hosted on G2.com.

One drawback is that the pricing can get expensive when you’re processing a large volume of audio. Overall, the transcription quality is good, but it can still make mistakes with strong accents, background noise, or unclear speech, so I usually need to do a few manual corrections. Some of the more advanced features can also be confusing for new users at first and take time to understand. It would be better if the dashboard offered simpler analytics and clearer monitoring tools to make it easier to track what’s going on. Review collected by and hosted on G2.com.

I really like how accurate AssemblyAI - Speech to Text API is in transcribing calls, even handling tougher accents like Irish very well. The ease of connecting it to my API makes the process of sending recordings for transcription super easy. I also found the initial setup to be super easy; I just needed to copy-paste an API key, and I was good to go. The $50 of included credits was brilliant as well. Review collected by and hosted on G2.com.

I don't have too much criticism, to be honest. The only thing that I can think of is transcription were a tiny bit better. It's already way better than other models that I've tried. But there's always room for improvement with transcriptions, particularly with more difficult accents. Review collected by and hosted on G2.com.

It is very easy to integrate with and the transcriptions seem to process very quickly. Pricing is fair, and they give you a generous free trial to test you integration without having to pay. Review collected by and hosted on G2.com.

I have not come across anything that I dislike so far. I think there might be opportunity to release a ruby sdk that would help make integration even quicker. Review collected by and hosted on G2.com.

I like AssemblyAI because it provides accurate transcriptions, easy API integration, and useful features like speaker detection and summaries that save significant development time. Review collected by and hosted on G2.com.

The pricing can become expensive at higher usage levels, and transcription accuracy occasionally drops with poor audio quality or strong background noise. Review collected by and hosted on G2.com.

I like AssemblyAI - Speech to Text API because it seems to be very accurate and I like how it separates different speakers. It's been very simple to set up, which is great since I'm a one-man operation. Having perfect transcripts is very important for my signal extraction workflow. Review collected by and hosted on G2.com.

It'd be nice to have an automatic switch to a lower skilled version if needed to reduce the cost. I've just warned them to keep the transcripts to a minimum for their long podcasts. Review collected by and hosted on G2.com.

I like that AssemblyAI - Speech to Text API is reasonably priced and quite accurate. It's cheaper than other tools like OpenAI Whisper, yet the quality is good and it's reasonably fast. I also appreciate that it offers $50 in starter credits and has tested well in quality. The initial setup was pretty easy too. Review collected by and hosted on G2.com.

I wish it was faster, identified speakers better, and cost less. Speed is the biggest thing, my product doesn’t work well with longer podcast episodes (over an hour) because it takes so long to transcribe it sometimes times out or fails in Vercel. Review collected by and hosted on G2.com.

I find the AssemblyAI - Speech to Text API very reliable, especially when it comes to the German language. It processes the German language accurately and is among the services with the highest accuracy in this area. Although it is sometimes a bit slow, everything else works quite well. Review collected by and hosted on G2.com.

Actually, mainly just speed, sometimes it could be a bit faster. And mainly perhaps continue working on the quality of the transcripts. Right. Especially when, for example, industry-specific or company-specific terms are mentioned, like certain names of people or names of projects or products or so, which occur more frequently. That one would have the possibility for the SMLD to basically recognize these terms more accurately. Especially in the German language. Review collected by and hosted on G2.com.