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AssemblyAI vs Google Cloud Speech-to-Text comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

AssemblyAI
Ranking in Speech-To-Text Services
5th
Average Rating
9.0
Reviews Sentiment
8.4
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Google Cloud Speech-to-Text
Ranking in Speech-To-Text Services
3rd
Average Rating
7.8
Reviews Sentiment
6.2
Number of Reviews
8
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Speech-To-Text Services category, the mindshare of AssemblyAI is 6.4%, down from 9.5% compared to the previous year. The mindshare of Google Cloud Speech-to-Text is 15.1%, down from 18.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Speech-To-Text Services Market Share Distribution
ProductMarket Share (%)
Google Cloud Speech-to-Text15.1%
AssemblyAI6.4%
Other78.5%
Speech-To-Text Services
 

Featured Reviews

Ishu Patil - PeerSpot reviewer
Python Developer and Application Analysts at All Solutions
Automated call reviews have saved time and protect sensitive customer information
AssemblyAI can be improved by addressing accuracy, which is the aspect they can improve in noisy audio and overlapping speakers because that's where transcripts sometimes lose clarity. The speaker diarizations could be more consistent when multiple people talk at the same time, and the summarization could be more customizable, such as letting us control the format, bullets, action times, or departmental wise. Lastly, better monitoring tools and clearer error messages would help in production scaling. Accuracy in noisy audios must be improved, overlapping speaker handling must be improved, and also more stable diarizations. Support for more languages plus accents would also make us able to boost our work more effortlessly, and custom vocabulary boost would better support company-specific terms, product names, and technical words.
reviewer2252211 - PeerSpot reviewer
Principal Architect & NLP Python Developer at a computer software company with 1-10 employees
Support challenges persist despite audio technology advancements
Google Cloud Speech-to-Text is not entirely accurate, so we have to correct for those errors in our AI software. It uses neural networks, and that stochastic processing is 70% to 75% accurate. It gets it wrong too often, and since I personally work with this, I don't appreciate that. However, they seem to be the best option currently. We have to write our own improvements because their tools to improve transcription accuracy in our domain aren't very powerful. The timestamp technology for recognized words is inadequate, so we don't use it. We understand words based on their meaning, and we have a whole AI engine that does that, which is one of our differentiators from a product standpoint. We didn't use the custom voice creation feature; we just use their voices, which are fine for our purposes.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"AssemblyAI gives us high quality speech to text with strong out of the box features including diarization, summaries, chapters, and PII redactions; the big win is we don't just get transcripts, we get structured insights we can plug into analytics fast."
"The product's initial setup phase is very easy."
"We've found the solution scales well."
"The implementation is simple, and the outputs are very accurate and crisp."
"Google Cloud Speech-to-Text helps to keep my team more productive."
"I would suggest Google Cloud Speech-to-Text to others, primarily for the speaker diarization feature."
"During the time I used Google Cloud Speech-to-Text, it was very impactful to the organization as it made our tasks much easier to perform."
"You could dictate a bunch of stuff, and then you can get ChatGPT or something to clean it up."
"Google Cloud Speech-to-Text sounds incredibly natural, which is impressive."
 

Cons

"AssemblyAI can be improved by addressing accuracy, which is the aspect they can improve in noisy audio and overlapping speakers because that's where transcripts sometimes lose clarity."
"Sometimes, speaker diarization is affected, leading to incorrect speaker identification."
"Since it is a paid service, it is very difficult to access if a user does not have the credentials. Also, we have to create the API keys and secret keys repeatedly to maintain authentication and privacy."
"Google Cloud Speech-to-Text's trial experience could be improved by adding some extra minutes in the trial version."
"Given the numerous accents and dialects in India, Google Cloud Speech-to-Text could improve its handling of Indian accents."
"The multilanguage support for the chatbot needs to be better."
"The one thing that I find is when I often use specialized terms, and the solution doesn't know them."
"The tool's telephony model does not produce accurate results."
"Google Cloud Speech-to-Text is 100 out of 100 when it works, and when it doesn't work, which is fairly often, it gets a zero. It doesn't fail gracefully; it fails in an unexpected way."
 

Pricing and Cost Advice

Information not available
"The tool's cost is also very low. The tool is cheaply priced. It charges around 0.13 INR per call with a duration of five minutes."
"Cost-wise, I would say it is all-inclusive in the payment made to Google."
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Top Industries

By visitors reading reviews
University
18%
Comms Service Provider
16%
Manufacturing Company
8%
Insurance Company
8%
Computer Software Company
11%
Healthcare Company
9%
Comms Service Provider
8%
Manufacturing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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What is your experience regarding pricing and costs for Google Cloud Speech-to-Text?
Our experience with pricing and licensing for Google Cloud Speech-to-Text is that we didn't have any other viable choices, so we cannot effectively evaluate if it's well-priced or badly priced.
What needs improvement with Google Cloud Speech-to-Text?
Google Cloud Speech-to-Text is not entirely accurate, so we have to correct for those errors in our AI software. It uses neural networks, and that stochastic processing is 70% to 75% accurate. It g...
What is your primary use case for Google Cloud Speech-to-Text?
I can answer questions about my experience with SQL Server as we are trying to capture reviews for SQL Server. We don't use the reporting services within SQL Server; we're using this for heavy-duty...
 

Overview

 

Sample Customers

Information Not Available
Home Depot, Paypal, Target, HSBC, McKesson
Find out what your peers are saying about Deepgram, Microsoft, Google and others in Speech-To-Text Services. Updated: January 2026.
881,082 professionals have used our research since 2012.