Turning your words into insights is easier with Google speech to text
December 18, 2025

Turning your words into insights is easier with Google speech to text

Sania Abdul | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Google Cloud Speech-to-Text

Previously, converting the speech to text seemed very time-consuming. The team often needed quick access to the information from the calls, and this real-time transcription enables faster decision-making and keeps the process smoother. Certain times it's very hard and difficult to analyze the large volume of the data. Once the audio is converted into text, we can easily search for any keyword and perform data analysis, as a result of which it will help in improving the report. We as a technical support team use this tool daily to convert the customer conversations into text for quality checking purpose and sentimental analysis We also use this tool for transforming the audio of our field offers into text.

Pros

  • Provides high-speed real time streaming transcription like live captioning, automatic note capturing during the the meeting etc
  • It supports more than 120 languages, which keeps this product globally recognized. Well, it helps in multilingual call centers that majorly relayed on Google speech-to-text.
  • The transcription is formatted very clearly with proper punctuation, commas, and question marks; therefore, no human intervention is needed for correcting the data

Cons

  • Real-time transcription needed high-quality audio
  • Cost is high for the large-scale operations
  • Integration seems to be complex; for certain vocabulary, there is no special GUI for the nontechnical users to make any corrections
  • Great accuracy and consistency, where Google Speech to Text provides more consistent results and fewer errors with common accents.
  • Significant reduction in the manual transcription as a result of which lower labour cost and faster processing time which improves efficiency and reduces delay in the downstream applications
  • There is a scope of accuracy drop in very noisy and overlapping speech environments; as a result, transcription accuracy decreases, requiring manual correction
  • Unless usage is optimised or reduced, ongoing costs for higher volume data and usage will be considered high
This has broad language support for more than 125 languages. Supports both batch and real-time transcription. Onboarding is very easier with clear documentation.
A certain pretrained model works well without heavy tuning. There are certain areas of improvement, like the interface lacking built-in transcript editing. Cost and usage process can be harder for the new users and beginners.
processing large volumes of audio quickly supports time-sensitive decision-making. Easier integration into application like google cloud services and also it has an ability to support more than 125 languages and accents. The amount of the manual correction has been completely decreased, and overall quality of the data has been improved. By automated transcription it saves time reduces operational costs
Google low latency streaming api seems to be working best when compared to other cloud-supporting tools as this will help in realtime transcription for customer interactions. while comparing azure and amazon the google support more than 125 languages and ascents as we work with multilingual teams and customers so broad language coverage and reliable ascent handling seems to be very essential

Do you think Google Cloud Speech-to-Text delivers good value for the price?

Yes

Are you happy with Google Cloud Speech-to-Text's feature set?

Yes

Did Google Cloud Speech-to-Text live up to sales and marketing promises?

Yes

Did implementation of Google Cloud Speech-to-Text go as expected?

Yes

Would you buy Google Cloud Speech-to-Text again?

Yes

Microsoft Teams, Google Hangouts (Classic), Slack
Our real-time field service agents use this very much, as it converts the audio into text and handles moderate background noise, and it supports more than 120 languages. Performing the code switching is also very easy. Voice-based data entry inside internal applications and CRM systems. This does not work well when there is an heavy background noise, as this will drop the accuracy in loud environments. Certain high technical language words cannot be added automatically, as it wont have capacity to phrase it

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