Google Cloud Speech-to-Text vs. Vertex AI

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google Cloud Speech-to-Text
Score 7.4 out of 10
N/A
Speech-to-Text on Google Cloud is a tool used to convert speech into text using an API powered by Google’s AI technologies. The vendor states users can transcribe content in real time or from stored files; deliver a better user experience in products through voice commands; and, gain insights from customer interactions to improve service.
$0.02
per min
Vertex AI
Score 8.6 out of 10
N/A
Vertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.
$0
Starting at
Pricing
Google Cloud Speech-to-TextVertex AI
Editions & Modules
Speech-to-Text V2 API
$0.016
per min
Speech-to-Text V1 API
$0.024
per min
Imagen model for image generation
$0.0001
Starting at
Text, chat, and code generation
$0.0001
per 1,000 characters
Text data upload, training, deployment, prediction
$0.05
per hour
Video data training and prediction
$0.462
per node hour
Image data training, deployment, and prediction
$1.375
per node hour
Offerings
Pricing Offerings
Google Cloud Speech-to-TextVertex AI
Free Trial
YesYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsSpeech-to-Text V1 API V1 offers data residency for multi region only. Models include short, long, phone call, and video. V1 does not include audit logging. New customers get $300 in free credits and 60 minutes for transcribing and analyzing audio free per month, not charged against your credits. Speech-to-Text V2 API V2 offers data residency for multi and single region. Models include short, long, telephony, video, and Chirp. V2 does include audit logging and support for customer managed encryption keys.Pricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
More Pricing Information
Best Alternatives
Google Cloud Speech-to-TextVertex AI
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Score 8.0 out of 10
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Score 7.8 out of 10
Medium-sized Companies
Zoom Contact Center
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Score 8.4 out of 10
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Score 7.8 out of 10
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Verint Speech and Text Analytics
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Score 8.4 out of 10
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Score 8.2 out of 10
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User Ratings
Google Cloud Speech-to-TextVertex AI
Likelihood to Recommend
7.0
(44 ratings)
8.0
(13 ratings)
Usability
7.4
(25 ratings)
-
(0 ratings)
Performance
-
(0 ratings)
7.1
(10 ratings)
Configurability
-
(0 ratings)
7.3
(10 ratings)
User Testimonials
Google Cloud Speech-to-TextVertex AI
Likelihood to Recommend
Google
So, I've had scenarios like when I collaborate with a team where the people are from around the world. So, I used it there, and we spoke to each other in their native language. That boosts everyone's confidence in our collaborative efforts. I've also utilized its model and the API in my projects, including a Virtual assistant and a multilingual application that allows us to learn languages from around the world. We tested it with a group of 12 people, and that's when it failed. I mean, it's not a failure, but it can't detect every person.
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Google
Vertex AI seems to be a lot more accurate with image editing versus other competitors (including free one). We do a lot of image creation, especially of dogs in very certain scenarios. We use Adobe Stock to get us started, but many times we need some very specific edits done to the image. We've found Vertex can produce those with a lot more precision than other AI image generators.
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Pros
Google
  • An amazing tool which helps a lot in a meetings.
  • It's an efficient tool for improving efficiency by saving a lot of time typing. It saves at least 40-50% of our time, thus increasing efficiency.
  • Incredible accuracy with multiple accents & multiple language.
  • It takes punctuation into consideration.
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Google
  • Vertex AI comes with support for LOTs of LLMs out of the box
  • MLOps tools are available that help to standardize operational aspects
  • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
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Cons
Google
  • Integration outside of the google eco system is challenging here.
  • Google Cloud Speech-to-Text works only with active internet connection if the internet bandwidth is low it effect the transcription process and can lead to data inaccuracy.
  • In terms of the pricing also this is at higher range which all the companies cannot afford like small scale organisation if they would like to use the tool they would look over the price to make the decision. Reducing the price can increase the product usage more
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Google
  • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
  • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
  • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
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Usability
Google
The reasoning behind my 10 is that the UI is very intuitive; I didn't require any formal training to use it. Google's speech-to-text is not just a conversion tool; it helps automate mundane tasks, saves time, and has an almost human-like understanding.
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Google
No answers on this topic
Performance
Google
No answers on this topic
Google
It's not always instant, but understandable when it's under heavy load. It's not impressive nor disappointing, just what is expected. But when calling this platform through API's for it to do the actions requested there is minimal delay and wait time. It feels very responsive and quick when integrating it with a call center chat platform for example.
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Alternatives Considered
Google
Google Cloud Speech-to-Text outperformed its competitors significantly in terms of accuracy, surpassing any other product available. Additionally, its support for multiple languages was unrivaled in the market. Moreover, for clients with robust bandwidth, Google Cloud Speech-to-Text offered real-time transcription capabilities, enabling users to transcribe live audio streams with minimal delay.
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Google
Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.
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Return on Investment
Google
  • It reduced our budget for assistants who transcribed files manually
  • It speeds up the process, because we can have a transcriptions straight after the interviews
  • It increased accuracy, because AI makes the transcriptions for every second, and you can find the words which were said at specific time.
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Google
  • It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
  • It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
  • It'll help you in terms of Security wherein we can use row level security access to authorized persons.
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ScreenShots

Google Cloud Speech-to-Text Screenshots

Screenshot of audio transcription creation -  Using the Speech-to-Text API from within the Cloud Console by creating an audio transcription is done in just a few steps. It can transcribe short, long, and streaming audio.Screenshot of creating subtitles for videos using AI -  Transcriptions with captions and subtitles can be added to existing content or in real time to streaming content. Google's video transcription model can be used for indexing or subtitling video and/or multispeaker content and uses similar machine learning technology as YouTube does for video captioning.Screenshot of adding Speech-to-Text to apps - The video pictures covers how to add AI to an application without extensive machine learning model experience. The pretrained Speech-to-Text API lets users enable AI for applications.Screenshot of Language, speech, text, and translation with Google Cloud API - The pictures displays a section of Google training course, where learners use the Speech-to-Text API to transcribe an audio file into a text file, translate with the Google Cloud Translation API, and create synthetic speech with Natural Language AI.

Vertex AI Screenshots

Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation -  A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.