Google Cloud Speech-to-Text vs. Vertex AI

Google Cloud speech-to-text is best suited when you want to work on live calls and transcribe interviews, meetings, customer service calls, and other audio or video recordings into text format. This helps create searchable archives, generate meeting minutes, and improve accessibility for individuals with hearing impairments. The service can provide real-time captioning for live events, webinars, broadcasts, and presentations. This enhances accessibility for individuals who are deaf or hard of hearing and those viewing content in noisy environments or without sound. It does not work well where the internet bandwidth is not that good; it requires a very good and strong internet connection to work well. And also where there are strong accents, especially in the Mandarin language.

Incentivized

We needed to build some ML models and Vertex AI is one such place where all the functionalities are consolidated for model deployment, tweaking and monitoring. And although it is costly, it is compatible with google cloud services and is scalable which makes it the perfect tool for us.

Incentivized

• 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.

Incentivized

• 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

Incentivized

• The software does occasionally get confused by confusing terminology.
• Its web-based interface can also feel a tad hard to use compared to more appealing desktop apps.
• I've experienced the occasional technical issue, though the provider's support team is quick to troubleshoot.

• 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

Incentivized

I can share insights with stakeholders in record time. And robust API connections let me pipe text into my CRM, marketing automation, and other mission-critical systems

Vertex AI is very user friendly and it is very fast. We can spin up instances pretty quickly and it allows to work with GPU instances without much planning. Pages load up very quickly and tasks are competed pretty much in time frame. It integrates with other systems also very well.

Incentivized

The accuracy of Google Cloud Speech-to-Text is much better than any other tool. It has better API integration with 3rd party tools. The transcription is on at real-time basis with the best efficiency. It has good language support from across the globe. It provides better noise robustness compare to other tools.

Incentivized

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.

Incentivized

• Automating the transcription process saved time and resources compared to manual transcription.
• Speech-to-text enabled us to make audio content accessible to a wider audience, including individuals with disabilities.
• We gained valuable insights into customer preferences, behaviors, and sentiment by analyzing voice data.

Incentivized

• It consolidated all the functionalities in one place for AI and ML development.
• Scalable and compatible with google cloud services.
• Though we can manually allocate resources, it is still very costly.

Incentivized