Amazon SageMaker vs. Dragon Speech Recognition vs. Verint Speech and Text Analytics

Amazon Sagemaker suits well in areas of data science and Machine learnings where medium to high-volume data is to be used for analysis. For a lean and platform agnostic deployment, it provides kubernetes integration to containerize the solution and deploy on any platform. It is one of the best solution for technical users for training Machine Learning models.

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Dragon is well suited for occasional dictation whereas for short tasks it may be less appropriate. Step by step commands can take a lot of time to program however these would be worthwhile long term if it is a repetitive task. Dragon is a new language to learn and this can be overwhelming. By following the guide this will support you for future use and it is possible to learn by using the "click" command which replicates the mouse click. With this scenario you can say what you see for example in Word, say click home then click centre which will centre the document

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This is well-suited for those who want an easy out-of-the-box solution and gateway to AI insights, call attributes, easy front-end reporting, and robust integrations of the rest of Verint data. You can even use it to support knowledge transfer, identifying the best agents for a specific call type and those with the greatest opportunity to improve.

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• SageMaker is useful as a managed Jupyter notebook server. Using the notebook instances' IAM roles to grant access to private S3 buckets and other AWS resources is great. Using SageMaker's lifecycle scripts and AWS Secrets Manager to inject connection strings and other secrets is great.
• SageMaker is good at serving models. The interface it provides is often clunky, but a managed, auto-scaling model server is powerful.
• SageMaker is opinionated about versioning machine learning models and useful if you agree with its opinions.

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• The main advantage is that it calibrates itself around your tone and accent.
• Integration with many apps and operative system is good.
• Integrating custom words and acronyms is very easy, so, over time, recognition becomes very precise and customized.

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• One of the things that I find extremely beneficial about Verint Speech Analytics is the transcription. Sometimes you have an hour call, an hour and a half call, and you don't have time to listen to an hour and a half call. The beauty is that we can find the transcription and then we can look in it. It specifies where if you look in the interaction details in the back of the call, you can actually see the transcription. You can see it'll identify where in the call, what line at what timestamp did that call hit your category and with what string, with what term did it hit. And that is extremely beneficial. And we're trying to go through and find those little points of, sometimes they're points of abrasion, sometimes there are things that are going really well. I love that we have a transcription. I love that we can also see the screens that is vital because a lot of times, and again, not that we're trying to find something bad, but the reality is in any industry, there's in any call center environment, should I say, there's call avoidance. There's always going to be some agents, it's just in any call center, in any industry, it happens.
• Or sometimes our agents are just struggling. And if you see in real life, for example, a very high silence time, when we notice a trend, we'll start going into those calls and actually looking at those screens and seeing, is silence time call avoidance or could it be the agents are having difficulty utilizing the resources? Are the resources not clear? Is that what the delay is? Are they having trouble trying to find the answer? And a lot of times we found that too. We found they're searching and clicking and searching and clicking and it's because they just didn't know where to go. So that is a coaching opportunity. And sometimes it's a coaching opportunity, not so much in a positive way because they're purchasing things from Amazon. But I think, like I said, that's inherent in any call center environment. I do find the screens, the transcription, the trend analysis that's available within speech, there are so many things I could literally sit here and talk to you for quite some time.
• We love it. And I'm even more excited personally now because I learned so much, as I was saying, about being in the cloud and being in that open-source environment where all of these enhancements that Verint has. And they're so often that they enhance their products and their offering now these little bots and AI to help with all of these different aspects, but that's only available if you're in the cloud and the open source. So there's a lot of benefit in being in prem, in net platform, which is where we are. And we were able to provide a lot of meaningful insight and guidance into a lot of different pain points in the company. But I anticipate, and I have full confidence, that we'd be a much more effective team once we're able to move into the cloud. So I'm very hopeful for that. I'm anticipating what else we could discover.

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• Searching and descriptions can be easier to read and interpret.
• Training modules and customer service training representative could make on boarding employees easier.

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• Word recognition can always improve.
• Sometimes puts stray words or characters on the page if you forget to tell the microphone to go to sleep.
• Adds non-spoken words for no reason if there is a delay in speaking.

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• Automated scrubbing of PCI and PII data from transcription transcripts and recordings. Using AI to detect the payment screens in a real time manner vs having to program triggers.
• Easier way to bulk export transcriptions and recordings for our legal teams.

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• Nuance Dragon Speech Recognition is not up to par with any of the other AI voice recognition technologies currently available
• The software is also very buggy and crashes frequently
• Punctuation also seems like an afterthought for Nuance Dragon Speech Recognition software--requiring the user to speak out each comma, period, etc.

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So excited for all the new bot functionality that is to come with Verint Interaction Analytics. AI is the future and Verint is leading the way!

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Overall, its gives the functionality that I need in my role and can support with automating tasks. I mainly use it for autotext, to add blocks of text and it works universally across all applications. It saves time and works well in Windows 11. It works very well navigating the web.

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Because between the training and integration of this product, I feel that this has been a seamless integration. The amount of training that is provided is second to none and the tams make sure you are taken care of in every way. I have nothing but great things to say about this product.

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There are few unplanned outages within the platform

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There is often latency within the Speech Analytics module.

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One of the worst companies in terms of customer service getting the download file because of a laptop upgrade took me months of work. No jokes.

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We have not invested in another machine learning software at this time and so far this has proved very successful with our machine learning teams. As mentioned, I am training these individuals simply on the fundamentals of the software and using it/customizing it for their needs. It has been very easy to do this and has gotten great reviews across the organization so far.

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I have previously used Adobe Acrobat Reader in other organisations and I found it to be very good. However, as I purchased Nuance Dragon Speech Recognition for home use, there was a considerable difference in the price between the two products. For both work and home use,I found that Nuance Dragon Speech Recognition meets all my requirements.

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In my opinion, Verint Speech and Text Analytics would rank near the bottom, But all other solutions minus Qualtrics was an AI solution so that helped enhance the application greatly

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The system is relatively reliable with minimal downtime. However, when there is an issue, it is often addressed slowly and causes significant business issues

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• Using SageMaker, we can truly implement 'fail early, learn fast,' using an on-demand server for training.
• It also saves your money from investing in a physical server for very rare use.
• However, the pricing is high, but it will cost you only for what you use.

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• Nuance Dragon Speech Recognition has made it easier to dictate progress notes
• Nuance Dragon Speech Recognition has made seeing patients more efficient
• Nuance Dragon Speech Recognition was a little expensive for our smaller practice

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• We are still developing ROI; we have a lot of data, but it's hard to get insights from the data at times. Adoption is something we are working on evaluating.
• We have alerts that have saved us $ on benefit quoting errors.

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