Microsoft Text Analytics Reviews

The ability to understand easily and requires no training.

Some what overwhelming at times.

But in long run it is beneficial in all aspects.

It helps because it makes my work easier and also there are a lot of languages supported.

MIcrosoft cognitive services lets you build apps to interpret, hear, speak natural needs of communication for few lines of code.

We can easily add speech, vision detection, emotion detection, search option into our app in any platform like iOS, windows or android.

Sometimes for few local languages, the recognition for some words has less sopport

Overall, a great product.

Solving Problems related to cognition - vision, voice, hear for the end user such as us.

Easy to use as the interface is simple. Most languages widely supported.

I like how it’s easy to use, you don’t really need training for it. It’s self explanatory

Na I like everything about it. Great way to provide us employees the tools we need to succeed in our jobs everyday

It’s makes my work lifestyle a lot easier

Feedback for surveys, especially when you have a large "client" base is a big hassle, but not when you have Microsoft text analytics in your corner. Just input the filters and run it, it will save you a ton of time. Also, the advancements in the filters and the ability to pinpoint words are a dream come true.

Sometimes when the replies are a bit unclear, the filters do not supply the right outcome and you have to do it the old-fashioned way. A more comprehensive dictionary would help.

Microsoft text analytics is a very capable assistant when it comes to data analysis. Just input your filters and it will take care of the rest. Some hazy or unclear answers though, might force you to do things manually so be sure and foresee the end results and prepare your queries accordingly.

As an educational institution, we need to sift through our surveys and forms replies very fast, in order to take swift action. Microsoft Text Analytics is helping us complete these tasks in a very fast and efficient way. The error margin is minimal and we get the results in a very fast and professional way.

I like how convenient it is to change phrases and codes in different webpages through one program. For example, if you have 5 webpages, you can edit/ update data across the platforms in a single action.

I find it difficult to operate the program since there’s a lot of features to it. Much like html scripting, requires in depth knowledge of how to build a website and manage pages. I prefer WYSIWYG front end web design.

I helped my coworker fix bugs and spelling errors. When there’s a spelling error or a code typo, I helped simplify the process of fixing them throughout his files.

I like how it helps me understand things and also helps me improve my vocabularies.

Not much for the language that I speak, which is Hmong. However, it provides more words, such as synonyms for me to think of another word to explain to customers who may not understand me if I am using big and difficult word.

I recommend them to use this to help them improve their business and partnership with others.

There's no problem on my end. It benefits everyone who is working to connect and know more about each other.

I have personally only used Microsoft's Linguistic Analysis API for part of speech tagging, but its POS tagger has served me well for several years. I rarely have issues with it being inaccurate, and its response time is usually pretty quick. Additionally, it is an Azure service, so if you're currently an active Azure user, it is relatively easy to gain access to the Linguistic Analysis API.

The rate limit was somewhat prohibitive for the project I was working on since I needed to make several different calls every few seconds. Additionally, there were several outages that obstructed my work throughout my time using the API.

Microsoft's Linguistic Analysis API offers services aside from part of speech tagging, but if you're looking for the best part of speech tagger to use, I would personally recommend using Stanford's open-source tagger. Unlike Microsoft's, you don't need any API keys, you don't need to worry about being dependent on an online solution, and you can make as many calls as your system can handle.

I previously used this API for my conversational artificial intelligence program, Aurora. The only component of the Linguistic Analysis API I used was the part of speech analyzer, but I ultimately ended up switching to Stanford's open source offline POS tagger to avoid being obstructed by API outages.

Especially after the events of the last couple of years, people are more "online" than ever before and this is creating a tsunami of feedbacks on almost every platform possible. Microsoft Text analytics actually helps by saving us time by "screening" and "categorizing" the feedback we get.

It is a very handy tool and I highly recommend using it sparingly.

In some cases, the person submitting a review is not very proficient in the language he is required to submit the feedback in so, some of the terms or words might not be precise or express the real feelings.

Receiving tons of messages as feedback from our students and their families is cumbersome. Microsoft Text Analytics helps us by categorizing them, thus facilitating the actions that might need to be done.

This is a very powerful tool and every organization that deals with big amounts of data needs.

Microsoft API offers some of the best , start of the art language processing. I love how easy it is to use, and it's seamless. You can use this to learn more about the big data through language models collected by Bing in the US market.

At times it can be overwhelming when you aren't sure which step to take for testing. Client libraries such as apex, bash, dart, or elixir can be confusing when you aren't used to how it's run.

Having knowledge of coding of at least some aspect is beneficial. This program definitely emphasizes Python.

I do not have major problems with microsoft web language model api, but rather I am learning how to build apps to see, speak and hear our needs using the best, natural methods of communication. You can easily add intelligent features into your applications.

I enjoy the data structuring and collection process of this build. The ease of use of the application in general is nice. Although not to be supported after this summer, the Azure sight documentation is quite sufficient.

It actually seems like a framework of a larger program snippet that doesn't yet exist. Simpler is not always better and then there is the question if consistency and overall stability.

Analyze trends and repetition

It has provided a generally enlightened experience in solving obstacles in our customer relations and feedback when attempting to decipher how to best meet our consumers needs.