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We use Google Cloud Text-to-Speech when we have an IVR and need to say something written on the API through the IVR. For example, if I'm on the IVR and need to say something to the customer that is written on the API, I need to vocalize this text. I use Google Cloud Text-to-Speech to take this text and vocalize it to the client.
Precision is the most valuable feature of Google Cloud Text-to-Speech because the text is perfectly voiced.
Google Cloud Text-to-Speech has just one female voice and one male voice in Brazil, while it has a lot of voices in other countries.
I have been using Google Cloud Text-to-Speech for two years.
Google Cloud Text-to-Speech has very good stability.
Google Cloud Text-to-Speech can be used extensively because you use and pay for it. The solution's scalability is very good.
The solution's initial setup is very simple. You have to register on Google Cloud and start using it.
I rate Google Cloud Text-to-Speech three out of ten for pricing.
The voice on Microsoft Text-to-Speech is a little bit better than the voice in Google Cloud Text-to-Speech.
Overall, I rate Google Cloud Text-to-Speech ten out of ten.
The solution is used for developing translators for chatbots.
In the past year, we won the hackathon with the chatbot and the chatbot is in two languages. We needed some solution for that translation. We didn't want to have two chatbots, one in English and one in Spanish. We wanted to have one chatbot in a multi-language format, and that is really a problem.
I like the languages and I made a multi-translator. You can write some in Spanish and then you can see the same sentence in English, Russian, and Hindi. For learning purposes, I'm interested in romance languages. I can compare the differences between Spanish, Portuguese, Romanian, and other romance languages.
I like how I can direct language, how I can direct the origin language, for example.
It's not complex to set up.
When you make a chatbot, you need to do it for only one language, typically. We now work in multilanguage companies, however, and we need a chatbot with smarter skills. We need a chat with the capacity of comprehension for English, Spanish, Hindi, and Chinese maybe, since we have people working in all that countries.
We had some problems with Dialogflow.
I don't like the sentiment analysis. I don't feel like it's that realistic.
I've been using the solution for two to three years.
It's very stable. The translation capabilities are better than, for example, Microsoft.
We did deal with technical support in the past. We wanted to make a multilanguage chatbot, however, we can't do that. You need to set it in one language.
I'm also familiar with Microsoft, however, Google can translate language more effectively.
The solution is easy to set up. It's not difficult. I'd rate it a five out of five in terms of the ease of setup. It's very straightforward.
The deployment is quick. It only takes a day or so.
I don't have a realistic outlook on the cost. We are working on the migration from server to data center in Jira, and that is a lot of work.
There is a lot of money to be made in languages. If you manage to create something that's very good with translation, you're going to become very wealthy.
I'd rate the solution a seven out of ten.
