Azure AI Speech Reviews and Ratings

Use Cases and Deployment Scope

We use Azure AI Speech to capture the user's voice from an Angular frontend app to then tokenize/rank words for helping the User to have a fact checker in an open discussion with another speaker

Likelihood to Recommend

For a Call Center question/answer model, Azure AI Speech performs very well.

It is not ideal for creating a flawless Speech-to-Text based customer self-service experience, OpenAI performs better.

Use Cases and Deployment Scope

There are two main uses for this product within our organisation as of yet, firstly: we use the accurate voice analysis with custom speech models in lectures to ensure our lectures are accessible to students with hearing-related accessibility issues, mostly through live text translation. Secondly, students are able to use this service and integrate its functionality into their application development during projects within their computing degrees.

Likelihood to Recommend

This service is well suited for scenarios where you need to integrate text-to-speech and/or speech-to-text into applications. Within our organisation, it is primarily used by students for development purposes to enable said functionality but is also used to provide accessibility to students who have hearing-related issues. Its multi-language support is also beneficial for our international students who have English as a second language and are therefore able to rapidly translate any text or speech that they do not understand.

Use Cases and Deployment Scope

Simplicity on the initial implementation of Azure Cognitive Speech Services is a big plus. The features' flexibility is very unique and customizing any function is simple. The software reaches with powerful tools with effective voice recognition ability and easy to manage record and other business data management through Cloud services, and even the engagement functions and also predictive data analytics from this solution are the best.

Likelihood to Recommend

Ease of the functionalities and the best solution on customer services management and intelligent ability on multiple voice recognition with Azure Cognitive Speech Services are very helpful. Also, the reporting functions manipulation is great and excellent experience managing multiple contacts and the effective data analytics functions offers results in real-time data.

Use Cases and Deployment Scope

We use Azure Cognitive Speech Services to add speech to text, text to speech, and other AI-driven NLP-related speech services to our customised applications esp those involving chatbots for different business functions. The idea was to make use of speech services for mobile apps to make them hands-free and more accessible. The range of languages helped especially from an Indian context as only one competitor product could support as many Indian languages apart from a few European and middle eastern ones.

Likelihood to Recommend

Excellent for voice enabled apps

built in security so speech data does not go outside

Flexible deployment on the cloud

Speech translation in real time scenarios

Using customised keywords to activate IoT devices

Use Cases and Deployment Scope

It is one of the most advanced software available. Through its advanced features, it recognizes even distorted noise efficiently. We can effectively convert speech-to-text and text-to-voice, which helps us communicate, make notes, and accurately discover requirements.

Likelihood to Recommend

Azure Cognitive Speech Services can work with many languages and dialects, making it imperative for people working with multi-lingual clients. It also helps to catch speeches while conversing in meetings. The setup is complicated, which is why for a novice user - it is not an easy endeavor to use. The pricing is also high.

Use Cases and Deployment Scope

We have been using chatbots within our organisation for several years. Our users have been asking whether it is possible to have a simulated 'voice conversation' with a chatbot (i.e., the user speaks into their microphone, which is converted into text and passed to the chatbot, which returns a text response which is synthesised into speech). We have recently been using Azure Cognitive Speech Services to handle speech-to-text and text-to-speech elements of interacting with a chatbot.

Likelihood to Recommend

It is well suited for scenarios where there is a requirement to integrate speech-to-text and text-to-speech into user interaction, for example, with chatbots used internally at a large enterprise. We have also investigated the use of Azure Cognitive Speech Services for live captions during meetings and presentations and the additional translation of these captions from English into German.

Use Cases and Deployment Scope

We used it for a POC where we had to convert speech recordings from customers calling at our helpline to text. These text scripts were to be used for training and doing an analysis on customer sentiments. Azure cognitive speech services were used to convert speech to text. The scope of the use case was extended to analyze all customer conversations calling for inquiries and support.

Likelihood to Recommend

Azure Cognitive Speech Services is well suited for scenarios where you need real-time or batch-based data conversion - either from speech to text or text to speech, It can be used to interpret and document customer conversations or employee conversations or to make specific training programs. It can also be used to make and train avatars to read from a text document. It can also be made to use for cases where it can read for employees with special needs.

Use Cases and Deployment Scope

We mainly used Azure Cognitive Speech Services for text to speech and speech to text use cases to take note of the things we say to our client. As a technical support engineer, we say a lot of pointers and reminders to our clients and we have to make sure that we also know what we previously had told them so this is very important for us.

Likelihood to Recommend

Since this is made by Microsoft, integration wouldn't be a huge obstacle with your O365 applications. You just have to check if your apps are available for integration, use the available APIs then you are good to go.