Azure AI Speech vs. Azure Bot Service (Microsoft Bot Framework)

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.

Incentivized

It is suited for applications like computerizing messages, or any business thought that would require the entrepreneur to robotize their reactions, particularly assuming they are managing a ton of clients and they can't answer to every single one of them. It'd be the most ideal to computerize messages of enormous associations where the reactions measure up to the clients' assumptions. It would be less appropriate in associations where clients' viewpoints matter and every client is interesting and requires the association's consideration, where the specialist organization doesn't need to sum up the clients' interests.

• APIs offered are very robust.
• Languages supported is far greater than most of its competitors.
• Integration with our custom apps was easy.
• Speech models that we created using neural voices were quite impressive.
• Translation services worked really well.
• Built in machine learning opens it to a lot more business use cases for the future.

Incentivized

• Real-time communication.
• Lightweight software protocols.

Incentivized

• More support for India regional languages and the ability to interpret Indian dialect.
• More detailed documentation with more coded examples to be available.

Incentivized

• They have simplified the coding for the bot in Azure, but it would help if the coding was further simplified so that non-IT can operate [and] create it easily.

Azure Bot Service provides an integrated environment for bot development. Microsoft Azure Cloud is fully compatible and its security features. It's more important to pay attention to the logic of business than the specifics of each messenger. We don't have any issues using the bot framework because the implementation is excellent.

Incentivized

Support is helpful when we have a problem, but online documentation is lacking

Azure Cognitive Speech Services is simple and the interface is not complicated even for those getting started with these customer services tools and the best voice recognition. Setting the platform dashboard preferences is also an easy process and with the ability to manage workflow and document management the system functions are stable and effective.

Microsoft Bot Framework is much better and well more established without a lot of proprietary software/coding language. Lex is very limited with integration with standard hardware and network configurations. Lex has performance issues and was too slow to meet near real-time collaboration requirements. Bot Framework complements many other Microsoft communication products and this was key to implementing without a lot of new training required.

Incentivized

• It helps us catch requirements and make notes so that we don't forget when drawing out proposals.
• Also helps us with targeted pitches and helps save time.

Incentivized

• Interfaces with the SQL data set, tracks down plans/replies, and tests them with the SDK.
• Utilizing the system is made conceivable by the Bot Dev gateway. We can interface our bot in excess of ten channels, including Twilio Facebook, Twilio, Twilio, and Slack, and that's only the tip of the iceberg.
• It is expensive.