• Don't get tripped up by thinking of the wrong kind of artificial intelligence (AI) when it comes to testing scenarios.
• To ensure the creation of a successful speech recognition engine, using enough high-quality data to train machine learning algorithms is paramount.
• Even where an algorithm has been built correctly, its performance still very much depends on the accuracy of the datasets it was trained with.
• In always striving for accuracy with our services while serving a number of different industries, we are able to continuously train our automatic speech recognition technology with incredibly precise data sets.
• AI/ML can be leveraged in the number of areas and scenarios to solve and help in our day to day testing activities.
• This talk would discuss about AI/ML, its impact, some existing solutions available to deal with it.
• This session will prove to you that, anyone just interested to learn about AI can get started on this journey.

Use Case:

In this prototype we are using speech to text recognition which will inturns
help to perform respective actions on particular web element.

1. Speech based automation framework
2. Framework written in java
3. Use of weak AI for speech to text conversion
4. Use of grammatical files for training data set