Data quality matters when building and refining a Classification Model

In the world of machine learning, data takes centre stage. It’s often said that data is the key to success. In this blog post, we emphasise the significance of data, especially when building a comment classification model. We will delve into how data quality, quantity, and biases significantly influence machine learning model performance. Additionally, we’ll explore techniques like undersampling as […]

Robustness Testing of Machine Learning Models

In the world of machine learning, assessing a model’s performance under real-world conditions is important to ensure its reliability and robustness. Real-world data is usually not perfect, it may contain messy data or data with noise, outliers, and variations. During model training, these types of data could be limited, and the model may not have received sufficient training to handle […]

Testing OpenAI Whisper with Indian Languages

In previous blog, we tested OpenAI Whisper for English language with different accents and observed it did great job. We also provided details about how we generated audios, setup and test details. In this blog, we attempted to test OpenAI Whisper’s capability to transcribe and translate Indian Languages. At Qxf2, our teammates work from different regions of India, and everyone […]

Testing OpenAI Whisper with different accents

At Qxf2, we did some black box testing on OpenAI Whisper – a tool that does speech recognition well. OpenAI Whisper is also capable of language detection and translation. This model can be tested in various ways, by adjusting different voice attributes such as volume, pace, pitch, rate, etc. However, in this particular case, we have chosen to test it […]