On the surface, speech data collection sounds like it should be simple. After all, we all can record our voices with our phones at any time. However, a professional speech data collection project is about far more than just recording voices. Instead, we need a representative selection of speech data—including varied accents, tones, dialects, speech patterns, and conversations—that are part of our everyday lives. Speech data is a form of Ground Truth Data, a field in which we at Qualitest have deep expertise. Natural speech input is a vital component of many software products built using artificial intelligence (AI), machine learning (ML) and natural language processing (NLP).
Speaking is a foundational way we understand and communicate our experiences. Speech data collection captures a range of linguistics data to inform speech-driven ML programs that are used in NLP. It’s essential to have the right sensitivity, accuracy, and contextual understanding of the nuances of language to prevent misinterpretation of core speech data in ML programs.
NLP is the area of software development concerned with regular written and spoken language. Through NLP, programs can easily understand any statement and create a natural interaction with an AI program. For NLP to be successful, computers must learn and understand human language the same way we do. As a result, accuracy and contextual understanding are essential in reducing incorrect responses to user queries, improving response times, and enhancing the overall user experience.
While capturing speech data seems straightforward on the surface, the process is very complex. Every speech data collection project must address three essential challenges.
As trusted leaders in Ground Truth Data collection, Qualitest has developed a robust and repeatable approach to speech data collection. Our practices ensure each unique project has clear goals and proven strategies to collect the right speech data to meet client requirements.
Today, the adoption of speech-driven applications is widespread through home automation solutions, chatbots, voice assistants, and other technologies. As demands for these products increase, companies need accurate Ground Truth Data and proven speech data collection best practices. The difference between capturing data and capturing high-quality data can make or break product performance in the real world. Clear goals, careful planning, and expert guidance are necessary to create a speech data collection program that achieves top-tier results.