Speech-to-Text for Contact Centers: Which API Handles Call Volume Best?

The article by Jose Nicholas Francisco delves into the challenges and considerations of selecting a Speech-to-Text (STT) API for contact centers operating under real telephony conditions, including narrowband audio, background noise, and speaker overlap. It emphasizes the importance of evaluating STT APIs based on their performance in production environments rather than relying on clean-audio demos, which do not reflect the complexities encountered in actual contact center scenarios. Key issues such as word error rate (WER) degradation due to acoustic conditions, the handling of alphanumeric data, concurrency limits during peak traffic, and cost modeling at scale are explored in detail. The article provides guidance on how to conduct realistic evaluations of STT APIs, stressing the necessity of testing with authentic telephony audio and load conditions to ensure reliability and compliance, particularly in regulated industries. Additionally, it highlights the significance of matching API capabilities to the specific call volume profiles and compliance requirements of a contact center to ensure optimal functionality and cost efficiency.