Large Language Models (LLMs) have enabled businesses to build advanced AI-driven features, but navigating the many available models and optimization techniques isn't always easy.
If you’re looking to combine speech recognition (STT) and LLMs for cutting-edge voice apps, look no further! Our ultimate guide is finally here, and it’s filled with valuable strategies and hands-on insights from our work with hundreds of audio-first companies and extensive interviews with experts in AI note-taking, sales enablement and customer support.
What you'll learn:
Speech-To-Text
Customer service is evolving fast to meet new challenges. Today's clients expect immediate, accurate answers to increasingly specific queries and complaints. Meanwhile, contact centers need to reduce costs, improve efficiency, and maintain compliance…all while delivering exceptional experiences.
Product News
Even the most advanced speech-to-text (STT) systems can make mistakes, especially when they encounter unfamiliar words like brand names, technical acronyms, or non-standard pronunciations. For call centers and customer service platforms, these missteps aren’t just minor glitches. They can lead to broken workflows, misinterpreted customer needs, and frustrating experiences on both ends of the call.
Speech-To-Text
CCaaS and BPO providers live and die by the quality of the customer experience they deliver. Clients rely on them not just to answer calls, but to do so with consistency, professionalism, empathy, and accuracy every time.
