Speech AI can assist human agents in contact centers, power virtual assistants and digital avatars, generate live captioning in video conferencing, and much more. Under the hood, these voice-based technologies orchestrate a network of automatic speech recognition (ASR) and text-to-speech (TTS) pipelines to deliver intelligent, real-time responses. Building these real-time speech AI applications from scratch is no easy task. From setting up GPU-optimized development environments to deploying speech AI inferences using customized large transformer-based language models in under 300ms, speech AI pipelines require dedicated time, expertise, and investment. In this post, we walk through how you can simplify the speech AI development process by using NVIDIA Riva to run GPU-optimized applications.

"We shape our tools and, thereafter, our tools shape us." Making the right technology decisions at the start of your chatbot journey has a significant influence on what your chatbot's trajectory will be. Choose and shape your tools wisely. As later in the process those tools will shape and influence the way you plan, develop, scale your chatbot. Chatbot development tools and frameworks can be divided into three categories, roughly.

"We shape our tools and, thereafter, our tools shape us." Making astute technology decisions at the inception of your chatbot journey has a significant impact on what your chatbot's trajectory will be. Choose and shape your tools wisely. Because, later in the process those tools will shape and influence the way you plan, develop, scale your chatbot. Impediments are usually system or framework related.

NVIDIA is busy developing Riva Studio which will help in building applications such as chatbots, virtual assistants and multimodal virtual assistants that leverage Riva skills. This eludes to the fact that NVIDIA will have a skills approach, like Microsoft, IBM etc. Looking at the demo examples, it could stand NVIDIA in good stead to have a more disparate approach in dialog state management. I have written in the past how a Riva dialog state management environment might look. Points 1 & 2, and 3 & 4 are usually tightly coupled.