Home > AI Solutions > Artificial Intelligence > White Papers > AI Driven Speech Recognition and Synthesis on Dell APEX Cloud Platform for Red Hat OpenShift > Solution overview
Imagine how much insight a company could extract from its support calls. Frequently asked questions, product usage patterns, customer behavior, and even market trends are examples of invaluable insights that might be available to many businesses in the form of audio. An accurate, high-performance, and scalable speech recognition solution is required to unlock the potential of audio data.
To help clients add conversational capabilities to their modern containerized applications, the solution described in this white paper uses NVIDIA Riva Speech services running on Dell APEX Cloud Platform for Red Hat OpenShift. This platform is well-suited for AI applications, because it offers a turnkey solution for containerized applications, bringing the cloud experience to customers’ data centers. It simplifies deployment and alleviates management burdens through a ready-to-use platform, combined with the leading Kubernetes orchestration solution.
Dell APEX Cloud Platform for Red Hat OpenShift integrates with Red Hat OpenShift AI, an open-source ML platform for the hybrid cloud, to build and deploy AI applications. OpenShift AI combines Red Hat components, open-source software, and technology partner offerings with the flexibility to develop and serve models on-premises or in public clouds. The platform makes it simple to embrace hardware acceleration without requiring users to perform daily management of Kubernetes.
NVIDIA Riva is a Kubernetes-based software development kit (SDK) that builds GPU-accelerated speech AI applications. Its pre-trained models empower the creation and deployment of fully customizable, real-time AI pipelines, delivering world-class accuracy across diverse environments—whether in the cloud, on-premises, at the edge, or on embedded devices.
Although, as mentioned in the Executive summary, conversational AI applications are relevant in several use cases and various industries, this document frames the application of speech recognition and natural language processing in the context of call center operations requirements.