NCA-GENM Exam Dumps | You're building an application utilizing NVIDIA ACE to create interactive virtual assistants. The goal

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Question 176/192

You're building an application utilizing NVIDIA ACE to create interactive virtual assistants. The goal is to have the assistant respond to user queries in a natural and contextually relevant way. Which of the following choices, when implemented together, would significantly contribute to achieving this objective?

A. Employing Riva for accurate Automatic Speech Recognition (ASR) and Text-to-Speech (TTS), utilizing a large language model (LLM) fine-tuned on a domain-specific dataset for natural language understanding and response generation, and integrating a dialogue management system to maintain conversation context and manage turn-taking.

B. Primarily focusing on high-fidelity avatar rendering using Omniverse, neglecting the accuracy of speech recognition and the quality of the generated responses.

C. Relying solely on pre-trained LLMs without fine-tuning for the specific application domain, assuming that the models will generalize well to all types of user queries.

D. Using a rule-based system for response generation, avoiding the complexity of training and deploying an LLM.

E. Using a small, low-latency speech recognition model to ensure quick response times, even if it results in reduced accuracy and frequent errors.

Correct Answer: A

Natural and contextually relevant responses require accurate speech recognition, a capable LLM, and a dialogue management system to track context. Riva provides the speech components. A domain-specific LLM improves accuracy. Dialogue management enables coherent conversations. High-fidelity rendering (B) is secondary. Pre-trained LLMs (C) might lack domain expertise. Rule-based systems (D) are inflexible. Sacrificing accuracy for latency (E) hurts the user experience.

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