0 views collected around this technical thread.
This article explains how to use NVIDIA Riva to rapidly deploy speech AI services, covering Riva's overview, Chinese ASR model updates, TTS capabilities, customization options, the Quickstart tool, and a Q&A session that clarifies deployment, model fine‑tuning, and integration with NeMo and Triton.
This article introduces NVIDIA’s open‑source NeMo framework, detailing its PyTorch‑based architecture for Speech AI, ASR and TTS training, NLP and LLM support, GPU‑optimized parallelism, pre‑trained model resources, fine‑tuning techniques, and the accompanying NeMo Aligner and Framework tools.
This article explains how to efficiently deploy speech AI models—including ASR and TTS—on GPUs using NVIDIA's Triton Inference Server and TensorRT, covering background challenges, GPU‑based solutions, decoding optimizations, Whisper acceleration with TensorRT‑LLM, streaming TTS improvements, voice‑cloning pipelines, future plans, and a Q&A session.
This article provides a comprehensive introduction to NVIDIA's NeMo toolkit for conversational AI, detailing its ASR capabilities, model architectures, training workflow, Chinese language support, deployment options, and additional speech AI features such as VAD and speaker diarization.
This article presents comprehensive best‑practice guidelines for deploying conversational speech AI—including ASR and TTS pipelines—on GPU servers using NVIDIA Triton Inference Server and TensorRT, covering workflow overview, performance optimizations, streaming inference, and real‑world deployment tips.
This article presents an in‑depth overview of Alibaba's real‑time voice dialogue system, covering the Hotline XiaoMi robot, the unique challenges of spoken interactions such as colloquialism, multimodality and duplex communication, and the research advances in ASR‑robust SLU, emotion detection, colloquial processing, and duplex conversation modeling.
The article describes the design and implementation of a voice robot platform, covering its background, layered architecture, dialogue flow, intent recognition techniques, micro‑service backend, and future improvements, highlighting how AI models and telephony integration enable automated multi‑turn voice interactions for sales and service scenarios.
On August 25, iQIYI’s Chengdu R&D Center hosted its second Technical Salon, featuring talks on AI-driven content understanding for short‑video feeds, speech synthesis and editing, industry‑standard speech recognition, semantic search ranking, anti‑spam UGC text analysis, and concluding with recruitment invites and a preview of the upcoming Shanghai salon.