Results for “magpie”

Deploy, run, and test NVIDIA speech recognition, speech synthesis, and translation services in the cloud or on your own infrastructure. Guidance covers model selection, environment checks, custom models, and adjustments to speech processing and pronunciation.

• Deploy and test a speech recognition model
• Generate speech with Magpie
• Adjust pronunciation for specific words

Build English clinical speech-recognition benchmarks by selecting medical terms, checking pronunciations, and generating synthetic audio. Outputs include audio files and a NeMo manifest, a structured file listing recordings and metadata, ready for a separate scoring stage.

• Building a speech-recognition benchmark for a clinical specialty
• Checking synthesized pronunciations of drug and procedure names
• Generating evaluation audio across voices, noise, and contexts

Build or repair NVIDIA voice agents with Pipecat or LiveKit for real-time spoken conversations. Set up speech recognition, language models, and speech synthesis, customize pronunciation or multilingual routing, and deploy locally or in the cloud.

• Build a new real-time voice agent
• Repair an existing voice conversation pipeline
• Customize speech recognition and pronunciation

Prepare an environment for evaluating speech recognition on clinical terms. Checks the API key and Python dependencies, then tests NVIDIA's hosted services by generating speech from one synthetic sentence and transcribing it before the next stage.

• Preparing a clinical speech recognition evaluation
• Checking API access from a fresh environment
• Testing speech synthesis and transcription together