Speech
A scalable generative AI framework for speech recognition and text-to-speech.
Build and deploy custom speech AI and LLM solutions with PyTorch
NVIDIA NeMo Speech is a generative AI framework designed for developers building Automatic Speech Recognition, Text-to-Speech, and Speech LLM applications. It suits Python developers and researchers needing custom speech model pipelines.
What it is
Provides modular components for ASR, TTS, and Speech LLMs, allowing you to train, customize, and deploy speech models using PyTorch. It supports advanced architectures like Fastconformer and multi-language datasets.
Who it's for
Suits machine learning engineers and researchers building specialized speech pipelines. Does not suit non-technical clinicians or therapists seeking ready-to-use transcription apps without coding.
Key features
Streaming ASR Support
Build low-latency streaming speech recognition applications using cache-aware Fastconformer models.
Multilingual TTS
Synthesize natural speech across multiple languages using the MagpieTTS architecture.
PyTorch Integration
Integrates directly into existing Python and PyTorch environments without replacing your stack.
Flexible Inference
Deploy models via Docker containers or install directly from source using uv package management.
Up and running in 3 steps
Our honest verdict
What's great
- Built-in support for low-latency streaming ASR models
- Multilingual speech synthesis across numerous languages
- Integrates directly into existing PyTorch and Python environments
- Official NGC Docker containers available for reproducible deployments
Where it falls short
- Requires dedicated NVIDIA GPUs with CUDA for model training and practical inference
- Demands advanced Python and machine learning engineering skills to configure
- Setup involves managing complex source dependencies and lock files
Pricing & license
Free under the Apache-2.0 licence, with the only direct cost being the hardware infrastructure required to host and run the models yourself.
Open remote AI-training roles
870 open remote AI-training roles, updated November 14, 2026; most pay $20–$170 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
Use it, or have us set it up
FAQ
What hardware do I need to run NeMo Speech?
An NVIDIA GPU with CUDA support is required for model training and strongly recommended for performant inference.
Can I use my existing PyTorch environment?
Yes, the framework installs on top of your existing Python, PyTorch, and CUDA stack via pip or source.
Where do I find pre-trained model weights?
You can access official open weight checkpoints and model collections directly via the NVIDIA HuggingFace collection.
