# NVIDIA NeMo Speech: Scalable Generative AI for Speech Models

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NVIDIA NeMo Speech is a powerful, scalable generative AI framework designed for researchers and developers focused on Large Language Models, Multimodal, and Speech AI. It provides tools for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS), enabling efficient creation, customization, and deployment of new AI models using existing code and pre-trained checkpoints. This framework supports a wide range of applications, from real-time streaming ASR to high-quality multilingual TTS.

GitHub: https://github.com/NVIDIA-NeMo/Speech
OSRepos URL: https://osrepos.com/repo/nvidia-nemo-speech

## Summary

NVIDIA NeMo Speech is a powerful, scalable generative AI framework designed for researchers and developers focused on Large Language Models, Multimodal, and Speech AI. It provides tools for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS), enabling efficient creation, customization, and deployment of new AI models using existing code and pre-trained checkpoints. This framework supports a wide range of applications, from real-time streaming ASR to high-quality multilingual TTS.

## Topics

- asr
- tts
- generative-ai
- deeplearning
- python
- speech-ai
- llm
- neural-networks

## Repository Information

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## Content

## Introduction

NVIDIA NeMo Speech is a comprehensive generative AI framework tailored for researchers and PyTorch developers working on advanced speech models. This includes Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and Speech Large Language Models (LLMs). The framework is engineered to streamline the process of creating, customizing, and deploying new AI models by leveraging existing code and a rich collection of pre-trained model checkpoints. It supports a wide range of applications, from real-time streaming ASR to high-quality multilingual TTS.

## Installation

NeMo Speech offers flexible installation options, allowing users to integrate it with their preferred Python, PyTorch, and CUDA versions.

### From source with uv (recommended)

For a reproducible setup with the actively-tested stack (Python 3.13, PyTorch 2.12, CUDA 13.2), `uv` is the recommended installer.

bash
git clone https://github.com/NVIDIA-NeMo/NeMo.git
cd NeMo
uv sync --extra all --extra cu13     # For CUDA 13.x (recommended)
# Use --extra cu12 for CUDA 12.x


This installs NeMo into a `.venv/` in editable mode.

### From PyPI with pip (fallback, bring your own versions)

If you prefer to use your own Python/PyTorch/CUDA stack, install PyTorch first (version ? 2.7), then install `nemo-toolkit` via `pip` or `uv pip`.

bash
uv pip install 'nemo-toolkit[asr,tts]'   # or plain: pip install 'nemo-toolkit[asr,tts]'


To pull NVIDIA's pinned PyTorch build, add the CUDA extra and the matching wheel index:

bash
pip install 'nemo-toolkit[asr,tts,cu13]' --extra-index-url https://download.pytorch.org/whl/cu132   # CUDA 13.x
pip install 'nemo-toolkit[asr,tts,cu12]' --extra-index-url https://download.pytorch.org/whl/cu126   # CUDA 12.x


## Examples

NVIDIA NeMo Speech provides a rich set of pre-trained models and demos to get started quickly. You can explore various models for ASR, TTS, and Speech LLMs.

*   **HuggingFace Collection**: Discover the latest open-weight checkpoints and interactive demos on the official [NVIDIA NeMo HuggingFace collection](https://huggingface.co/collections/nvidia/nemotron-speech){:target="_blank"}.
*   **Documentation**: The [NeMo Framework User Guide](https://docs.nvidia.com/nemo/speech/nightly/){:target="_blank"} offers comprehensive technical documentation, including tutorials and examples for implementing different speech models.
*   **Specific Demos**: Look for demos like [Nemotron 3 VoiceChat](https://build.nvidia.com/nvidia/nemotron-voicechat){:target="_blank"} for full-duplex conversations or [Nemotron-Speech-Streaming](https://huggingface.co/spaces/nvidia/nemotron-speech-streaming-en-0.6b){:target="_blank"} for real-time ASR.

## Why Use NVIDIA NeMo Speech?

NVIDIA NeMo Speech stands out as a robust framework for several reasons:

*   **Scalability**: Built for large-scale generative AI, it supports complex models and high-throughput applications.
*   **Comprehensive Features**: It covers a broad spectrum of speech AI tasks, including ASR, TTS, and multimodal LLMs.
*   **Efficiency**: Designed to help researchers and developers efficiently create, customize, and deploy new AI models.
*   **Pre-trained Models**: Access to a vast collection of pre-trained model checkpoints accelerates development and experimentation.
*   **Flexibility**: Works with your chosen Python, PyTorch, and CUDA versions, offering adaptability to existing environments.
*   **Active Development**: The project is actively maintained by NVIDIA, ensuring continuous updates and support for cutting-edge research.

## Links

*   **GitHub Repository**: [https://github.com/NVIDIA-NeMo/Speech](https://github.com/NVIDIA-NeMo/Speech){:target="_blank"}
*   **Official Documentation**: [https://docs.nvidia.com/nemo/speech/nightly/](https://docs.nvidia.com/nemo/speech/nightly/){:target="_blank"}
*   **HuggingFace Collection**: [https://huggingface.co/collections/nvidia/nemotron-speech](https://huggingface.co/collections/nvidia/nemotron-speech){:target="_blank"}
*   **Contributing Guide**: [https://github.com/NVIDIA-NeMo/NeMo/blob/main/CONTRIBUTING.md](https://github.com/NVIDIA-NeMo/NeMo/blob/main/CONTRIBUTING.md){:target="_blank"}