NVIDIA
NVIDIA
RIVA Magpie-TTS Multilingual
Model
NVIDIA
NVIDIA
RIVA Magpie-TTS Multilingual

Riva NeMo-MagpieTTS Multilingual IPA multispeaker model with Emotions

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Speech Synthesis: Multilingual Multispeaker - MagpieTTS Model Overview

Description:

The Magpie-TTS model leverages an encoder-decoder transformer architecture for speech synthesis. The encoder processes text input, and the auto-regressive decoder takes a reference speech prompt from the target speaker. The auto-regressive decoder then generates speech tokens by attending to the encoder’s output through the transformer’s cross-attention heads. These cross-attention heads implicitly learn to align text and speech. However, their robustness can falter, especially when the input text contains repeated words.

References:

MagpieTTS Blog

Model Architecture:

Architecture Type: Transformer + Generative Adversarial Network (GAN)

Network Architecture: MagpieTTS + AudioCodec

Input:

For MagpieTTS (1st Stage): Text Strings

Other Properties Related to Input: 400 Character Text String Limit

Output:

For AudioCodec (2nd Stage): Audio of shape (batch x time) in wav format

Other Parameters Related to Output: Mono, Encoded 16 bit audio; 20 Second Maximum Length; Depending on input, this model can output a female or a male voice for English, French and Spanish.

Software Integration:

Runtime Engine(s): Riva 2.19.0 or greater

Supported Hardware Platform(s):

  • NVIDIA Blackwell GPU
  • NVIDIA Turing T4
  • NVIDIA A100 GPU
  • NVIDIA A30 GPU
  • NVIDIA A10 GPU
  • NVIDIA H100 GPU
  • NVIDIA L4 GPU
  • NVIDIA L40 GPU

Supported Operating System(s):

  • Linux

Inference:

Engine: Triton
Test Hardware:

  • NVIDIA Blackwell GPU
  • NVIDIA Turing T4
  • NVIDIA A100 GPU
  • NVIDIA A30 GPU
  • NVIDIA A10 GPU
  • NVIDIA H100 GPU
  • NVIDIA L4 GPU
  • NVIDIA L40 GPU

Ethical Considerations:

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License

By downloading and using the models and resources packaged with Riva Conversational AI, you accept the terms of the Riva license.

Publisher
NVIDIA
NVIDIA
Latest Versiondeployable_1.0
UpdatedMarch 19, 2025 UTC
Compressed Size653.92 MB