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parakeet-ctc-0.6b-zh-cn

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Record-setting accuracy and performance for Mandarin English transcriptions.

ASRMandarinNVIDIA NIMStreamingSpeech-to-Text
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Accelerated by DGX Cloud

Speech Recognition: Parakeet CTC 0.6b Mandarin English Code Switch Model

Description

RIVA Parakeet-CTC-XL-0.6B-Unified ASR Mandarin (around 600M parameters) [1] is trained on ASR Set with over 17,000 hours of Mandarin (zh-CN) and English (en-US) speech. The model transcribes speech in Mandarin and English, in upper case and lower case alphabets, along with punctuations (period, comma, and question mark), spaces, and apostrophes.

This model is ready for commercial use.

License/Terms of Use

GOVERNING TERMS: The use of this model is governed by the NVIDIA Community Model License (found at https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-community-models-license/).

References

[1] Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition
[2] Fast-Conformer-CTC Model
[3] Conformer: Convolution-augmented Transformer for Speech Recognition

Model Architecture

Architecture Type: Parakeet-CTC (also known as FastConformer-CTC) [1], [2] which is an optimized version of Conformer model [3] with 8x depthwise-separable convolutional downsampling with CTC loss
Network Architecture: Parakeet-CTC-XL-0.6B

Input

Input Type(s): Audio
Input Format(s): wav
Input Parameters: 1-Dimension
Other Properties Related to Input: Maximum Length in seconds specific to GPU Memory, No Pre-Processing Needed, Mono channel is required.

Output

Output Type(s): Text Output Format: String (in Mandarin and English)
Output Parameters: 1-Dimension
Other Properties Related to Output: No Maximum Character Length, Does not handle special characters.

Supported Operating System(s):

  • Linux

Model Version(s):

Parakeet-CTC-XL-unified-0.6b_spe7k_zh-CN_3.0

Training & Evaluation

Training Dataset

Data Collection Method by dataset

  • Human

Labeling Method by dataset

  • Human

Properties:

This model is trained on over 17,000 hours of Mandarin (zh-CN) and English (en-US) speech, comprised of a dynamic blend of public and internal proprietary datasets normalized to have upper-cased, lower-cased, punctuated, and spoken forms in text.

Evaluation Dataset

Data Collection Method by dataset

  • Human

Labeling Method by dataset

  • Human

Properties:

A dynamic blend of public and internal proprietary datasets normalized to have upper-cased, lower-cased, punctuated, and spoken forms in text.

Inference

Engine: Triton
Test Hardware:

  • NVIDIA A2
  • NVIDIA A10
  • NVIDIA A16
  • NVIDIA A30
  • NVIDIA A40
  • NVIDIA A100
  • NVIDIA H100
  • NVIDIA L4
  • NVIDIA L40
  • GeForce RTX 40xx
  • GeForce RTX 50xx
  • Blackwell RTX 60xx

Ethical Considerations (For NVIDIA Models Only):

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety & Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns here.