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Accurate and optimized Spanish English transcriptions with punctuation and word timestamps.
NVIDIA Parakeet-CTC-0.6B is a 600M parameter model trained on ASR Set with over 28k hours of Spanish (es-US) and English (en-US) speech. The model transcribes speech in Spanish 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.
GOVERNING TERMS: This trial is governed by the NVIDIA API Trial Terms of Service (found at https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf).
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-XXL-0.6B
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 Type(s): Transcription for what was spoken in input speech
Output Type(s): Text
Output Format: String (in Spanish and English)
Output Parameters: 1-Dimension
Other Properties Related to Output: No Maximum Character Length, Does not handle special characters
Supported Operating System(s):
Parakeet-CTC-XL-unified-0.6b_spe1024_es-en-US_3.0
Data Collection Method by dataset
Labeling Method by dataset
Properties:
This model is trained on over 28,000 hours of Spanish (es-US) and English (en-US) speech, comprised of a dynamic blend of public and internal proprietary and customer datasets normalized to have upper-cased, lower-cased, punctuated, and spoken forms in text.
Data Collection Method by dataset
Labeling Method by dataset
Properties: A dynamic blend of public and internal proprietary and customer datasets normalized to have upper-cased, lower-cased, punctuated, and spoken forms in text.
Engine: Triton
Test Hardware:
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