## Model Overview Conformer-CTC (around 120M parameters) is trained on ASRSet with over 4100 hours of Spanish (es-US) speech. The model transcribes speech in lower case Spanish alphabet along with spaces and apostrophes. ## Model Architecture Conformer-CTC model is a non-autoregressive variant of Conformer model for Automatic Speech Recognition which uses CTC loss/decoding instead of Transducer. For more information, refer to the [Conformer-CTC Model](https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/asr/models.html#conformer-ctc) documentation. ## Terms of use By using this software or microservice, you are agreeing to the [terms and conditions](https://www.nvidia.com/en-us/data-center/products/nvidia-ai-enterprise/eula/) of the license and acceptable use policy. # Disclaimer AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data. Your use is logged for security. # References * [Paper](https://arxiv.org/abs/2005.08100) * [Conformer](https://docs.nvidia.com/nemo-framework/user-guide/latest/nemotoolkit/asr/models.html#conformer) ## Model Architecture **Architecture Type:** Convolutional Neural Network + Transformer
**Network Architecture:** Conformer Encoder with CTC Decoder
## Input **Input Type(s):** Audio in Spanish
**Input Format(s):** Linear PCM 16-bit 1 channel
## Output **Output Type(s):** Text String in Text String in Spanish
## Software Integration **Supported Operating System(s):**
* Linux
## Model Version * Conformer-CTC-L_spe256_es-US_3.1
# Inference **Engine:** Triton
**Test Hardware:**
* NVIDIA A10
* NVIDIA A100
* NVIDIA A30
* NVIDIA H100
* NVIDIA Jetson Orin
* NVIDIA L4
* NVIDIA L40
* NVIDIA Turing T4
* NVIDIA Volta V100
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