nvidia
/

stt_it_fastconformer_hybrid_large_pc

Automatic Speech Recognition

hf-asr-leaderboard

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igitman commited on Jun 22, 2023

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Add links to SDP configs

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@@ -191,9 +191,9 @@ The tokenizers for these models were built using the text transcripts of the tra
 The model in this collection are trained on a composite dataset (NeMo PnC IT ASRSET) comprising of 487 hours of Italian speech:
-- Mozilla Common Voice 12.0 (Italian) - 220 hours after data cleaning
-- Multilingual LibriSpeech (Italian) - 214 hours after data cleaning
-- VoxPopuli transcribed subset (Italian) - 53 hours after data cleaning
 ## Performance

 The model in this collection are trained on a composite dataset (NeMo PnC IT ASRSET) comprising of 487 hours of Italian speech:
+- Mozilla Common Voice 12.0 (Italian) - 220 hours after data cleaning. [Speech Data Processor](https://github.com/NVIDIA/NeMo-speech-data-processor) config used to prepare this data is [here](https://github.com/NVIDIA/NeMo-speech-data-processor/blob/main/dataset_configs/italian/mcv/config.yaml).
+- Multilingual LibriSpeech (Italian) - 214 hours after data cleaning. [Speech Data Processor](https://github.com/NVIDIA/NeMo-speech-data-processor) config used to prepare this data is [here](https://github.com/NVIDIA/NeMo-speech-data-processor/blob/main/dataset_configs/italian/mls/config.yaml).
+- VoxPopuli transcribed subset (Italian) - 53 hours after data cleaning. [Speech Data Processor](https://github.com/NVIDIA/NeMo-speech-data-processor) config used to prepare this data is [here](https://github.com/NVIDIA/NeMo-speech-data-processor/blob/main/dataset_configs/italian/voxpopuli/config.yaml).
 ## Performance