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    Models/Automatic Speech Recognition/nvidia/stt_en_conformer_ctc_large

    stt_en_conformer_ctc_large

    by nvidia

    Identifier
    Model ID
    nvidia/stt_en_conformer_ctc_large

    Tags

    nemoautomatic-speech-recognitionspeechaudioCTCConformerTransformerpytorchNeMohf-asr-leaderboardRivaendataset:librispeech_asrdataset:fisher_corpusdataset:Switchboard-1dataset:WSJ-0dataset:WSJ-1dataset:National-Singapore-Corpus-Part-1dataset:National-Singapore-Corpus-Part-6dataset:vctkdataset:mozilla-foundation/common_voice_7_0dataset:facebook/multilingual_librispeechdataset:facebook/voxpopuliarxiv:2005.08100license:cc-by-4.0model-indexeval-resultsregion:us

    Use stt_en_conformer_ctc_large on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, stt_en_conformer_ctc_large runs as a managed extractor inside a processing pipeline. Point a bucket of automatic speech recognition data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.