W2
ENT-00001432 · Foundation Model

wav2vec 2.0

wav2vec 2.0 is a self-supervised speech model associated with Meta AI.

Level IV — ConnectedActiveStructured
Human readable record

Overview

wav2vec 2.0 is a self-supervised speech model associated with Meta AI. The entity is included because it represents a distinct public model, architecture, benchmark, dataset or AI research system with an identifiable source base and documented role.

Timeline

  1. 2020wav2vec 2.0 public release or documentation

    wav2vec 2.0 appears in public documentation as a self-supervised speech model associated with Meta AI.

Capabilities

Documented AI capabilityResearch or product source anchorModel or system lineageRelationship mapping

Known limitations

Capabilities depend on version, training data, deployment configuration and evaluation setting.The record documents public identity and source context rather than private implementation details.
Technical and registry detail

Technical description

Structured record for wav2vec 2.0. The technical layer captures creator, release period, source anchor, system category, capability profile, limitations and relationships to adjacent models, platforms, benchmarks or research systems.

Controlled tags

Foundation ModelDocumented EntityContemporaryBatch 03 Candidate
Relationship graph
wav2vec 2.0
Created or maintained byMeta AI

wav2vec 2.0 is associated with Meta AI.

Machine readable layer

Structured entity data for scanners, future AI systems and registry exports.

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    "identifier": "ENT-00001432",
    "name": "wav2vec 2.0",
    "alternateName": [],
    "additionalType": "Foundation Model",
    "description": "wav2vec 2.0 is a self-supervised speech model associated with Meta AI.",
    "creator": "Meta AI",
    "url": "entity.php?id=ENT-00001432",
    "sameAs": "https://github.com/facebookresearch/fairseq/tree/main/examples/wav2vec",
    "lxkeysWorld": {
        "classification": "self-supervised speech model",
        "organization": "Meta AI",
        "originContext": "AI model, architecture and research record",
        "firstPublicAppearance": "2020",
        "currentStatus": "Active",
        "registryStatus": "Structured",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "level": "Level IV — Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:14+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:14+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "capabilities": [
            "Documented AI capability",
            "Research or product source anchor",
            "Model or system lineage",
            "Relationship mapping"
        ],
        "limitations": [
            "Capabilities depend on version, training data, deployment configuration and evaluation setting.",
            "The record documents public identity and source context rather than private implementation details."
        ],
        "tags": [
            "Foundation Model",
            "Documented Entity",
            "Contemporary",
            "Batch 03 Candidate"
        ],
        "timeline": [
            {
                "date": "2020",
                "title": "wav2vec 2.0 public release or documentation",
                "description": "wav2vec 2.0 appears in public documentation as a self-supervised speech model associated with Meta AI."
            }
        ],
        "relationships": [
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                "type": "Created or maintained by",
                "description": "wav2vec 2.0 is associated with Meta AI.",
                "evidence_level": "documentary"
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        ],
        "sources": [
            {
                "label": "wav2vec 2.0 public reference",
                "url": "https://github.com/facebookresearch/fairseq/tree/main/examples/wav2vec",
                "source_type": "Official or Research Source",
                "verification_status": "verified"
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        ]
    }
}
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