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Table · dataset · 2026

Preference-ASR

Listed in Hugging Face Datasets

Preference-ASR Preference-ASR tests whether an ASR system can follow natural-language instructions about how a transcript should be written.

Description

Should numbers appear as words or digits? Should disfluencies stay in the transcript?

How should names be spelled and cased? Conventional ASR benchmarks assume a single answer style, and their normalizers often erase the differences those questions are meant to test. Each example in Preference-ASR instead pairs an audio clip with a… See the full description on the dataset page: huggingface.co/datasets/nvidia/preference-asr-bench.

Links

Where it is published

Documentation and papers

Catalogue records · 1

Topics

Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsnvidia/preference-asr-bench13 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:audiosource · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].local:modality:audiomapping · Hugging Facevocabulary-mapper@1.0.0keywords['speech']
concepts[task].hf_task:automatic-speech-recognitionsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
licensesource · Hugging Faceconnector:huggingface@1.0.0/tags[license:*]
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0