datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ne-asr-dataset-nag-aug
NE ASR Augmented Dataset -- Nagamese (nag)
Augmented automatic speech recognition dataset for Nagamese (nag),
a Assamese-based creole language spoken in Nagaland, India.
Source
Augmented from sulabhkatiyar/ne-asr-nag
(original transcribed speech data from the ARTPARK-IISc Vaani project).
Language Information
Property
Value
Language
Nagamese
ISO 639-3
nag
Family
Assamese-based creole
Region
Nagaland, India
Tonal
No
Tier
D (23.76h… See the full description on the dataset page: https://huggingface.co/datasets/sulabhkatiyar/ne-asr-dataset-nag-aug.ne-asr-dataset-nag
Nagamese (nag) — ASR dataset
A small Nagamese (nag) speech-to-text dataset for automatic speech recognition
(ASR) of a low-resource North-East India language. Each example pairs a short audio
clip with its Romanized (Latin-script) transcript.
Source
Derived from the ARTPARK-IISc Vaani project (https://vaani.iisc.ac.in/)
Splits
Split
Samples
train
12,862
validation
1,532
test
1,717
Data fields
Each example has:… See the full description on the dataset page: https://huggingface.co/datasets/sulabhkatiyar/ne-asr-dataset-nag.mondegreen-asr-errors
Mondegreen ASR error pairs
(ASR hypothesis, gold text) pairs for Japanese ASR post-correction.
This build is simulated -- errors come from a phonetic corruption model, not from a real ASR system. It exists so the whole pipeline (gate training, benchmarks, figures, CI) is reproducible without a GPU. Treat every number derived from it as a stated assumption, not a measurement.
How it was made
synthetic text
-> phonetic corruption model (mondegreen.simulate)
->… See the full description on the dataset page: https://huggingface.co/datasets/NagaYu/mondegreen-asr-errors.reazonspeech_qwen3-asr_large_filtered
Summary
This is the ReazonSpeech corpus's large split, featuring Qwen3-ASR 1.7B transcriptions.
Since the original transcriptions often contain errors, comparing them with the Qwen3-ASR outputs could be useful.
This is a filtered version in which no insertions occurred from the original transcriptions to the Qwen3-ASR transcriptions.
Usage
import json
import webdataset as wds
from huggingface_hub import get_token
SHARDS = (
f"pipe:curl -sLf -H 'Authorization: Bearer… See the full description on the dataset page: https://huggingface.co/datasets/nagohachi/reazonspeech_qwen3-asr_large_filtered.reazonspeech_qwen3-asr_large
Summary
This is the ReazonSpeech corpus's large split, featuring Qwen3-ASR 1.7B transcriptions.
Since the original transcriptions often contain errors, comparing them with the Qwen3-ASR outputs could be useful.
Usage
import json
import webdataset as wds
from huggingface_hub import get_token
SHARDS = (
f"pipe:curl -sLf -H 'Authorization: Bearer {get_token()}' "
"https://huggingface.co/datasets/nagohachi/reazonspeech_qwen3-asr_large/"… See the full description on the dataset page: https://huggingface.co/datasets/nagohachi/reazonspeech_qwen3-asr_large.