datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
korean-full-duplex-synthetic-dataset-preview
Korean Full-Duplex Synthetic Dataset Preview
Overview
Public preview of a Korean full-duplex synthetic speech dataset. This
repository contains 100 conversations sampled from a corpus of 89,273
conversations (2,000.5 hours); it does not publish the full corpus audio.
Preview contents
100 conversation WAV files
data/representative.jsonl
24 kHz, mono, 16-bit PCM
Events: normal, barge_in, backchannel, cutoff_by_user
Annotation format… See the full description on the dataset page: https://huggingface.co/datasets/Wi-Fi/korean-full-duplex-synthetic-dataset-preview.parakeet-hindi-asr
Parakeet Hindi-English Bilingual ASR
Fine-tuning NVIDIA Parakeet TDT 0.6B for bilingual Hindi-English automatic speech recognition.
Quick Start
# Download
pip install huggingface_hub
huggingface-cli download ketav/parakeet-hindi-asr --repo-type dataset --local-dir ./parakeet-hindi-asr
# Install dependencies
pip install nemo_toolkit[asr] bitsandbytes sentencepiece
# Train (after updating paths in config)
cd parakeet-hindi-asr/scripts
python ft_0.6B_hi_v3.py… See the full description on the dataset page: https://huggingface.co/datasets/ketav/parakeet-hindi-asr.KazMix-3
KazMix-3
Kazakh three-speaker overlapping-speech dataset for target-speaker ASR (TS-ASR), released with the Persona-ASR project. Given a short enrollment utterance of a target speaker and a 3-speaker mixture, the task is to transcribe only the target speaker, or reject the utterance when the target is absent.
This repository ships the mixture manifests and generation scripts, not the audio. Mixtures are derived from the Kazakh Speech Dataset (KSD, OpenSLR 140); download KSD and… See the full description on the dataset page: https://huggingface.co/datasets/issai/KazMix-3.KambaBench-ASR
KambaBench-ASR
Status: v0.0 — scaffold. No evaluation audio or gold transcriptions have been finalized yet.
An open, leakage-controlled, reproducible evaluation benchmark for Kamba (Kikamba, kam) automatic speech recognition (ASR).
KambaBench-ASR is designed to provide a common evaluation standard for Kamba speech-recognition systems. The benchmark is intended to be model-agnostic: any Kamba ASR system, whether based on Whisper, MMS, Omnilingual ASR, Parakeet, or another… See the full description on the dataset page: https://huggingface.co/datasets/lawmaluki/KambaBench-ASR.deafbench-synthetic-v2
DeafBench synthetic-v2
DeafBench synthetic-v2 is a frozen, 25-sample benchmark specification for
testing whether automatic speech recognition systems preserve information that
matters in accessible captions. It keeps conventional word error rate separate
from typed critical-information recall so a plausible transcript cannot hide a
lost time, digit sequence, username, code, Wi-Fi name, or proper name.
This repository publishes the reference text and reproducibility metadata. It… See the full description on the dataset page: https://huggingface.co/datasets/kvjones0243/deafbench-synthetic-v2.