multilingual-asr
Ethio-ASR-multilingual-600MNemotron-3.5-ASR-Streaming-Multilingual-0.6b-CoreMLNemotron-3.5-ASR-Streaming-Multilingual-0.6B-ONNX-FP16Ethio-ASR-multilingual-1BNemotron-3.5-ASR-Streaming-Multilingual-0.6B-LiteRT-INT8nemotron-3.5-asr-streaming-multilingual-0.6b-litert-fp16Nemotron-3.5-ASR-Streaming-Multilingual-0.6B-LiteRT-FP16Ethio-ASR-multilingual-94M
open-asr-leaderboard-multilingual-datasets
ASR Leaderboard Datasets
This repository contains test splits from multiple speech corpora, including FLEURS, Common Voice (MCV), and Multilingual LibriSpeech (MLS).
How to Load
To load a specific subset, use load_dataset with the corresponding config_name in the format <set>_<lang>.
from datasets import load_dataset
# Load the FLEURS dataset for Bulgarian
fleurs_bg = load_dataset("nithinraok/asr-leaderboard-datasets", "fleurs_bg")
print(fleurs_bg)
# Load the… See the full description on the dataset page: https://huggingface.co/datasets/hf-audio/open-asr-leaderboard-multilingual-datasets.indic-multilingual-asr
Indic Multilingual ASR Dataset
A multilingual ASR dataset covering 13 major Indian languages with 1.1M+ samples.
Usage
from datasets import load_dataset
ds = load_dataset("grushaaaaa/indic-multilingual-asr", split="train")
Features
audio: 16kHz WAV audio
sentence: Transcription text
language: Language name
source: Source dataset
Zambia-MultiLingual-ASR-Dataset
🇿🇲 Zambia Multilingual ASR Dataset
A continuously growing and curated multilingual speech corpus for Zambian languages, designed to advance Automatic Speech Recognition (ASR) research through community-driven data collection and real-world evaluation.
Overview
The Zambia Multilingual ASR Dataset is an open, continuously evolving speech corpus developed as part of the ZamVoice project.
The dataset supports research and development of Automatic Speech… See the full description on the dataset page: https://huggingface.co/datasets/buumba641/Zambia-MultiLingual-ASR-Dataset.multilingual-wolof-french-asrKinyarwanda_Engligh_Multilingual_ASRThis dataset was created from Mozilla's Common Voice dataset for the purposes of Multilingual ASR on Kinyarwanda and English.
The dataset contains 3000 hours of multilingual training samples, 300 hours of validation samples and 200 of testing samples.
asr-lwazi-multilingual