datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CAIMAN-ASR-BackgroundNoise
Dataset Card for Myrtle/CAIMAN-ASR-BackgroundNoise
This dataset provides background noise audio, suitable for noise augmentation
while training Myrtle.ai's CAIMAN-ASR models.
Dataset Details
Dataset Description
Curated by: Myrtle.ai
License: Myrtle.ai's modifications to the source data are licensed under
the CC BY 4.0 license.
Some of the original data is under the CC BY 3.0 license; the rest is in the public domain.
Please see the Source Data section… See the full description on the dataset page: https://huggingface.co/datasets/Myrtle/CAIMAN-ASR-BackgroundNoise.ASR-WPM-And-Background-Noise-Eval
ASR WPM and Background Noise Evaluation Dataset
A dataset of annotated audio recordings for evaluating how different factors affect Whisper (and other ASR/STT systems) transcription accuracy.
Purpose
This dataset provides controlled audio samples with annotations to evaluate ASR performance across:
Speaking pace (fast, normal, slow, mumbled, whispered, weird voices)
Background noise (cafe, music, conversations in various languages, traffic, sirens, etc.)
Microphone… See the full description on the dataset page: https://huggingface.co/datasets/danielrosehill/ASR-WPM-And-Background-Noise-Eval.background-noise-detection-dataset
Speech-Free Background Noise Dataset — Real-World, Non-Synthetic (50+ Hours)
Dataset summary
50+ hours of real-world urban environmental/ambient background noise (field recordings) without intelligible speech (speech-free), from three scenes: airport, street, subway. The dataset is non-synthetic and intended for speech enhancement via noise augmentation and sound event detection (SED) as “clean background”/negative class
Full version of dataset is… See the full description on the dataset page: https://huggingface.co/datasets/kakadong2018/background-noise-detection-dataset.background-noise-detection-dataset
Speech-Free Background Noise Dataset — Real-World, Non-Synthetic (50+ Hours)
Dataset summary
50+ hours of real-world urban environmental/ambient background noise (field recordings) without intelligible speech (speech-free), from three scenes: airport, street, subway. The dataset is non-synthetic and intended for speech enhancement via noise augmentation and sound event detection (SED) as “clean background”/negative class
Full version of dataset is availible… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/background-noise-detection-dataset.background-noise-detection-dataset
Speech-Free Background Noise Dataset — Real-World, Non-Synthetic (50+ Hours)
Dataset summary
50+ hours of real-world urban environmental/ambient background noise (field recordings) without intelligible speech (speech-free), from three scenes: airport, street, subway. The dataset is non-synthetic and intended for speech enhancement via noise augmentation and sound event detection (SED) as “clean background”/negative class
Purpose and usage scenarios
Speech… See the full description on the dataset page: https://huggingface.co/datasets/NashAli/background-noise-detection-dataset.background_noisebackground_noise