datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
red_ace_asr_error_detection_and_correction
RED-ACE
Dataset Summary
This dataset can be used to train and evaluate ASR Error Detection or Correction models. It was introduced in the RED-ACE paper (Gekhman et al, 2022).
The dataset contains ASR outputs on the LibriSpeech corpus (Panayotov et al., 2015) with annotated transcription errors.
Dataset Details
The LibriSpeech corpus was decoded using Google Cloud Speech-to-Text API, with the default and video models.
The word-level confidence was enabled… See the full description on the dataset page: https://huggingface.co/datasets/google/red_ace_asr_error_detection_and_correction.audio-emotion-detection-dataset
Audio Emotion Detection Dataset
Github: Audio Emotion Detection Dataset
Connect with me : Linkedin
Speech clips in English and Hindi annotated with emotion labels and ASR transcripts.
Audio is sourced from public YouTube videos and trimmed to approximately 60 seconds per clip.
Noise reduction is applied via noisereduce and silero-vad.
Emotions (5 classes)
Label
Description
angry
Aggressive, confrontational speech
calm… See the full description on the dataset page: https://huggingface.co/datasets/RapidOrc121/audio-emotion-detection-dataset.audio-emotion-detection-dataset
Audio Emotion Detection Dataset
Github: Audio Emotion Detection Dataset
Connect with me : Linkedin
Speech clips in English and Hindi annotated with emotion labels and ASR transcripts.
Audio is sourced from public YouTube videos and trimmed to approximately 60 seconds per clip.
Noise reduction is applied via noisereduce and silero-vad.
Emotions (5 classes)
Label
Description
angry
Aggressive, confrontational speech
calm… See the full description on the dataset page: https://huggingface.co/datasets/kotangalechaitali9007/audio-emotion-detection-dataset.