MUSAN: A Music, Speech, and Noise Corpus
David Snyder, Guoguo Chen, Daniel Povey
TL;DR
This paper presents MUSAN, a comprehensive and publicly available dataset of music, speech, and noise, designed to improve voice activity detection and music/speech discrimination models across various applications.
Contribution
It introduces a new diverse corpus with multiple genres and languages, specifically created for training and evaluating VAD and music/speech discrimination systems.
Findings
Effective for music/speech discrimination in Broadcast news
Useful for voice activity detection in speaker identification
Released under a flexible Creative Commons license
Abstract
This report introduces a new corpus of music, speech, and noise. This dataset is suitable for training models for voice activity detection (VAD) and music/speech discrimination. Our corpus is released under a flexible Creative Commons license. The dataset consists of music from several genres, speech from twelve languages, and a wide assortment of technical and non-technical noises. We demonstrate use of this corpus for music/speech discrimination on Broadcast news and VAD for speaker identification.
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Code & Models
- 🤗nvidia/parakeet-tdt-0.6b-v3model· 254k dl· ♡ 747254k dl♡ 747
- 🤗nvidia/canary-1b-v2model· 123k dl· ♡ 371123k dl♡ 371
- 🤗chime-dasr/nemo_baseline_modelsmodel· 48 dl· ♡ 348 dl♡ 3
- 🤗SoSolaris/parakeet-tdt-0.6b-v3model· 7 dl7 dl
- 🤗ManuelZnnmc/parakeet-tdt-0.6b-v3model· 1 dl1 dl
- 🤗MadnessOverflow/parakeet-tdt-0.6b-v3-bpe-vocabmodel
- 🤗Endy2001/parakeet-tdt-0.6b-v3model· 3 dl3 dl
- 🤗everyscribe/parakeet-tdt-0.6b-v3model· 9 dl9 dl
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Taxonomy
TopicsSpeech Recognition and Synthesis · Music and Audio Processing · Speech and Audio Processing