Singer Identification
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Benchmarks
VocalSet
Most implemented
M2D2: Exploring General-purpose Audio-Language Representations Beyond CLAP
From Real to Cloned Singer Identification
Self-Supervised Contrastive Learning for Singing Voices
Addressing the confounds of accompaniments in singer identification
Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each source
VocalSet: A Singing Voice Dataset
Papers
Recognizing Ornaments in Vocal Indian Art Music with Active Annotation
Ornamentations, embellishments, or microtonal inflections are essential to melodic expression across many musical traditions, adding depth, nuance, and emotional impact to performances. Recognizing ornamentations in sing…
ChunkingGenre classificationSinger IdentificationTime Series AnalysisM2D2: Exploring General-purpose Audio-Language Representations Beyond CLAP
Contrastive language-audio pre-training (CLAP) has addressed audio-language tasks such as audio-text retrieval by aligning audio and text in a common feature space. While CLAP addresses general audio-language tasks, its …
Audio captioningAudio ClassificationAudio TaggingAudio to Text Retrieval+13From Real to Cloned Singer Identification
Cloned voices of popular singers sound increasingly realistic and have gained popularity over the past few years. They however pose a threat to the industry due to personality rights concerns. As such, methods to identif…
Contrastive LearningSinger IdentificationToward Leveraging Pre-Trained Self-Supervised Frontends for Automatic Singing Voice Understanding Tasks: Three Case Studies
Automatic singing voice understanding tasks, such as singer identification, singing voice transcription, and singing technique classification, benefit from data-driven approaches that utilize deep learning techniques. Th…
DiversityMusic ClassificationSelf-Supervised LearningSinger IdentificationSelf-Supervised Contrastive Learning for Singing Voices
This study introduces self-supervised contrastive learning to acquire feature representations of singing voices. To acquire robust representations in an unsupervised manner, regular self-supervised contrastive learning t…
Contrastive LearningSinger IdentificationVocal technique classificationBoosting the Predictive Accurary of Singer Identification Using Discrete Wavelet Transform For Feature Extraction
Facing the diversity and growth of the musical field nowadays, the search for precise songs becomes more and more complex. The identity of the singer facilitates this search. In this project, we focus on the problem of i…
Singer Identification