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A Transformer-Based Visual Piano Transcription Algorithm

2024-11-13 · Uros Zivanovic, Carlos Eduardo Cancino-Chacón

Automatic music transcription (AMT) for musical performances is a long standing problem in the field of Music Information Retrieval (MIR). Visual piano transcription (VPT) is a multimodal subproblem of AMT which focuses on extracting a symbolic representation of a piano performance from visual information only (e.g., from a top-down video of the piano keyboard). Inspired by the success of Transformers for audio-based AMT, as well as their recent successes in other computer vision tasks, in this paper we present a Transformer based architecture for VPT. The proposed VPT system combines a piano bounding box detection model with an onset and pitch detection model, allowing our system to perform well in more naturalistic conditions like imperfect image crops around the piano and slightly tilted images.

📄 PDF Abstract BibTeX arXiv:2411.09037

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Tasks

Information RetrievalMusic Information RetrievalMusic TranscriptionRetrieval

Methods 이 논문이 사용한 방법론

Attention 설명 없음
Absolute Position Encodings Absolute Position Encodings are a type of position embeddings for [Transformer-based models] where positional encodings are…
Label Smoothing Label Smoothing is a regularization technique that introduces noise for the labels. This accounts for the fact that datasets may have mistakes in them, so maximizing the…
Adam 설명 없음
Residual Connection 설명 없음
Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…

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