论文标题
旋律使用无订单的nade，和弦平衡和阻塞吉布斯采样
Melody Harmonization Using Orderless NADE, Chord Balancing, and Blocked Gibbs Sampling
论文作者
论文摘要
连贯性和有趣性是评估旋律统一性的两个标准，旨在从符号旋律中产生和弦进展。在这项研究中，我们将无秩序的Nade的概念应用于旋律及其部分掩盖的和弦序列作为基于Bilstm的网络的输入，以学习掩盖的地面真理，并将其用于培训过程。此外，班级的权重用于补偿一些合理的和弦标签，这些标签在训练集中很少见。与训练的随机性一致，在推理阶段使用适当数量的掩盖/生成环的阻塞Gibbs采样，以逐步交易生成的和弦序列的连贯性，以与其有趣性相对。实验是在18,005个旋律/和弦对的数据集上进行的。我们提出的模型在基于和弦/旋律谐波和和弦进展的六个不同客观指标中的五个中，五个不同的目标指标中的五个都优于最先进的系统Mtharmonizer。与100多名参与者的主观测试结果还显示了我们模型的优越性。
Coherence and interestingness are two criteria for evaluating the performance of melody harmonization, which aims to generate a chord progression from a symbolic melody. In this study, we apply the concept of orderless NADE, which takes the melody and its partially masked chord sequence as the input of the BiLSTM-based networks to learn the masked ground truth, to the training process. In addition, the class weights are used to compensate for some reasonable chord labels that are rarely seen in the training set. Consistent with the stochasticity in training, blocked Gibbs sampling with proper numbers of masking/generating loops is used in the inference phase to progressively trade the coherence of the generated chord sequence off against its interestingness. The experiments were conducted on a dataset of 18,005 melody/chord pairs. Our proposed model outperforms the state-of-the-art system MTHarmonizer in five of six different objective metrics based on chord/melody harmonicity and chord progression. The subjective test results with more than 100 participants also show the superiority of our model.
