6 accepted papers
Recent advances in coding agents suggest rapid progress toward autonomous software development, yet existing benchmarks primarily evaluate short-horizon behaviors such as localized code generation, scaffolded completion, or repository repair, leaving it unclear whether agents can sustain coherent re…
Note-level automatic singing transcription, involving the extraction of onset, offset, and pitch information from a singing voice, is a crucial process in the field of Music Information Retrieval (MIR), The recent advancements in deep learning models have led to significant progress in this field. H…
Creating a piece of music is difficult for people who have never been trained to compose. We present an automatic music generation system to lower the threshold of creating music. The system takes the user's humming as input and creates full music based on the humming melody. The system consists of…
This paper presents a novel system, named LingGe ("伶歌" in Chinese), to generate songs for ancient Chinese poems automatically. LingGe takes the poem as the lyric, composes music conditioned on the lyric, and finally outputs a full song including the singing and the accompaniment. It consists of four…
Evaluation metrics in machine learning are often hardly taken as loss functions, as they could be non-differentiable and non-decomposable, e.g., average precision and F1 score. This paper aims to address this problem by revisiting the surrogate loss learning, where a deep neural network is employed…
It is important for task-oriented dialogue systems to discover the dialogue structure (i.e. the general dialogue flow) from dialogue corpora automatically. Previous work models dialogue structure by extracting latent states for each utterance first and then calculating the transition probabilities a…