SongRewriter: A Chinese Song Rewriting System with Controllable Content and Rhyme Scheme

Although lyrics generation has achieved significant progress in recent years, it has limited practical applications because the generated lyrics cannot be performed without composing compatible melodies. In this work, we bridge this practical gap by proposing a song rewriting system which rewrites the lyrics of an existing song such that the generated lyrics are compatible with the rhythm of the existing melody and thus singable. In particular, we propose SongRewriter, a controllable Chinese lyric generation and editing system which assists users without prior knowledge of melody composition. The system is trained by a randomized multi-level masking strategy which produces a unified model for generating entirely new lyrics or editing a few fragments. To improve the controllabiliy of the generation process, we further incorporate a keyword prompt to control the lexical choices of the content and propose novel decoding constraints and a vowel modeling task to enable flexible end and internal rhyme schemes. While prior rhyming metrics are mainly for rap lyrics, we propose three novel rhyming evaluation metrics for song lyrics. Both automatic and human evaluations show that the proposed model performs better than the state-of-the-art models in both contents and rhyming quality. Our code and models implemented in MindSpore Lite tool will be available

Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics

Lyrics generation is a well-known application in natural language generation research, with several previous studies focusing on generating accurate lyrics using precise control such as keywords, rhymes, etc. However, lyrics imitation, which involves writing new lyrics by imitating the style and content of the source lyrics, remains a challenging task due to the lack of a parallel corpus. In this paper, we introduce \textbf{\textit{Sudowoodo}}, a Chinese lyrics imitation system that can generate new lyrics based on the text of source lyrics. To address the issue of lacking a parallel training corpus for lyrics imitation, we propose a novel framework to construct a parallel corpus based on a keyword-based lyrics model from source lyrics. Then the pairs \textit{(new lyrics, source lyrics)} are used to train the lyrics imitation model. During the inference process, we utilize a post-processing module to filter and rank the generated lyrics, selecting the highest-quality ones. We incorporated audio information and aligned the lyrics with the audio to form the songs as a bonus. The human evaluation results show that our framework can perform better lyric imitation. Meanwhile, the \textit{Sudowoodo} system and demo video of the system is available at \href{https://Sudowoodo.apps-hp.danlu.netease.com/}{Sudowoodo} and \href{https://youtu.be/u5BBT_j1L5M}{https://youtu.be/u5BBT\_j1L5M}.Comment: 7 pages,3 figures, submit to emnlp 2023 demo trac

Organising music for movies

Purpose - The purpose of this paper is to examine and discuss the classification of commercial popular music when large digital collections are organised for use in films. Design/methodology/approach - A range of systems are investigated and their organization is discussed, focusing on an analysis of the metadata used by the systems and choices given to the end-user to construct a query. The indexing of the music is compared to a checklist of music facets which has been derived from recent musicological literature on semiotic analysis of popular music. These facets include aspects of communication, cultural and musical expression, codes and competences. Findings -In addition to bibliographic detail, descriptive metadata is used to organise music in these systems. Genre, subject and mood are used widely; some musical facets also appear. The extent to which attempts are being made to reflect these facets in the organization of these systems is discussed. A number of recommendations are made which may help to improve this process. Originality/value - This paper discusses an area of creative music search which has not previously been investigated in any depth and makes recommendations based on findings and the literature which may be used in the development of commercial systems as well as making a contribution to the literature

Analysing the Creative Process through a Modelling of Tools and Methods for Composition in Hans Tutschku’s Entwurzelt

The analysis of the creative processes involved in electroacoustic music may to a large extent rely on the thorough study of the technological tools used for the realisation of a musical work, both on the composition and on the performance sides. Understanding the behaviour and potential range of aesthetic results of such tools enables the musicologist to approach the studied work much beyond its final form, as presented on tape or as performed on a particular occasion: gaining knowledge on a wider technological context leads to considering the actual artistic decisions in the perspective of the potential outcomes that the composer and performer could face but not necessarily adopt. Hence, analysing an electroacoustic work on the basis of the study of its creative context, technological tools and compositional methods may constitute a useful approach to a better understanding of its related creative processes. However, the implementation of such an approach, mainly based on the hardware or software elements used during the creation of a given work, is not straightforward. First, it implies that the considered technologies are still in use and have not be come irreversibly obsolete. In this matter, new performances of a work are good opportunities for such investigations, as they often provide a technical update and require a deep understanding of the composer’s intentions. The musicologist also needs to have access to the resources, which may not be available without a direct contact with the composer. Assuming these conditions are reached,the musicological and organological studies can encounter another issue, particularly in the digital domain: the sources are not always presented under forms that are directly readable by the analyst, for instance with a specific programming language. Despite all these possible difficulties, many cases of technological tools lean themselves to an in-depth investigation, leading to relevant conclusions on some of the creative processes appearing in the field of electroacoustic music. In the context of a common session of several analytical approaches to a same electroacoustic piece, Hans Tutschku’s Entwurzelt for six singers and electronics (2012), this article focuses on the investigation and modelling of tools and methods of the compositional stage of the realisation of the work. During a performance of Entwurzelt, the electronic materials are simply triggered as events by one of the singers, without further interactivity–thus, the essential part of the research on the electroacoustic realisation aims at exploring the processes used during the compositional stage itself. As the electronics are used as an extension of the live vocal expression by the means of harmonic amplification and complex texturing, the tools for generation and processing of both symbolic representations and audio explored. Since the software tools that constitute the primary sources for our research were not directly designed to be used beyond their creative purposes, this talk presents software modelling implemented by the two authors to demonstrate the technological context in which Tutschku could compose Entwurzelt, emphasizing his creative methods and the decisions he could make upon a wider range of possible materials and processing techniques

Automatic Time Signature Determination for New Scores Using Lyrics for Latent Rhythmic Structure

There has recently been a sharp increase in interest in Artificial Intelligence-Generated Content (AIGC). Despite this, musical components such as time signatures have not been studied sufficiently to form an algorithmic determination approach for new compositions, especially lyrical songs. This is likely because of the neglect of musical details, which is critical for constructing a robust framework. Specifically, time signatures establish the fundamental rhythmic structure for almost all aspects of a song, including the phrases and notes. In this paper, we propose a novel approach that only uses lyrics as input to automatically generate a fitting time signature for lyrical songs and uncover the latent rhythmic structure utilizing explainable machine learning models. In particular, we devise multiple methods that are associated with discovering lyrical patterns and creating new features that simultaneously contain lyrical, rhythmic, and statistical information. In this approach, the best of our experimental results reveal a 97.6% F1 score and a 0.996 Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) score. In conclusion, our research directly generates time signatures from lyrics automatically for new scores utilizing machine learning, which is an innovative idea that approaches an understudied component of musicology and therefore contributes significantly to the future of Artificial Intelligence (AI) music generation.Comment: Accepted by 2023 IEEE International Conference on Big Data (IEEE BigData 2023

Usability and expressiveness in database keyword search : bridging the gap

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