歌词到歌曲转换系统的实现

将文语转换技术与语音修改技术相结合,实现了一个歌词到歌曲的转换系统。首先利用一个文语转换系统将输入的歌词转换为语音,同时从歌曲的MIDI文件中提取歌曲的旋律参数,最后通过旋律控制模型对语音信号的声学特征进行修改,实现由歌词到歌曲的转换。实验结果表明,系统合成的歌曲达到了3.29的平均MOS得分。     

让歌词为你的歌曲添色

使用Winamp收听MP3音乐是一种时尚，很多流行歌曲歌词写得很美，那我们参不能在用Winamp欣赏歌曲的同时，能够查看到美丽的歌词？答案是肯定的，有了歌词秀，我们不仅能够在收听歌曲的同时欣赏到歌词，还可以自己编写歌词，并对它们进行同步控制呢？[编者按]     

音乐和歌词融合的歌曲情感分类研究

为更好地对歌词进行情感分类,提出一种改进的基于类间差别的CHI特征选择方法。该方法可单独用于歌词情感特征提取,将选取的特征应用于支持向量机分类器中,融合音频特征与利用改进CHI方法选择的歌词特征对歌曲进行情感分类。实验结果表明,融合后的特征可以取得比任何单一种类特征更好的分类效果。     

歌词同步调整千千有招

我们在使用《千千静听》播放器欣赏歌曲时,如果网络通畅,该软件就会自动从网络下载对应歌词。但这样下载到的歌词有时会存在与歌曲播放不同步的情况,用每次0．5秒的选项来调整费时费力。其实,我们还可以使用另一种轻松的方法对歌词进行调整。右键单击“歌词秀”窗口,在弹出的菜单中依次点击“调整歌词／鼠     

卡拉OK，想唱就唱

在电脑上唱卡拉OK最大问题就是歌曲伴奏,其实,千千静听就可以解决唱卡拉OK时的歌曲伴奏问题,利用千千静听的歌词显示功能,我们可以一边看着歌词,一边尽情高歌,好像没有比这更爽的事情了。下边,就给大家介绍一下如何在电脑上利用千千静听来唱卡拉OK。先从http://work.newhua.com/cfan/200813/defx.rar下载插件,将其中的文     

可编辑歌词的MP3播放软件MP3Word

不好意思,本人虽然喜欢一边工作一边欣赏音乐,不过有些歌曲的歌词却始终记不住,因而在欣赏那些不能显示歌词的ＭＰ３文件时总会闹些不大不小的笑话。为解决这一问题,本人一直试图找一个可以显示歌词的ＭＰ３播放软件,ＭＰ３ Ｗｏｒｄ的出现终于让我如愿以偿。 ＭＰ３ Ｗｏｒｄ是一个具有歌词显示功能的 ＭＰ３播放软件．我们可利用它将歌词嵌入到ＭＰ３文件中,然后就可以一边看着歌词,一边欣赏忧美的ＭＰ３歌曲,再也不必为记不住歌词而烦恼了！     

基于情感向量空间模型的歌曲情感标签预测模型

音乐的情感标签预测对音乐的情感分析有着重要的意义。该文提出了一种基于情感向量空间模型的歌曲情感标签预测算法,首先,提取歌词中的情感特征词构建情感空间向量模型,然后利用SVM分类器对已知情感标签的音乐进行训练,通过分类技术找到与待预测歌曲情感主类一致的歌曲集合,最后,通过歌词的情感相似度计算找到最邻近的k首歌曲,将其标签推荐给待预测歌曲。实验发现本文提出的情感向量空间模型和“情感词—情感标签”共现的特征降维方法比传统的文本特征向量模型能够更好地提高歌曲情感分类准确率。同时,在分类基础上进行的情感标签预测方法可以有效地防止音乐“主类情感漂移”,比最近邻居方法达到更好的标签预测准确率。     

歌曲歌词来速配

很多朋友在用MP3随身听欣赏歌曲时,喜欢看着歌词哼唱,这就需要在把歌曲复制进随身听中时,要连歌词一起复制。不用在“我的电脑”中寻觅歌词,利用千千静听,可以使歌曲歌词速配到随身听中。     

Windows Media Player 8.0应用技巧两则

1.为歌曲添加歌词 首先在播放列表中找到要添加歌词的歌曲,用鼠标右键单击该文件,在弹出的快捷菜单中选择“属性”,单击“歌词”选项卡,接下来就可以在“歌词”文本框中输入或编辑该歌曲的歌词了。 要在播放该歌曲的同时查看歌词,可在“查看”菜单上指向“正在播放工     

五步!打造免费的卡拉OK点播台

想要在家唱卡拉OK,伴奏歌曲就要自己来准备了,一方面我们可以从网上搜索下载别人制作好的卡拉OK伴奏歌曲,另一方面也可以通过软件自己来制作,卡拉OK制作点歌台2006(下载地址:http://www.onlinedown.net/soft/17267.htm)就是不错的一个工具。第一步:启动软件,从资源管理器中,将需要制作卡拉O K的M P3歌曲拖放到软件左侧的“收藏室”中。第二步:选中“收藏室”中的歌曲,点击“媒体制作→媒体信息编辑”打开媒体编辑窗口,在“歌词”栏把准备好的歌词粘贴进去。对歌词文字进行编辑修改后,依次点击“保存→开始制作”按钮进行下一步制作。第…     

Multimodal mood classification of Hindi and Western songs

Music mood classification is one of the most interesting research areas in music information retrieval, and it has many real-world applications. Many experiments have been performed in mood classification or emotion recognition of Western music; however, research on mood classification of Indian music is still at initial stage due to scarcity of digitalized resources. In the present work, a mood taxonomy is proposed for Hindi and Western songs; both audio and lyrics were annotated using the proposed mood taxonomy. Differences in mood were observed during the annotation of the audio and lyrics for Hindi songs only. The detailed studies on mood classification of Hindi and Western music are presented for the requirement of the recommendation system. LibSVM and Feed-forward neural networks have been used to develop mood classification systems based on audio, lyrics, and a combination of them. The multimodal mood classification systems using Feed-forward neural networks for Hindi and Western songs obtained the maximum F-measures of 0.751 and 0.835, respectively.     

结合TF-IDF的歌曲情感多标记分类

提出一种结合词频-逆向文件频率(TF-IDF)规则与多标记分类的歌曲情感分析方法。对歌曲中基于声学特征的音乐内容,用带向量夹角的多标记k近邻算法进行分类,将TF-IDF规则用于歌词内容,以计算歌词情感分数,并将其作为情感特征。采用该方法对歌词内容分类错误的类别标记进行修正。选用396首英文歌曲对该算法进行测试,结果表明,与其他方法相比,该方法能使分类精确度从69%提高到74%。     

LyricAlly: Automatic Synchronization of Textual Lyrics to Acoustic Music Signals

We present LyricAlly, a prototype that automatically aligns acoustic musical signals with their corresponding textual lyrics, in a manner similar to manually-aligned karaoke. We tackle this problem based on a multimodal approach, using an appropriate pairing of audio and text processing to create the resulting prototype. LyricAlly's acoustic signal processing uses standard audio features but constrained and informed by the musical nature of the signal. The resulting detected hierarchical rhythm structure is utilized in singing voice detection and chorus detection to produce results of higher accuracy and lower computational costs than their respective baselines. Text processing is employed to approximate the length of the sung passages from the lyrics. Results show an average error of less than one bar for per-line alignment of the lyrics on a test bed of 20 songs (sampled from CD audio and carefully selected for variety). We perform a comprehensive set of system-wide and per-component tests and discuss their results. We conclude by outlining steps for further development.     

基于序列模型的音乐词曲匹配度智能评估算法

情感匹配模型是一种常用于评价词曲匹配程度的方法;然而,单纯地依靠情感匹配模型无法对评价词曲匹配度进行准确的评价。为改善此问题,提出了基于序列模型的词曲匹配度智能评估算法,其综合考虑词曲情感和词曲间节奏关系以给出一个更加准确的词曲评估方法。基于公开词曲同步数据集,构建了音乐情感和节奏正反例模型,并基于此模型将音乐切分成片段;进一步,将歌词和旋律片段分别通过歌词编码器和旋律编码器进行编码,并将编码后具有上下语境的歌词特征和旋律特征输入词曲匹配解码器,解析词曲间特征关系,判断词曲片段匹配程度。仿真结果表明:基于序列模型的词曲匹配度智能评估算法,相对于单纯的情感匹配模型,能够更精确地评价词曲匹配程度,验证了本文提出算法的有效性。     

基于FLASH探究MTV制作的关键技术

阐述能成功导入Flash中的MP3音乐必需是标准的MP3格式和将非标准MP3格式转换设置成标准MP3格式的方法,然后介绍用Flash制作MTV作品时实现词曲同步的科学方法.     

A face robot for autonomous simplified musical notation reading and singing

This research is aimed to devise an anthropomorphic robotic head with a human-like face and a sheet of artificial skin that can read a randomly composed simplified musical notation and sing the corresponding content of the song once. The face robot is composed of an artificial facial skin that can express a number of facial expressions via motions driven by internal servo motors. Two cameras, each of them installed inside each eyeball of the face, provide vision capability for reading simplified musical notations. Computer vision techniques are subsequently used to interpret simplified musical notations and lyrics of their corresponding songs. Voice synthesis techniques are implemented to enable the face robot to sing songs by enunciating synthesized sounds. Mouth patterns of the face robot will be automatically changed to match the emotions corresponding to the lyrics of the songs. The experiments show that the face robot can successfully read and then accurately sing a song which is assigned discriminately.     

基于Python 的网易民谣歌词数据分析

随着大数据时代下的数据来源和获取日趋重要，基于Python 的爬虫技术已成为获取数据工具的研究热点之 一。本文应用Python 爬虫关键技术对网易云季度歌词以及歌词相关文章的信息采集和汇总，并对其汇总后的网易歌词利用 Python 类库和数据分析技术对歌手情绪、词频统计、词云可视化以及歌手对时光和城市偏爱程度等进行数据分析。研究结果 表明，当下民谣歌手情绪稳定且有激情，能通过歌曲表达其正面情感，以及对当下时光与繁华城市的喜好。     

Continuous query processing over music streams based on approximate matching mechanisms

It is foreseen that more and more music objects in symbolic format and multimedia objects, such as audio, video, or lyrics, integrated with symbolic music representation (SMR) will be published and broadcasted via the Internet. The SMRs of the flowing songs or multimedia objects will form a music stream. Many interesting applications based on music streams, such as interactive music tutorials, distance music education, and similar theme searching, make the research of content-based retrieval over music streams much important. We consider multiple queries with error tolerances over music streams and address the issue of approximate matching in this environment. We propose a novel approach to continuously process multiple queries over the music streams for finding all the music segments that are similar to the queries. Our approach is based on the concept of n-grams, and two mechanisms are designed to reduce the heavy computation of approximate matching. One mechanism uses the clustering of query n-grams to prune the query n-grams that are irrelevant to the incoming data n-gram. The other mechanism records the data n-gram that matches a query n-gram as a partial answer and incrementally merges the partial answers of the same query. We implement a prototype system for experiments in which songs in the MIDI format are continuously broadcasted, and the user can specify musical segments as queries to monitor the music streams. Experiment results show the effectiveness and efficiency of the proposed approach.     

中文音乐情感词典构建及情感分类方法研究

作为仅次于及时通信和搜索引擎的中国互联网网民第三大应用,网络音乐及其应用技术受到业界学者的青睐。音乐作为人类最重要的交流媒介,携带着丰富的情感信息,计算机音乐情感分析更是得到人机情感交互技术领域的高度重视。在基于歌词文本的音乐情感分析过程中,一部合理的音乐领域情感词典,将提供更加细致、更加准确的分析结果。以改进后的Hevner情感环模型为基础,借助HowNet所提供的语义资源和从网络爬取的歌词文本语料库,构建了一部树形层次结构的音乐领域中文情感词典,并利用LRC歌词携带的时间标签获取歌曲的语速信息,实现了基于情感向量空间模型和情感词典的歌词情感分类。实验表明与人工构建的情感词典相比,所构建的情感词典更适用于音乐领域。     

Mining transposed motifs in music

The discovery of frequent musical patterns (motifs) is a relevant problem in musicology. This paper introduces an unsupervised algorithm to address this problem in symbolically-represented musical melodies. Our algorithm is able to identify transposed patterns including exact matchings, i.e., null transpositions. We have tested our algorithm on a corpus of songs and the results suggest that our approach is promising, specially when dealing with songs that include non-exact repetitions.