英语翻译Music transcription could be defined as an act oflistening to a piece of music and writing down musicnotation for the piece.Transcription of polyphonicmusic (polyphonic pitch recognition) converts anacoustical waveform into a parametric r

英语翻译Music transcription could be defined as an act oflistening to a piece of music and writing down musicnotation for the piece.Transcription of polyphonicmusic (polyphonic pitch recognition) converts anacoustical waveform into a parametric r
英语翻译
Music transcription could be defined as an act of
listening to a piece of music and writing down music
notation for the piece.Transcription of polyphonic
music (polyphonic pitch recognition) converts an
acoustical waveform into a parametric representation,
where notes,their pitches,starting times and
durations are extracted from the signal.Transcription
is a difficult cognitive task and is not inherent in
human perception of music,although it can be
learned.It is also a very difficult problem for current
computer systems.Separating notes from a mixture of
other sounds,which may include notes played by the
same or different instruments or simply background
noise requires robust algorithms with performance
that should degrade gracefully when noise increases.
In recent years,several transcription systems have
been developed.Some of them are targeted to
transcription of music played on specific instruments
[3-5],while others are general transcription systems
[1-2].All of them share several common
characteristics.In the beginning,they calculate a
time-frequency representation of the musical signal.
In the next step,the time-frequency representation is
refined by locating partials in the signal.To track
partials,most systems use ad hoc algorithms such as
peak picking and peak connecting.Partial tracks are
then grouped into notes with different algorithms
relying on cues such as common onset time and
harmonicity.Some authors use templates of
instrument tones in this process [1,3],as well as
higher-level knowledge of music,such as
probabilities of chord transitions [2].
Recognizing notes in a signal is a typical pattern
recognition task and we were surprised that few
current systems use machine learning algorithms in the transcription process.Therefore,our motivation
was to develop a transcription system based on neural
networks,which have proved to be useful in a variety
of pattern recognition tasks.We tried to avoid explicit
symbolic algorithms,and instead used connectionist
approaches in different parts of our system.
The name of our transcription system is SONIC.
Transcription is a difficult task,so we put one major
constraint on the system:it only transcribes piano
music,so piano should be the only instrument in the
analyzed musical signal.We didn't make any other
assumptions about the signal,such as maximal
polyphony,minimal note length,style of transcribed
music or the type of piano used.The system takes an
acoustical waveform of a piano recording (44.1 kHz
sampling rate,16 bit resolution) as its input.Stereo
recordings are converted to mono.The output of the
system is a MIDI file containing the transcription.
Notes,their starting times,durations and loudness' are
extracted from the signal.
额 不要哪种GOOGLE啊 百度啊 上的翻译 哪些网站的翻译很不精准 最好能翻的精准点。
WOSHIWANGZHIQI在哪里找的翻译啊

英语翻译Music transcription could be defined as an act oflistening to a piece of music and writing down musicnotation for the piece.Transcription of polyphonicmusic (polyphonic pitch recognition) converts anacoustical waveform into a parametric r
音乐转录可以被定义为行为
听一首乐曲,并写下音乐
符号的一块.转录的和弦
音乐（和弦音调识别）转换为
声学参数波形为代表,
这些纸币,他们的球场,开始时间和
工期提取信号.转录
认知是一个困难的任务,不是固有的
人类感知音乐,尽管它可以
教训.这也是一个十分棘手的问题当前
计算机系统.从混合物分离笔记
其他声音可能包括票据的作用
相同或不同的工具或简单的背景
噪声需要与性能强大的算法
应适度地降低噪音增大的时候.
近年来,一些转录系统
被开发.其中一些是针对
转录具体乐器演奏音乐
[3-5],而另一些是一般转录系统
[1-2].他们都具有一些共同
特征.一开始,他们计算
时频信号表示的音乐.
在下一步的时频表示是
精致的定位信号陪音.要跟踪
陪音,大多数系统使用特设算法,如
采摘高峰期和高峰期连接.部分轨道
然后分为不同的算法注意到
依赖于线索,如共同起效时间和
调和.有些作者使用模板
文书铃声在这个过程中[1,3],以及
较高的音乐,如知识水平
和弦转换的概率[2].
在信号确认债券是典型模式
识别任务,我们感到惊讶的是少数
目前的系统中使用的机器学习算法的转录过程.因此,我们的动力
是开发一种转录系统的神经基础
网络,这已证明在各种有用
模式识别任务.我们试图避免明确
象征性的算法,而是使用了联结
方法在我们系统的不同部分.
我们的转录系统的名称是索尼克.
转录是一项艰巨的任务,因此我们提出的一个主要
在系统上的约束：只转录钢琴
音乐,使钢琴应该是唯一的工具
分析音乐信号.我们没有任何其他
假设有关,如最大信号,
复音,最小音符长度,样式的转录
音乐或钢琴的类型.该系统采用一
声学波形的钢琴录音（44.1千赫
采样率,16位分辨率）作为它的输入.立体声
录音转换为单声道.输出
系统是一个MIDI文件包含转录.
注意到,他们的出发时间,期限和响度'是
从信号中提取.