[MIREX] MIREX评测介绍

MIREX作为国际最权威音频检索评测大赛，竟然在百度上找不到任何介绍，只有几个与什么搜狗、腾讯获得什么成绩相关的检索内容，相比而言，TRECVID的内容收到重视多了...由于研究生阶段主要研究音频领域，需要对整个领域有一个大致的了解，感觉还是从MIREX入手比较合适，所以借此机会也与大家分享一记。

MIREX全称Music Information Retrieval Evaluation eXchange，即音乐信息检索评测，至于eXchange放在这不太清楚什么意思，或许与“交流”类似的含义吧，比赛由IMIRSEL承办，每个子项目由任务组织者设计并管理，这些任务组织者基本就是各个领域的领头专家。

【最普适的任务：音频分类任务】

Audio Classification (Train/Test) Tasks

包含了以下几个子任务：1. 美国流行音乐、拉丁音乐、韩国流行音乐的流派分类，2. 音乐情感分类、韩国流行音乐情感分类，3. 古典音乐的作曲家鉴别。这个任务做了很多年，感觉准确率到达一个瓶颈，不同任务的准确率基本上就稳定在0.65~0.8之间。

【音频相似度和检索】

Audio Music Similarity and Retrieval

音频相似度和检索，7000首30s的歌曲，返回一个稀疏矩阵，对每首歌返回相似度前100名的歌曲及相似度。看看应用场景吧 A music similarity system can help a music consumer find new music by finding the music that is most musically similar to specific query songs (or is nearest to songs that the consumer already likes). 其实不太清楚这种相似性度量是通过哪个衡量标准：节拍、速度、调式、节奏、旋律、和声、和弦，中的一个还是几个。

【符号旋律相似性】

Symbolic Melodic Similarity

计算旋律相似性，应该指的是通过MIDI的旋律符号，比较旋律的相似性。Retrieve the most similar items from a collection of symbolic pieces, given a symbolic query, and rank them by melodic similarity. There will be only 1 task this year which comprises a set of six "base" monophonic MIDI queries to be matched against a monophonic MIDI collection. 类似于以下结构信息

Example distance matrix 0.1
1    /path/to/audio/file/track1.wav
2    /path/to/audio/file/track2.wav
3    /path/to/audio/file/track3.wav
4    /path/to/audio/file/track4.wav
5    /path/to/audio/file/track5.wav
Q/R   1        2        3        4        5
1     0.00000  1.24100  0.2e-4   0.42559  0.21313
3     50.2e-4  0.62640  0.00000  0.38000  0.15152

Format
评价标准如下

The following evaluation metrics will be computed for each submission: 1. Total number of covers identified in top 10；2. Mean number of covers identified in top 10 (average performance)；3. Mean (arithmetic) of Avg. Precisions；4. Mean rank of first correctly identified cover。话说1和2是一个意思吧，MAP在10时的值；3是平均准确率，应该还跟内部位置有关；4是第一个识别正确的cover song的排名

【重复主题章节的发现】

Discovery of Repeated Themes & Sections

Algorithms that take a single piece of music as input, and output a list of patterns repeated within that piece. Also known as intra-opus discovery. 输入：一段音乐；输出：在这段音乐里重复出现的模式。那么所谓的模式是什么呢？For the purposes of this task, a pattern is defined as a set of ontime-pitch pairs that occurs at least twice (i.e., is repeated at least once) in a piece of music. The second, third, etc. occurrences of the pattern will likely be shifted in time and perhaps also transposed, relative to the first occurrence. Ideally an algorithm would be able to discover all exact and inexact occurrences of a pattern within a piece, so in evaluating this task we are interested in both (1) whether an algorithm can discover one occurrence, up to time shift and transposition, and (2) to what extent it can find all occurrences. It has been pointed out by Lartillot and Toiviainen (2007) among others that as well as ontime-pitch patterns, there are various types of repeating pattern (e.g., ontimes alone, duration, contour, harmony, etc.). For the sake of simplicity, the current task is restricted to ontime-pitch pairs.

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Audio Melody Extraction

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Query by Singing/Humming

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Audio Chord Estimation

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Singing Voice Separation

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Audio Fingerprinting