Difference between revisions of "2011:Audio Music Similarity and Retrieval Results"

Latest revision as of 22:29, 21 October 2011

Introduction

These are the results for the 2011 running of the Audio Music Similarity and Retrieval task set. For background information about this task set please refer to the Audio Music Similarity and Retrieval page.

Each system was given 7000 songs chosen from IMIRSEL's "uspop", "uscrap" and "american" "classical" and "sundry" collections. Each system then returned a 7000x7000 distance matrix. 100 songs were randomly selected from the 10 genre groups (10 per genre) as queries and the first 5 most highly ranked songs out of the 7000 were extracted for each query (after filtering out the query itself, returned results from the same artist were also omitted). Then, for each query, the returned results (candidates) from all participants were grouped and were evaluated by human graders using the Evalutron 6000 grading system. Each individual query/candidate set was evaluated by a single grader. For each query/candidate pair, graders provided two scores. Graders were asked to provide 1 categorical BROAD score with 3 categories: NS,SS,VS as explained below, and one FINE score (in the range from 0 to 100). A description and analysis is provided below.

The systems read in 30 second audio clips as their raw data. The same 30 second clips were used in the grading stage.

General Legend

Team ID

Sub code	Submission name	Abstract	Contributors
CTCP1	IrcamSimilarity_1	PDF	Christophe Charbuillet, Geoffroy Peeters, Frédéric Cornu, Damien Tardieu
CTCP2	IrcamSimilarity_2	PDF	Christophe Charbuillet, Geoffroy Peeters, Frédéric Cornu, Damien Tardieu
CTCP3	IrcamSimilarity_3	PDF	Christophe Charbuillet, Geoffroy Peeters, Frédéric Cornu, Damien Tardieu
DM2	AMS_soton1	PDF	Franz de Leon, Kirk Martinez
DM3	AMS_soton2	PDF	Franz de Leon, Kirk Martinez
GKC1	RHYTHM_SIM	PDF	Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
HKHLL1	MARG_SIM1	PDF	Byeong-jun Han, Kyogu Lee, Ziwon Hyung, Hyunwoo Kim, Sheayun Lee
ML1	ML1	PDF	Brian McFee, Gert Lanckriet
ML2	ML2	PDF	Brian McFee, Gert Lanckriet
ML3	ML3	PDF	Brian McFee, Gert Lanckriet
PS1	PS09	PDF	Dominik Schnitzer, Tim Pohle
SSKS3	cbmr_sim	PDF	Klaus Seyerlehner, Markus Schedl, Peter Knees, Reinhard Sonnleitner
SSPK2	cbmr_sim_2010	PDF	Klaus Seyerlehner, Markus Schedl, Peter Knees, Tim Pohle
STBD1	AMS2011_vario	PDF	Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
STBD2	AMS2011_multi	PDF	Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
STBD3	AMS2011_f0delta	PDF	Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
YL1	SC Learning	PDF	Yin-Tzu Lin, Wen-Huang Cheng, Ja-Ling Wu
ZYC2	SUMMs for AMS	PDF	Dongying Zhang, Deshun Yang, Xiaoou Chen

Broad Categories

NS = Not Similar
SS = Somewhat Similar
VS = Very Similar

Understanding Summary Measures

Fine = Has a range from 0 (failure) to 100 (perfection).
Broad = Has a range from 0 (failure) to 2 (perfection) as each query/candidate pair is scored with either NS=0, SS=1 or VS=2.

Human Evaluation

Overall Summary Results

Measure	CTCP1	CTCP2	CTCP3	DM2	DM3	GKC1	HKHLL1	ML1	ML2	ML3	PS1	SSKS3	SSPK2	STBD1	STBD2	STBD3	YL1	ZYC2
Average Fine Score	57.268	58.586	56.208	50.492	50.348	31.844	42.188	47.784	47.304	47.782	57.700	58.128	58.642	33.906	30.562	30.386	42.366	50.042
Average Cat Score	1.260	1.296	1.222	1.088	1.078	0.594	0.874	0.990	0.988	1.008	1.272	1.292	1.312	0.636	0.578	0.574	0.886	1.078

download these results as csv

Note:RZ1 is the random result for comparing purpose.

Friedman's Tests

Friedman's Test (FINE Scores)

The Friedman test was run in MATLAB against the Fine summary data over the 100 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);

TeamID	TeamID	Lowerbound	Mean	Upperbound	Significance
SSPK2	CTCP2	-2.005	0.620	3.245	FALSE
SSPK2	SSKS3	-2.120	0.505	3.130	FALSE
SSPK2	PS1	-2.430	0.195	2.820	FALSE
SSPK2	CTCP1	-1.510	1.115	3.740	FALSE
SSPK2	CTCP3	-1.145	1.480	4.105	FALSE
SSPK2	DM2	0.820	3.445	6.070	TRUE
SSPK2	DM3	0.840	3.465	6.090	TRUE
SSPK2	ZYC2	0.620	3.245	5.870	TRUE
SSPK2	ML1	1.850	4.475	7.100	TRUE
SSPK2	ML3	2.530	5.155	7.780	TRUE
SSPK2	ML2	2.435	5.060	7.685	TRUE
SSPK2	YL1	3.360	5.985	8.610	TRUE
SSPK2	HKHLL1	4.085	6.710	9.335	TRUE
SSPK2	STBD1	5.745	8.370	10.995	TRUE
SSPK2	GKC1	5.880	8.505	11.130	TRUE
SSPK2	STBD2	6.435	9.060	11.685	TRUE
SSPK2	STBD3	6.575	9.200	11.825	TRUE
CTCP2	SSKS3	-2.740	-0.115	2.510	FALSE
CTCP2	PS1	-3.050	-0.425	2.200	FALSE
CTCP2	CTCP1	-2.130	0.495	3.120	FALSE
CTCP2	CTCP3	-1.765	0.860	3.485	FALSE
CTCP2	DM2	0.200	2.825	5.450	TRUE
CTCP2	DM3	0.220	2.845	5.470	TRUE
CTCP2	ZYC2	0.000	2.625	5.250	TRUE
CTCP2	ML1	1.230	3.855	6.480	TRUE
CTCP2	ML3	1.910	4.535	7.160	TRUE
CTCP2	ML2	1.815	4.440	7.065	TRUE
CTCP2	YL1	2.740	5.365	7.990	TRUE
CTCP2	HKHLL1	3.465	6.090	8.715	TRUE
CTCP2	STBD1	5.125	7.750	10.375	TRUE
CTCP2	GKC1	5.260	7.885	10.510	TRUE
CTCP2	STBD2	5.815	8.440	11.065	TRUE
CTCP2	STBD3	5.955	8.580	11.205	TRUE
SSKS3	PS1	-2.935	-0.310	2.315	FALSE
SSKS3	CTCP1	-2.015	0.610	3.235	FALSE
SSKS3	CTCP3	-1.650	0.975	3.600	FALSE
SSKS3	DM2	0.315	2.940	5.565	TRUE
SSKS3	DM3	0.335	2.960	5.585	TRUE
SSKS3	ZYC2	0.115	2.740	5.365	TRUE
SSKS3	ML1	1.345	3.970	6.595	TRUE
SSKS3	ML3	2.025	4.650	7.275	TRUE
SSKS3	ML2	1.930	4.555	7.180	TRUE
SSKS3	YL1	2.855	5.480	8.105	TRUE
SSKS3	HKHLL1	3.580	6.205	8.830	TRUE
SSKS3	STBD1	5.240	7.865	10.490	TRUE
SSKS3	GKC1	5.375	8.000	10.625	TRUE
SSKS3	STBD2	5.930	8.555	11.180	TRUE
SSKS3	STBD3	6.070	8.695	11.320	TRUE
PS1	CTCP1	-1.705	0.920	3.545	FALSE
PS1	CTCP3	-1.340	1.285	3.910	FALSE
PS1	DM2	0.625	3.250	5.875	TRUE
PS1	DM3	0.645	3.270	5.895	TRUE
PS1	ZYC2	0.425	3.050	5.675	TRUE
PS1	ML1	1.655	4.280	6.905	TRUE
PS1	ML3	2.335	4.960	7.585	TRUE
PS1	ML2	2.240	4.865	7.490	TRUE
PS1	YL1	3.165	5.790	8.415	TRUE
PS1	HKHLL1	3.890	6.515	9.140	TRUE
PS1	STBD1	5.550	8.175	10.800	TRUE
PS1	GKC1	5.685	8.310	10.935	TRUE
PS1	STBD2	6.240	8.865	11.490	TRUE
PS1	STBD3	6.380	9.005	11.630	TRUE
CTCP1	CTCP3	-2.260	0.365	2.990	FALSE
CTCP1	DM2	-0.295	2.330	4.955	FALSE
CTCP1	DM3	-0.275	2.350	4.975	FALSE
CTCP1	ZYC2	-0.495	2.130	4.755	FALSE
CTCP1	ML1	0.735	3.360	5.985	TRUE
CTCP1	ML3	1.415	4.040	6.665	TRUE
CTCP1	ML2	1.320	3.945	6.570	TRUE
CTCP1	YL1	2.245	4.870	7.495	TRUE
CTCP1	HKHLL1	2.970	5.595	8.220	TRUE
CTCP1	STBD1	4.630	7.255	9.880	TRUE
CTCP1	GKC1	4.765	7.390	10.015	TRUE
CTCP1	STBD2	5.320	7.945	10.570	TRUE
CTCP1	STBD3	5.460	8.085	10.710	TRUE
CTCP3	DM2	-0.660	1.965	4.590	FALSE
CTCP3	DM3	-0.640	1.985	4.610	FALSE
CTCP3	ZYC2	-0.860	1.765	4.390	FALSE
CTCP3	ML1	0.370	2.995	5.620	TRUE
CTCP3	ML3	1.050	3.675	6.300	TRUE
CTCP3	ML2	0.955	3.580	6.205	TRUE
CTCP3	YL1	1.880	4.505	7.130	TRUE
CTCP3	HKHLL1	2.605	5.230	7.855	TRUE
CTCP3	STBD1	4.265	6.890	9.515	TRUE
CTCP3	GKC1	4.400	7.025	9.650	TRUE
CTCP3	STBD2	4.955	7.580	10.205	TRUE
CTCP3	STBD3	5.095	7.720	10.345	TRUE
DM2	DM3	-2.605	0.020	2.645	FALSE
DM2	ZYC2	-2.825	-0.200	2.425	FALSE
DM2	ML1	-1.595	1.030	3.655	FALSE
DM2	ML3	-0.915	1.710	4.335	FALSE
DM2	ML2	-1.010	1.615	4.240	FALSE
DM2	YL1	-0.085	2.540	5.165	FALSE
DM2	HKHLL1	0.640	3.265	5.890	TRUE
DM2	STBD1	2.300	4.925	7.550	TRUE
DM2	GKC1	2.435	5.060	7.685	TRUE
DM2	STBD2	2.990	5.615	8.240	TRUE
DM2	STBD3	3.130	5.755	8.380	TRUE
DM3	ZYC2	-2.845	-0.220	2.405	FALSE
DM3	ML1	-1.615	1.010	3.635	FALSE
DM3	ML3	-0.935	1.690	4.315	FALSE
DM3	ML2	-1.030	1.595	4.220	FALSE
DM3	YL1	-0.105	2.520	5.145	FALSE
DM3	HKHLL1	0.620	3.245	5.870	TRUE
DM3	STBD1	2.280	4.905	7.530	TRUE
DM3	GKC1	2.415	5.040	7.665	TRUE
DM3	STBD2	2.970	5.595	8.220	TRUE
DM3	STBD3	3.110	5.735	8.360	TRUE
ZYC2	ML1	-1.395	1.230	3.855	FALSE
ZYC2	ML3	-0.715	1.910	4.535	FALSE
ZYC2	ML2	-0.810	1.815	4.440	FALSE
ZYC2	YL1	0.115	2.740	5.365	TRUE
ZYC2	HKHLL1	0.840	3.465	6.090	TRUE
ZYC2	STBD1	2.500	5.125	7.750	TRUE
ZYC2	GKC1	2.635	5.260	7.885	TRUE
ZYC2	STBD2	3.190	5.815	8.440	TRUE
ZYC2	STBD3	3.330	5.955	8.580	TRUE
ML1	ML3	-1.945	0.680	3.305	FALSE
ML1	ML2	-2.040	0.585	3.210	FALSE
ML1	YL1	-1.115	1.510	4.135	FALSE
ML1	HKHLL1	-0.390	2.235	4.860	FALSE
ML1	STBD1	1.270	3.895	6.520	TRUE
ML1	GKC1	1.405	4.030	6.655	TRUE
ML1	STBD2	1.960	4.585	7.210	TRUE
ML1	STBD3	2.100	4.725	7.350	TRUE
ML3	ML2	-2.720	-0.095	2.530	FALSE
ML3	YL1	-1.795	0.830	3.455	FALSE
ML3	HKHLL1	-1.070	1.555	4.180	FALSE
ML3	STBD1	0.590	3.215	5.840	TRUE
ML3	GKC1	0.725	3.350	5.975	TRUE
ML3	STBD2	1.280	3.905	6.530	TRUE
ML3	STBD3	1.420	4.045	6.670	TRUE
ML2	YL1	-1.700	0.925	3.550	FALSE
ML2	HKHLL1	-0.975	1.650	4.275	FALSE
ML2	STBD1	0.685	3.310	5.935	TRUE
ML2	GKC1	0.820	3.445	6.070	TRUE
ML2	STBD2	1.375	4.000	6.625	TRUE
ML2	STBD3	1.515	4.140	6.765	TRUE
YL1	HKHLL1	-1.900	0.725	3.350	FALSE
YL1	STBD1	-0.240	2.385	5.010	FALSE
YL1	GKC1	-0.105	2.520	5.145	FALSE
YL1	STBD2	0.450	3.075	5.700	TRUE
YL1	STBD3	0.590	3.215	5.840	TRUE
HKHLL1	STBD1	-0.965	1.660	4.285	FALSE
HKHLL1	GKC1	-0.830	1.795	4.420	FALSE
HKHLL1	STBD2	-0.275	2.350	4.975	FALSE
HKHLL1	STBD3	-0.135	2.490	5.115	FALSE
STBD1	GKC1	-2.490	0.135	2.760	FALSE
STBD1	STBD2	-1.935	0.690	3.315	FALSE
STBD1	STBD3	-1.795	0.830	3.455	FALSE
GKC1	STBD2	-2.070	0.555	3.180	FALSE
GKC1	STBD3	-1.930	0.695	3.320	FALSE
STBD2	STBD3	-2.485	0.140	2.765	FALSE

download these results as csv

Friedman's Test (BROAD Scores)

The Friedman test was run in MATLAB against the BROAD summary data over the 100 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);

TeamID	TeamID	Lowerbound	Mean	Upperbound	Significance
SSPK2	CTCP2	-2.007	0.515	3.037	FALSE
SSPK2	SSKS3	-2.132	0.390	2.912	FALSE
SSPK2	PS1	-2.262	0.260	2.782	FALSE
SSPK2	CTCP1	-1.432	1.090	3.612	FALSE
SSPK2	CTCP3	-1.207	1.315	3.837	FALSE
SSPK2	DM2	0.448	2.970	5.492	TRUE
SSPK2	DM3	0.418	2.940	5.462	TRUE
SSPK2	ZYC2	0.308	2.830	5.352	TRUE
SSPK2	ML3	1.893	4.415	6.937	TRUE
SSPK2	ML1	1.838	4.360	6.882	TRUE
SSPK2	ML2	1.953	4.475	6.997	TRUE
SSPK2	YL1	2.828	5.350	7.872	TRUE
SSPK2	HKHLL1	3.383	5.905	8.427	TRUE
SSPK2	STBD1	5.173	7.695	10.217	TRUE
SSPK2	GKC1	5.293	7.815	10.337	TRUE
SSPK2	STBD2	5.633	8.155	10.677	TRUE
SSPK2	STBD3	5.938	8.460	10.982	TRUE
CTCP2	SSKS3	-2.647	-0.125	2.397	FALSE
CTCP2	PS1	-2.777	-0.255	2.267	FALSE
CTCP2	CTCP1	-1.947	0.575	3.097	FALSE
CTCP2	CTCP3	-1.722	0.800	3.322	FALSE
CTCP2	DM2	-0.067	2.455	4.977	FALSE
CTCP2	DM3	-0.097	2.425	4.947	FALSE
CTCP2	ZYC2	-0.207	2.315	4.837	FALSE
CTCP2	ML3	1.378	3.900	6.422	TRUE
CTCP2	ML1	1.323	3.845	6.367	TRUE
CTCP2	ML2	1.438	3.960	6.482	TRUE
CTCP2	YL1	2.313	4.835	7.357	TRUE
CTCP2	HKHLL1	2.868	5.390	7.912	TRUE
CTCP2	STBD1	4.658	7.180	9.702	TRUE
CTCP2	GKC1	4.778	7.300	9.822	TRUE
CTCP2	STBD2	5.118	7.640	10.162	TRUE
CTCP2	STBD3	5.423	7.945	10.467	TRUE
SSKS3	PS1	-2.652	-0.130	2.392	FALSE
SSKS3	CTCP1	-1.822	0.700	3.222	FALSE
SSKS3	CTCP3	-1.597	0.925	3.447	FALSE
SSKS3	DM2	0.058	2.580	5.102	TRUE
SSKS3	DM3	0.028	2.550	5.072	TRUE
SSKS3	ZYC2	-0.082	2.440	4.962	FALSE
SSKS3	ML3	1.503	4.025	6.547	TRUE
SSKS3	ML1	1.448	3.970	6.492	TRUE
SSKS3	ML2	1.563	4.085	6.607	TRUE
SSKS3	YL1	2.438	4.960	7.482	TRUE
SSKS3	HKHLL1	2.993	5.515	8.037	TRUE
SSKS3	STBD1	4.783	7.305	9.827	TRUE
SSKS3	GKC1	4.903	7.425	9.947	TRUE
SSKS3	STBD2	5.243	7.765	10.287	TRUE
SSKS3	STBD3	5.548	8.070	10.592	TRUE
PS1	CTCP1	-1.692	0.830	3.352	FALSE
PS1	CTCP3	-1.467	1.055	3.577	FALSE
PS1	DM2	0.188	2.710	5.232	TRUE
PS1	DM3	0.158	2.680	5.202	TRUE
PS1	ZYC2	0.048	2.570	5.092	TRUE
PS1	ML3	1.633	4.155	6.677	TRUE
PS1	ML1	1.578	4.100	6.622	TRUE
PS1	ML2	1.693	4.215	6.737	TRUE
PS1	YL1	2.568	5.090	7.612	TRUE
PS1	HKHLL1	3.123	5.645	8.167	TRUE
PS1	STBD1	4.913	7.435	9.957	TRUE
PS1	GKC1	5.033	7.555	10.077	TRUE
PS1	STBD2	5.373	7.895	10.417	TRUE
PS1	STBD3	5.678	8.200	10.722	TRUE
CTCP1	CTCP3	-2.297	0.225	2.747	FALSE
CTCP1	DM2	-0.642	1.880	4.402	FALSE
CTCP1	DM3	-0.672	1.850	4.372	FALSE
CTCP1	ZYC2	-0.782	1.740	4.262	FALSE
CTCP1	ML3	0.803	3.325	5.847	TRUE
CTCP1	ML1	0.748	3.270	5.792	TRUE
CTCP1	ML2	0.863	3.385	5.907	TRUE
CTCP1	YL1	1.738	4.260	6.782	TRUE
CTCP1	HKHLL1	2.293	4.815	7.337	TRUE
CTCP1	STBD1	4.083	6.605	9.127	TRUE
CTCP1	GKC1	4.203	6.725	9.247	TRUE
CTCP1	STBD2	4.543	7.065	9.587	TRUE
CTCP1	STBD3	4.848	7.370	9.892	TRUE
CTCP3	DM2	-0.867	1.655	4.177	FALSE
CTCP3	DM3	-0.897	1.625	4.147	FALSE
CTCP3	ZYC2	-1.007	1.515	4.037	FALSE
CTCP3	ML3	0.578	3.100	5.622	TRUE
CTCP3	ML1	0.523	3.045	5.567	TRUE
CTCP3	ML2	0.638	3.160	5.682	TRUE
CTCP3	YL1	1.513	4.035	6.557	TRUE
CTCP3	HKHLL1	2.068	4.590	7.112	TRUE
CTCP3	STBD1	3.858	6.380	8.902	TRUE
CTCP3	GKC1	3.978	6.500	9.022	TRUE
CTCP3	STBD2	4.318	6.840	9.362	TRUE
CTCP3	STBD3	4.623	7.145	9.667	TRUE
DM2	DM3	-2.552	-0.030	2.492	FALSE
DM2	ZYC2	-2.662	-0.140	2.382	FALSE
DM2	ML3	-1.077	1.445	3.967	FALSE
DM2	ML1	-1.132	1.390	3.912	FALSE
DM2	ML2	-1.017	1.505	4.027	FALSE
DM2	YL1	-0.142	2.380	4.902	FALSE
DM2	HKHLL1	0.413	2.935	5.457	TRUE
DM2	STBD1	2.203	4.725	7.247	TRUE
DM2	GKC1	2.323	4.845	7.367	TRUE
DM2	STBD2	2.663	5.185	7.707	TRUE
DM2	STBD3	2.968	5.490	8.012	TRUE
DM3	ZYC2	-2.632	-0.110	2.412	FALSE
DM3	ML3	-1.047	1.475	3.997	FALSE
DM3	ML1	-1.102	1.420	3.942	FALSE
DM3	ML2	-0.987	1.535	4.057	FALSE
DM3	YL1	-0.112	2.410	4.932	FALSE
DM3	HKHLL1	0.443	2.965	5.487	TRUE
DM3	STBD1	2.233	4.755	7.277	TRUE
DM3	GKC1	2.353	4.875	7.397	TRUE
DM3	STBD2	2.693	5.215	7.737	TRUE
DM3	STBD3	2.998	5.520	8.042	TRUE
ZYC2	ML3	-0.937	1.585	4.107	FALSE
ZYC2	ML1	-0.992	1.530	4.052	FALSE
ZYC2	ML2	-0.877	1.645	4.167	FALSE
ZYC2	YL1	-0.002	2.520	5.042	FALSE
ZYC2	HKHLL1	0.553	3.075	5.597	TRUE
ZYC2	STBD1	2.343	4.865	7.387	TRUE
ZYC2	GKC1	2.463	4.985	7.507	TRUE
ZYC2	STBD2	2.803	5.325	7.847	TRUE
ZYC2	STBD3	3.108	5.630	8.152	TRUE
ML3	ML1	-2.577	-0.055	2.467	FALSE
ML3	ML2	-2.462	0.060	2.582	FALSE
ML3	YL1	-1.587	0.935	3.457	FALSE
ML3	HKHLL1	-1.032	1.490	4.012	FALSE
ML3	STBD1	0.758	3.280	5.802	TRUE
ML3	GKC1	0.878	3.400	5.922	TRUE
ML3	STBD2	1.218	3.740	6.262	TRUE
ML3	STBD3	1.523	4.045	6.567	TRUE
ML1	ML2	-2.407	0.115	2.637	FALSE
ML1	YL1	-1.532	0.990	3.512	FALSE
ML1	HKHLL1	-0.977	1.545	4.067	FALSE
ML1	STBD1	0.813	3.335	5.857	TRUE
ML1	GKC1	0.933	3.455	5.977	TRUE
ML1	STBD2	1.273	3.795	6.317	TRUE
ML1	STBD3	1.578	4.100	6.622	TRUE
ML2	YL1	-1.647	0.875	3.397	FALSE
ML2	HKHLL1	-1.092	1.430	3.952	FALSE
ML2	STBD1	0.698	3.220	5.742	TRUE
ML2	GKC1	0.818	3.340	5.862	TRUE
ML2	STBD2	1.158	3.680	6.202	TRUE
ML2	STBD3	1.463	3.985	6.507	TRUE
YL1	HKHLL1	-1.967	0.555	3.077	FALSE
YL1	STBD1	-0.177	2.345	4.867	FALSE
YL1	GKC1	-0.057	2.465	4.987	FALSE
YL1	STBD2	0.283	2.805	5.327	TRUE
YL1	STBD3	0.588	3.110	5.632	TRUE
HKHLL1	STBD1	-0.732	1.790	4.312	FALSE
HKHLL1	GKC1	-0.612	1.910	4.432	FALSE
HKHLL1	STBD2	-0.272	2.250	4.772	FALSE
HKHLL1	STBD3	0.033	2.555	5.077	TRUE
STBD1	GKC1	-2.402	0.120	2.642	FALSE
STBD1	STBD2	-2.062	0.460	2.982	FALSE
STBD1	STBD3	-1.757	0.765	3.287	FALSE
GKC1	STBD2	-2.182	0.340	2.862	FALSE
GKC1	STBD3	-1.877	0.645	3.167	FALSE
STBD2	STBD3	-2.217	0.305	2.827	FALSE

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Summary Results by Query

FINE Scores

These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 and 100. A perfect score would be 100. Genre labels have been included for reference.

Genre	Query	CTCP1	CTCP2	CTCP3	DM2	DM3	GKC1	HKHLL1	ML1	ML2	ML3	PS1	SSKS3	SSPK2	STBD1	STBD2	STBD3	YL1	ZYC2
BAROQUE	d006677	83.4	84.2	84.8	84.2	84.2	51.4	78.6	74.4	77.8	73.8	84.0	87.4	85.8	65.0	69.8	51.6	84.8	83.2
BAROQUE	d006696	78.8	96.2	80.0	86.6	86.8	52.6	87.2	86.8	86.8	78.0	86.8	79.0	88.0	32.2	39.0	15.6	52.0	74.4
BAROQUE	d007449	71.8	86.0	71.8	85.2	85.2	48.8	54.4	69.6	75.0	81.4	84.6	86.4	85.6	60.2	74.0	59.4	17.6	72.4
BAROQUE	d008986	82.4	82.8	64.4	65.0	68.0	13.4	66.8	77.4	61.4	72.0	81.4	70.8	83.8	22.0	0.0	20.2	8.8	62.2
BAROQUE	d012398	67.0	83.0	66.0	81.0	76.0	72.0	71.0	62.0	74.0	74.0	81.0	75.0	76.0	70.0	55.0	43.0	79.0	74.0
BAROQUE	d013785	18.6	12.0	20.6	0.0	0.0	8.4	0.0	4.0	0.0	0.0	11.0	11.8	34.6	0.0	21.2	1.8	0.0	13.6
BAROQUE	d014514	75.8	73.8	76.4	34.6	35.2	19.4	73.4	71.8	75.2	75.2	76.6	66.6	70.0	29.6	17.8	18.6	44.4	75.6
BAROQUE	d014776	61.2	59.2	68.6	62.2	62.2	22.2	44.6	43.6	37.2	38.6	61.4	67.4	71.6	33.2	36.6	25.8	44.6	69.8
BAROQUE	d015410	21.6	25.8	21.0	24.6	30.6	31.0	22.0	22.2	22.0	22.6	35.0	35.6	36.8	33.0	19.0	32.0	24.4	34.4
BAROQUE	d016296	67.8	69.4	43.8	53.2	53.2	18.8	32.0	61.0	54.6	65.8	68.6	53.0	55.4	13.2	5.0	47.2	43.0	54.2
BLUES	e003498	23.0	19.2	21.8	7.8	7.8	12.0	3.0	12.4	6.8	6.8	29.2	23.2	8.0	21.0	8.6	3.2	8.4	13.8
BLUES	e006591	35.2	37.8	36.2	33.4	33.4	14.0	30.2	39.6	33.2	44.8	56.6	45.0	51.2	36.8	13.6	45.8	47.4	27.0
BLUES	e006594	83.2	67.6	83.2	87.4	87.4	4.6	84.0	70.0	33.2	67.8	78.0	86.0	85.0	41.0	55.4	32.4	69.4	42.8
BLUES	e007332	81.6	80.0	81.6	68.0	64.4	32.2	76.4	76.0	71.8	74.6	81.2	81.0	85.2	44.0	61.2	36.2	60.6	82.8
BLUES	e010207	59.8	63.6	65.0	49.0	49.0	22.2	22.8	23.2	22.4	24.2	80.0	75.2	59.6	25.2	19.4	46.6	53.4	39.6
BLUES	e010715	74.2	68.2	76.0	63.8	63.8	23.8	40.6	67.0	49.6	70.0	76.2	75.2	72.8	51.6	56.2	35.6	54.2	10.4
BLUES	e012145	64.8	64.8	57.4	50.0	50.0	49.0	35.2	32.6	14.2	43.8	62.2	53.0	49.2	49.8	44.4	22.6	58.4	50.8
BLUES	e012250	71.6	75.6	73.2	65.2	65.2	60.2	66.6	29.6	58.8	61.0	77.6	67.4	62.8	28.0	46.6	33.8	37.4	66.0
BLUES	e012576	40.0	36.0	20.0	17.0	23.0	50.0	23.0	28.0	18.0	17.0	64.0	33.0	28.0	26.0	57.6	46.0	61.0	40.0
BLUES	e015955	80.8	77.8	82.8	67.2	67.2	33.0	61.6	39.2	52.4	49.4	84.8	81.8	82.2	27.4	34.6	41.0	50.8	54.4
CLASSICAL	d002664	29.6	39.8	35.2	30.0	30.0	16.0	20.8	48.6	44.0	31.6	34.6	33.6	33.0	3.6	2.0	1.0	37.6	16.4
CLASSICAL	d008359	71.4	69.0	62.6	69.4	69.2	32.8	69.0	58.6	60.0	60.6	74.8	69.4	74.0	37.0	37.2	28.4	63.8	52.4
CLASSICAL	d008847	68.0	64.2	66.6	69.8	66.8	55.4	64.6	62.4	59.6	53.4	71.0	72.6	71.2	44.6	13.4	55.2	21.6	66.4
CLASSICAL	d009363	31.0	25.0	30.2	26.8	28.0	41.4	28.0	38.2	39.2	32.6	43.8	28.8	30.6	32.8	29.6	26.2	36.2	38.8
CLASSICAL	d010273	84.0	82.0	83.8	81.0	78.0	37.2	78.6	83.0	82.2	83.0	83.6	82.6	65.0	65.6	15.6	49.2	79.8	78.8
CLASSICAL	d012347	87.6	82.8	88.4	86.2	86.2	10.6	76.4	79.2	85.6	82.6	90.0	90.6	90.0	7.4	14.0	73.6	66.6	69.0
CLASSICAL	d013474	64.4	74.6	73.8	75.8	75.8	67.4	64.2	68.8	69.2	62.8	71.6	69.8	77.6	39.2	33.8	44.8	48.6	61.2
CLASSICAL	d013555	12.6	9.2	25.6	23.8	16.8	14.6	21.0	22.2	21.6	21.8	17.2	23.6	27.4	9.2	14.2	6.2	20.2	24.6
CLASSICAL	d013745	79.8	81.4	79.0	62.0	62.0	16.0	72.8	73.4	76.6	75.6	81.6	71.4	72.0	59.0	23.2	48.4	63.4	72.6
CLASSICAL	d019428	70.8	72.6	67.2	60.6	60.6	25.8	36.4	58.2	57.4	56.2	64.0	65.6	61.2	53.2	42.0	7.8	39.8	50.2
COUNTRY	b007754	55.2	65.0	50.0	51.0	55.0	5.0	0.0	60.8	44.8	33.2	58.2	41.0	49.2	23.0	33.8	14.4	54.8	40.2
COUNTRY	e000004	56.4	65.2	54.4	35.0	35.0	28.4	50.6	20.0	39.2	26.8	26.2	70.4	67.0	24.4	32.2	15.2	41.0	28.4
COUNTRY	e005074	62.0	73.0	65.0	50.0	48.0	46.0	68.0	42.0	52.0	62.0	61.0	58.0	68.0	31.0	46.0	10.0	48.0	67.0
COUNTRY	e006998	71.0	71.0	53.0	27.0	34.0	23.0	28.0	40.0	27.0	35.0	66.0	74.0	59.0	3.0	23.0	15.0	24.0	41.0
COUNTRY	e008019	76.0	76.0	70.0	66.0	66.0	50.0	58.0	68.0	60.0	70.0	82.0	68.0	70.0	66.0	36.0	24.0	66.0	78.0
COUNTRY	e010395	53.4	52.2	47.6	54.2	51.8	23.2	36.8	31.0	37.4	26.4	55.4	50.8	65.6	43.2	36.2	18.6	19.6	46.4
COUNTRY	e012084	68.8	71.6	82.2	76.2	72.0	13.0	75.2	63.6	51.2	57.8	82.6	69.2	80.4	55.4	45.2	70.8	72.8	70.4
COUNTRY	e014772	42.2	40.4	41.0	46.4	49.2	33.8	40.2	39.2	35.8	38.6	41.0	40.8	50.0	37.0	37.2	39.2	38.8	51.2
COUNTRY	e019603	47.8	45.2	38.8	47.8	47.8	13.6	22.8	37.6	38.0	31.8	36.8	33.4	51.6	16.4	8.6	9.8	45.4	30.6
COUNTRY	e019738	71.0	59.0	65.0	67.0	67.0	38.0	59.0	62.0	64.0	61.0	57.0	64.0	67.0	43.0	49.0	33.0	55.0	65.0
EDANCE	a005135	54.0	57.0	57.0	27.0	30.0	41.0	19.0	2.2	31.0	53.0	41.0	39.0	43.0	54.0	32.0	28.0	46.0	0.0
EDANCE	a005589	54.4	37.4	32.4	22.6	22.6	22.0	0.0	28.0	13.8	44.2	33.6	26.8	39.8	3.4	21.0	0.0	45.0	35.2
EDANCE	a007506	61.2	57.4	68.8	52.2	52.2	72.6	10.4	35.2	43.2	24.4	64.8	71.4	70.4	56.0	25.6	23.4	42.0	56.6
EDANCE	b003709	44.4	42.8	45.2	50.6	50.6	38.6	5.8	36.6	37.6	38.8	45.6	44.2	57.6	29.6	18.0	30.6	21.0	12.0
EDANCE	b005745	26.2	17.2	26.4	24.0	24.0	14.6	25.8	28.6	20.4	24.6	30.8	33.8	29.0	12.0	18.4	14.2	19.6	26.6
EDANCE	b006254	35.6	28.6	49.0	1.6	3.4	44.6	15.0	4.6	9.4	5.2	18.4	54.4	49.0	1.2	10.0	6.4	32.0	2.4
EDANCE	b011836	34.0	40.0	40.0	34.0	42.0	42.0	24.0	52.0	40.0	40.0	32.0	46.0	54.0	18.0	40.0	32.0	24.0	24.0
EDANCE	b016602	66.0	66.0	63.0	33.4	46.6	57.0	49.8	34.6	59.6	42.0	49.2	70.6	55.0	30.4	30.4	49.2	45.6	37.4
EDANCE	f003218	83.0	88.0	76.0	76.0	76.0	78.0	31.0	77.0	74.0	76.0	87.0	70.0	94.0	42.0	52.0	77.0	59.0	54.0
EDANCE	f019182	32.4	53.0	28.4	42.8	30.2	35.6	15.6	16.8	18.6	23.0	34.6	51.6	26.4	24.4	29.6	17.2	65.0	34.4
JAZZ	a006733	83.0	85.0	72.0	11.0	11.0	38.0	13.0	21.0	19.0	23.0	65.0	81.0	81.0	21.0	34.0	44.0	32.0	22.0
JAZZ	a009161	61.0	57.8	64.4	33.0	29.2	25.6	45.8	60.6	56.2	53.6	40.0	55.6	76.0	33.4	21.2	12.0	63.6	57.4
JAZZ	e004616	67.4	74.4	70.6	74.2	73.4	53.2	69.8	69.6	69.8	69.8	78.2	77.6	80.6	61.0	57.4	44.6	64.2	75.4
JAZZ	e004656	79.0	82.6	74.2	70.2	70.2	29.0	64.8	73.4	78.4	73.4	72.4	79.0	81.0	51.0	47.2	40.2	69.8	76.4
JAZZ	e008805	71.8	61.6	64.2	26.4	13.8	21.0	3.4	46.2	39.6	36.0	37.2	55.6	33.0	12.2	9.4	10.8	54.6	29.2
JAZZ	e009003	87.0	83.0	83.0	74.0	74.0	45.0	45.0	58.0	77.0	74.0	82.0	85.0	83.0	41.0	57.0	64.0	10.4	87.0
JAZZ	e009926	0.0	0.0	0.0	0.2	0.2	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	8.0	0.2	3.2	0.4	0.0
JAZZ	e010314	87.2	90.0	83.0	16.0	19.0	33.8	27.8	41.2	53.2	42.6	59.4	78.8	76.4	32.6	24.4	33.4	12.6	62.2
JAZZ	e010700	71.8	81.6	68.8	28.2	23.4	22.2	52.0	53.0	41.2	36.4	33.8	56.8	47.2	14.6	30.4	26.8	14.8	41.8
JAZZ	e012958	6.0	8.0	0.0	23.2	23.2	20.4	0.0	0.0	6.0	0.0	20.6	0.6	0.0	15.0	2.0	0.0	0.0	0.0
METAL	a000907	21.8	23.0	39.0	32.0	39.8	8.2	23.8	21.0	8.8	19.6	22.0	29.2	39.0	2.2	1.2	8.6	19.4	20.6
METAL	b001064	72.2	74.2	71.4	49.4	44.8	34.8	44.0	45.4	67.8	71.4	46.4	79.8	71.4	20.4	25.6	49.8	66.8	44.8
METAL	b005963	86.0	79.0	85.0	83.0	79.0	71.0	52.0	74.0	68.0	77.0	83.0	79.0	72.0	42.0	43.0	56.0	77.0	74.0
METAL	b007455	59.6	68.2	57.4	57.2	63.8	11.6	48.2	55.0	55.8	50.0	65.6	41.2	65.8	36.2	24.0	11.4	48.4	61.6
METAL	b008450	38.2	37.4	55.4	63.4	64.6	7.8	40.0	75.6	53.0	56.2	37.4	30.8	14.4	16.8	10.6	21.6	43.2	60.6
METAL	b009939	35.0	27.0	32.4	17.0	15.0	15.8	17.0	48.0	46.0	33.4	40.0	41.0	46.0	18.2	14.0	25.2	23.0	40.0
METAL	b012964	46.0	44.0	33.0	42.0	42.0	10.0	58.0	45.0	41.0	35.0	49.0	46.0	43.0	30.0	8.0	0.0	19.0	49.0
METAL	b019036	33.8	44.2	49.2	26.0	33.2	25.8	29.6	34.0	44.4	43.0	35.2	41.8	29.0	36.2	36.8	20.0	27.0	17.4
METAL	f007939	56.4	37.0	64.0	65.8	55.6	30.8	59.0	67.2	62.2	59.0	60.8	32.4	68.8	12.2	7.4	3.8	52.8	65.4
METAL	f015638	73.0	74.8	81.4	64.0	64.0	4.2	52.4	61.2	61.2	59.8	77.0	83.2	90.2	19.8	15.6	31.6	68.0	67.4
RAPHIPHOP	a000184	45.2	60.0	42.8	59.0	59.0	6.4	58.2	55.6	59.0	57.4	62.6	65.4	61.6	63.2	46.6	15.4	45.0	46.0
RAPHIPHOP	a000369	72.6	78.4	78.0	68.8	53.8	22.4	46.2	72.4	77.4	73.2	79.2	79.2	82.2	73.8	74.0	68.8	75.2	82.0
RAPHIPHOP	a002853	52.2	56.4	26.8	57.8	57.8	38.6	57.4	49.2	75.2	66.0	64.6	57.2	56.8	35.6	15.6	59.8	28.6	51.4
RAPHIPHOP	a006408	73.6	66.0	68.6	72.6	71.8	56.4	73.8	76.6	71.8	70.2	70.8	76.4	71.4	69.8	68.4	73.2	73.8	74.0
RAPHIPHOP	a007204	78.6	80.8	70.8	75.4	75.4	65.0	82.8	46.8	70.4	65.4	80.6	81.6	80.0	33.2	32.8	27.4	58.4	76.6
RAPHIPHOP	a008101	68.4	73.2	63.8	57.8	51.0	11.0	49.8	69.2	63.2	66.4	71.2	71.0	68.4	45.8	31.2	55.0	54.8	68.2
RAPHIPHOP	b001529	61.0	53.0	52.0	53.4	47.4	4.2	44.2	56.0	18.0	43.0	43.0	36.0	57.0	24.0	54.0	12.2	66.0	36.0
RAPHIPHOP	b009504	57.0	59.0	50.0	67.0	67.0	13.2	54.4	56.4	63.0	74.2	61.6	43.6	48.8	6.2	3.0	57.4	60.6	60.2
RAPHIPHOP	b012102	39.0	59.6	47.0	62.2	62.2	29.6	38.4	62.0	65.6	81.6	59.8	74.2	59.0	63.0	29.6	45.6	25.8	71.0
RAPHIPHOP	b018710	41.6	69.0	48.0	71.6	64.2	26.6	32.4	59.0	67.2	59.0	66.0	69.4	77.0	26.0	32.2	65.2	42.8	46.0
ROCKROLL	a003466	10.2	9.6	28.8	8.6	8.6	32.6	17.8	25.2	18.4	9.4	25.6	38.2	20.6	24.2	24.4	22.4	18.8	20.2
ROCKROLL	b000979	29.0	41.0	28.0	38.0	50.0	0.0	23.0	49.0	36.0	30.0	44.0	63.0	37.0	18.0	14.0	8.0	16.0	58.0
ROCKROLL	b001750	32.0	30.0	29.0	41.0	41.0	38.0	36.0	42.0	49.0	49.0	32.0	38.0	51.0	24.0	30.0	14.0	42.0	28.0
ROCKROLL	b005580	41.2	35.2	35.8	31.6	31.6	27.2	22.0	41.0	27.4	18.6	32.6	33.8	36.4	34.4	24.0	2.6	23.8	36.8
ROCKROLL	b008059	48.0	41.2	37.2	36.4	36.4	30.0	8.4	8.2	17.6	9.2	51.6	63.8	37.8	12.2	21.2	11.4	11.8	30.0
ROCKROLL	b008990	48.4	70.4	46.2	44.2	44.2	38.8	25.4	41.6	29.0	38.0	54.6	64.6	46.0	32.2	24.0	1.6	43.4	51.2
ROCKROLL	b011113	36.0	36.4	36.2	38.0	37.8	25.8	32.6	37.6	34.6	27.8	33.0	38.4	36.8	27.4	37.6	23.8	38.0	39.4
ROCKROLL	b016165	66.8	69.8	60.4	57.6	59.2	49.8	54.4	46.6	29.0	45.4	61.0	59.2	49.8	31.4	12.6	30.0	57.8	73.6
ROCKROLL	b017586	55.0	55.0	57.0	47.0	53.0	53.0	49.0	51.0	49.0	48.0	58.0	60.0	51.0	21.0	25.0	18.0	47.0	47.0
ROCKROLL	b019928	49.8	50.2	55.2	59.4	55.4	29.2	31.8	44.2	40.0	50.2	49.2	50.0	52.2	37.4	51.4	42.2	43.8	53.8
ROMANTIC	d005834	58.6	48.4	62.0	46.2	46.2	23.4	5.6	17.6	29.0	22.8	55.8	59.8	52.2	7.6	10.8	43.4	29.2	50.0
ROMANTIC	d009949	67.0	64.8	59.8	65.2	65.2	50.6	59.8	62.0	62.0	62.0	67.4	68.4	65.4	58.4	47.4	20.6	35.6	69.4
ROMANTIC	d010217	43.6	42.6	50.2	36.2	36.2	29.4	39.6	44.4	34.2	34.2	52.2	37.8	43.0	39.4	30.0	17.2	32.4	32.4
ROMANTIC	d012214	66.0	68.4	61.0	65.2	64.0	55.0	53.2	55.6	58.4	55.2	63.8	66.0	70.6	34.0	43.0	46.0	45.0	69.2
ROMANTIC	d015538	82.6	85.2	89.6	82.4	86.4	44.2	57.2	60.8	69.0	73.6	85.0	84.6	85.2	67.4	34.6	50.6	80.8	88.0
ROMANTIC	d016565	46.0	54.0	45.0	33.0	37.0	25.0	24.0	22.0	29.0	18.0	48.0	42.0	47.0	54.0	29.0	7.0	15.0	41.0
ROMANTIC	d017427	94.6	91.0	94.0	91.6	91.6	79.2	71.8	54.0	53.4	51.2	94.8	92.0	94.6	78.6	47.2	36.8	39.8	84.2
ROMANTIC	d017784	69.0	74.0	69.0	73.0	73.0	68.0	71.0	47.0	66.0	51.0	75.0	67.0	77.0	87.0	63.0	85.0	33.0	73.0
ROMANTIC	d018721	47.6	56.2	45.0	32.2	32.2	11.2	61.4	46.8	52.4	26.0	51.4	46.6	58.4	12.0	20.0	16.2	6.8	57.8
ROMANTIC	d019573	73.2	77.4	75.0	65.0	67.6	16.2	51.4	66.4	50.8	74.2	75.0	72.0	72.6	51.4	26.0	27.6	36.8	65.0

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BROAD Scores

These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference.

Genre	Query	CTCP1	CTCP2	CTCP3	DM2	DM3	GKC1	HKHLL1	ML1	ML2	ML3	PS1	SSKS3	SSPK2	STBD1	STBD2	STBD3	YL1	ZYC2
BAROQUE	d006677	2.0	2.0	2.0	2.0	2.0	1.0	1.6	1.6	1.8	1.6	2.0	2.0	2.0	1.2	1.4	1.2	2.0	1.8
BAROQUE	d006696	1.6	2.0	1.6	1.8	1.8	1.0	1.8	1.8	1.8	1.6	1.8	1.6	1.8	0.6	0.8	0.2	1.0	1.6
BAROQUE	d007449	1.6	2.0	1.6	2.0	2.0	1.0	1.0	1.6	1.6	1.8	2.0	2.0	2.0	1.4	1.6	1.2	0.0	1.8
BAROQUE	d008986	1.8	2.0	1.4	1.8	1.8	0.2	1.4	1.8	1.4	1.8	1.8	1.8	2.0	0.4	0.0	0.4	0.0	1.2
BAROQUE	d012398	1.6	1.8	1.6	1.8	1.8	1.6	1.4	1.2	1.8	2.0	1.8	2.0	1.8	1.6	1.2	0.8	2.0	1.6
BAROQUE	d013785	0.4	0.2	0.4	0.0	0.0	0.2	0.0	0.0	0.0	0.0	0.2	0.2	0.8	0.0	0.4	0.0	0.0	0.4
BAROQUE	d014514	1.8	1.6	1.8	0.4	0.4	0.0	1.6	1.6	1.8	1.8	1.6	1.6	1.6	0.2	0.2	0.0	1.0	1.6
BAROQUE	d014776	1.4	1.2	1.4	1.4	1.4	0.4	1.0	1.0	0.6	0.6	1.4	1.6	1.8	0.4	0.6	0.4	1.0	1.6
BAROQUE	d015410	0.0	0.2	0.0	0.0	0.2	0.4	0.0	0.0	0.0	0.0	0.4	0.4	0.4	0.4	0.4	0.4	0.2	0.6
BAROQUE	d016296	1.6	1.4	0.8	1.2	1.2	0.2	0.6	1.2	1.2	1.6	1.6	1.0	1.2	0.2	0.0	1.2	1.2	1.2
BLUES	e003498	0.2	0.2	0.2	0.0	0.0	0.2	0.0	0.2	0.0	0.0	0.4	0.2	0.0	0.4	0.2	0.0	0.2	0.2
BLUES	e006591	0.6	0.6	0.8	0.6	0.6	0.0	0.6	0.8	0.6	1.0	1.2	0.8	1.0	0.6	0.0	1.0	1.0	0.4
BLUES	e006594	2.0	1.6	2.0	2.0	2.0	0.0	2.0	1.8	0.8	1.6	2.0	2.0	2.0	0.8	1.0	0.8	1.8	1.0
BLUES	e007332	1.8	1.8	2.0	1.4	1.2	0.4	1.6	1.8	1.6	1.8	1.8	1.8	2.0	0.8	1.2	0.8	1.4	2.0
BLUES	e010207	1.4	1.2	1.2	1.2	1.2	0.4	0.4	0.4	0.4	0.4	2.0	1.6	1.4	0.2	0.2	1.2	1.0	0.8
BLUES	e010715	1.6	1.4	1.8	1.4	1.4	0.2	0.6	1.4	0.8	1.6	1.8	1.8	1.6	1.0	1.2	0.4	1.0	0.0
BLUES	e012145	1.6	1.6	1.6	1.0	1.0	0.8	0.8	0.6	0.0	1.0	1.6	1.2	1.0	1.0	0.8	0.2	1.4	1.0
BLUES	e012250	1.6	1.8	1.8	1.6	1.6	1.2	1.6	0.6	1.2	1.4	2.0	1.6	1.6	0.4	0.8	0.6	0.8	1.6
BLUES	e012576	0.8	0.6	0.2	0.2	0.4	1.0	0.4	0.2	0.0	0.0	1.4	0.6	0.4	0.6	1.2	1.0	1.4	0.8
BLUES	e015955	2.0	1.8	2.0	1.6	1.6	0.4	1.2	0.6	1.0	1.0	2.0	2.0	2.0	0.4	0.6	0.8	1.0	1.0
CLASSICAL	d002664	0.6	1.0	0.8	0.6	0.6	0.4	0.4	1.0	1.0	0.4	0.8	0.6	0.6	0.0	0.0	0.0	0.8	0.2
CLASSICAL	d008359	1.8	1.8	1.4	1.6	1.6	0.6	1.8	1.2	1.4	1.4	2.0	1.6	2.0	0.4	0.4	0.2	1.6	1.2
CLASSICAL	d008847	1.2	1.0	1.2	1.4	1.4	1.0	1.0	1.0	1.0	0.8	1.0	1.2	1.2	0.6	0.4	1.0	0.2	1.0
CLASSICAL	d009363	0.8	0.6	0.8	0.8	1.0	0.8	0.8	1.0	1.0	1.0	1.2	0.8	0.8	1.0	0.8	1.0	1.2	1.0
CLASSICAL	d010273	2.0	2.0	2.0	2.0	1.8	0.8	1.8	2.0	2.0	2.0	2.0	2.0	1.6	1.4	0.0	1.0	2.0	2.0
CLASSICAL	d012347	2.0	1.8	2.0	2.0	2.0	0.0	1.8	1.8	1.8	2.0	2.0	2.0	2.0	0.0	0.0	1.4	1.4	1.2
CLASSICAL	d013474	1.6	2.0	1.8	2.0	2.0	1.6	1.6	1.8	1.6	1.2	1.8	1.8	2.0	0.8	0.8	1.0	1.2	1.6
CLASSICAL	d013555	0.0	0.0	0.4	0.2	0.2	0.0	0.0	0.0	0.0	0.0	0.0	0.2	0.2	0.0	0.0	0.0	0.2	0.0
CLASSICAL	d013745	2.0	2.0	2.0	1.6	1.6	0.2	2.0	2.0	1.8	2.0	2.0	2.0	2.0	1.6	0.4	1.2	1.6	1.8
CLASSICAL	d019428	1.8	1.8	1.6	1.6	1.6	0.6	0.6	1.2	1.4	1.2	1.6	1.6	1.4	1.4	1.0	0.0	1.0	1.2
COUNTRY	b007754	0.8	1.0	0.4	0.8	1.0	0.0	0.0	0.6	0.6	0.4	0.8	0.4	0.8	0.4	0.4	0.2	1.0	0.4
COUNTRY	e000004	1.2	1.4	1.0	0.4	0.4	0.2	1.2	0.2	0.6	0.4	0.2	1.4	1.6	0.2	0.2	0.0	0.8	0.2
COUNTRY	e005074	1.4	1.8	1.6	1.0	0.8	0.8	1.8	0.6	0.8	1.4	1.2	1.2	1.4	0.4	0.8	0.0	0.8	1.6
COUNTRY	e006998	1.6	1.6	1.2	0.4	0.6	0.2	0.6	0.8	0.4	0.4	1.4	1.6	1.2	0.0	0.4	0.2	0.4	0.8
COUNTRY	e008019	1.8	1.8	1.6	1.4	1.4	1.0	1.2	1.6	1.2	1.6	2.0	1.6	1.6	1.4	0.4	0.0	1.4	1.8
COUNTRY	e010395	1.2	1.0	1.0	1.0	1.0	0.2	0.4	0.4	0.6	0.4	1.2	0.8	1.4	0.6	0.4	0.2	0.2	0.8
COUNTRY	e012084	1.2	1.2	1.6	1.4	1.2	0.2	1.4	1.0	1.0	1.0	1.6	1.2	1.4	1.0	0.6	1.2	1.2	1.2
COUNTRY	e014772	1.0	1.0	1.0	1.0	1.2	0.6	1.0	1.0	1.0	1.0	1.0	1.0	1.2	1.0	1.0	1.0	1.0	1.2
COUNTRY	e019603	1.2	1.2	1.0	1.2	1.2	0.2	0.6	0.8	1.0	0.6	0.8	1.0	1.4	0.4	0.2	0.0	1.0	0.8
COUNTRY	e019738	1.6	1.2	1.8	1.6	1.6	0.6	1.4	1.0	1.2	1.2	1.2	1.4	1.6	0.4	1.0	0.4	1.0	1.6
EDANCE	a005135	1.0	1.2	1.2	0.4	0.4	0.8	0.2	0.0	0.4	1.2	0.6	0.8	1.0	1.4	0.8	0.4	1.0	0.0
EDANCE	a005589	1.6	1.0	0.8	0.6	0.6	0.6	0.0	0.8	0.4	1.2	1.0	0.6	1.0	0.2	0.6	0.0	1.2	0.8
EDANCE	a007506	1.2	1.0	1.4	0.8	0.8	1.6	0.0	0.4	0.6	0.0	1.0	1.2	1.4	1.0	0.4	0.0	0.6	1.0
EDANCE	b003709	0.8	0.8	0.8	1.2	1.2	0.4	0.0	0.6	0.8	0.8	1.0	0.8	1.0	0.6	0.2	0.8	0.2	0.2
EDANCE	b005745	0.6	0.4	0.6	0.6	0.6	0.2	0.6	0.6	0.4	0.6	0.8	0.8	0.6	0.0	0.2	0.2	0.4	0.6
EDANCE	b006254	0.6	0.6	1.0	0.0	0.0	1.0	0.4	0.0	0.2	0.0	0.4	1.0	1.0	0.0	0.2	0.0	0.6	0.0
EDANCE	b011836	0.6	0.8	0.8	0.6	0.8	0.8	0.2	1.0	0.6	0.6	0.4	1.0	1.2	0.0	0.8	0.4	0.2	0.2
EDANCE	b016602	1.6	1.4	1.4	0.8	1.2	1.2	0.8	0.6	1.4	0.8	1.2	1.4	1.0	0.6	0.4	1.2	1.2	0.6
EDANCE	f003218	1.8	1.8	1.8	1.8	1.8	1.8	0.8	1.6	1.8	1.8	2.0	1.6	2.0	0.6	1.2	1.6	1.2	1.0
EDANCE	f019182	0.4	1.0	0.2	0.8	0.4	0.8	0.0	0.0	0.2	0.2	0.4	1.0	0.0	0.4	0.4	0.0	1.6	0.4
JAZZ	a006733	2.0	2.0	1.6	0.0	0.0	0.6	0.0	0.0	0.0	0.2	1.4	2.0	2.0	0.2	0.6	1.0	0.4	0.2
JAZZ	a009161	1.2	1.2	1.2	0.8	0.6	0.6	1.2	1.2	1.0	1.0	0.8	1.4	1.8	0.6	0.2	0.2	1.4	1.4
JAZZ	e004616	1.4	1.6	1.6	1.8	1.8	1.2	1.6	1.6	1.6	1.6	1.8	2.0	2.0	1.4	1.4	1.0	1.4	2.0
JAZZ	e004656	2.0	2.0	1.8	1.4	1.4	0.4	1.6	1.8	2.0	1.8	1.6	2.0	1.8	0.8	0.8	0.6	1.6	2.0
JAZZ	e008805	1.6	1.4	1.4	0.4	0.0	0.4	0.0	1.0	1.0	0.8	1.0	1.2	0.8	0.0	0.2	0.2	1.0	0.4
JAZZ	e009003	2.0	2.0	2.0	1.6	1.6	1.2	1.0	1.6	2.0	1.8	2.0	2.0	2.0	0.8	1.2	1.6	0.2	2.0
JAZZ	e009926	0.0	0.0	0.2	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.2	0.0	0.0	0.2	0.0	0.0	0.0	0.0
JAZZ	e010314	2.0	2.0	2.0	0.2	0.2	0.6	0.4	0.8	1.2	0.8	1.2	1.8	1.6	0.8	0.2	0.6	0.0	1.4
JAZZ	e010700	1.6	1.8	1.4	0.2	0.2	0.4	1.0	1.2	0.6	0.6	0.6	1.4	1.0	0.0	0.2	0.4	0.0	0.6
JAZZ	e012958	0.4	0.4	0.0	0.0	0.0	0.4	0.0	0.0	0.4	0.0	0.2	0.0	0.0	0.4	0.2	0.0	0.0	0.0
METAL	a000907	0.2	0.4	0.6	0.4	0.6	0.2	0.4	0.2	0.0	0.2	0.2	0.4	0.6	0.0	0.0	0.2	0.2	0.4
METAL	b001064	1.8	2.0	1.8	0.8	0.8	0.4	1.0	0.6	1.6	1.6	1.0	2.0	1.8	0.0	0.2	1.2	1.4	1.0
METAL	b005963	1.8	1.8	2.0	1.8	1.6	1.8	1.2	1.6	1.4	1.8	2.0	1.8	1.4	0.8	1.0	1.4	1.6	1.8
METAL	b007455	1.4	1.4	1.2	1.2	1.4	0.0	1.0	1.4	1.4	1.2	1.6	0.6	1.2	0.6	0.4	0.0	1.2	1.2
METAL	b008450	1.2	1.2	1.4	1.6	1.6	0.4	0.8	1.8	1.6	1.6	0.8	1.0	0.6	0.2	0.4	0.6	1.2	1.8
METAL	b009939	0.4	0.2	0.6	0.2	0.0	0.2	0.2	0.8	0.6	0.4	0.6	0.8	1.0	0.4	0.2	0.4	0.2	0.8
METAL	b012964	0.8	0.6	0.4	0.8	0.8	0.2	1.2	1.0	0.6	0.6	0.8	0.8	0.8	0.4	0.2	0.0	0.2	1.0
METAL	b019036	0.6	0.8	1.0	1.0	1.0	0.6	0.6	1.2	1.0	1.0	1.0	1.0	0.8	0.8	0.6	0.4	1.0	0.4
METAL	f007939	1.2	0.8	1.4	1.2	1.0	0.6	1.4	1.4	1.4	1.2	1.2	0.6	1.4	0.2	0.0	0.0	1.0	1.4
METAL	f015638	1.6	1.8	2.0	1.4	1.4	0.0	1.2	1.4	1.2	1.2	1.8	2.0	2.0	0.4	0.2	0.6	1.4	1.4
RAPHIPHOP	a000184	1.0	1.4	0.8	1.4	1.4	0.0	1.4	1.4	1.4	1.4	1.8	1.8	1.6	1.8	1.2	0.2	1.0	1.2
RAPHIPHOP	a000369	1.2	1.6	1.6	1.4	1.0	0.4	0.8	1.4	1.6	1.4	1.8	1.6	1.8	1.4	1.6	1.6	1.4	1.8
RAPHIPHOP	a002853	1.2	1.4	0.4	1.4	1.4	0.8	1.6	1.2	2.0	1.6	1.6	1.6	1.6	0.8	0.2	1.4	0.6	1.0
RAPHIPHOP	a006408	2.0	2.0	2.0	2.0	2.0	1.2	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	1.8	2.0	2.0	2.0
RAPHIPHOP	a007204	1.8	1.8	1.4	2.0	2.0	1.4	2.0	0.8	1.6	1.4	1.8	2.0	1.8	0.6	0.6	0.2	1.4	2.0
RAPHIPHOP	a008101	2.0	2.0	1.8	1.4	1.2	0.0	1.2	2.0	1.8	1.8	2.0	2.0	2.0	1.2	0.8	1.4	1.6	1.8
RAPHIPHOP	b001529	1.4	1.2	1.0	1.2	1.0	0.0	0.8	1.2	0.2	0.8	0.8	0.8	1.4	0.2	1.2	0.2	1.4	0.8
RAPHIPHOP	b009504	1.2	1.2	1.0	1.6	1.6	0.2	1.2	1.0	1.4	1.6	1.0	0.8	0.8	0.0	0.0	1.2	1.2	1.2
RAPHIPHOP	b012102	0.8	1.2	1.0	1.4	1.4	0.6	0.8	1.2	1.4	2.0	1.4	1.8	1.2	1.4	0.8	0.8	0.6	1.6
RAPHIPHOP	b018710	0.8	1.8	1.0	1.8	1.6	0.0	0.4	1.6	1.8	1.4	1.6	1.8	2.0	0.4	0.4	1.6	0.8	1.0
ROCKROLL	a003466	0.0	0.0	0.4	0.0	0.0	0.6	0.2	0.4	0.2	0.0	0.2	0.8	0.2	0.6	0.4	0.4	0.2	0.2
ROCKROLL	b000979	0.4	0.8	0.4	0.6	0.8	0.0	0.2	0.8	0.6	0.4	0.8	1.2	0.6	0.2	0.2	0.0	0.2	1.4
ROCKROLL	b001750	0.2	0.2	0.2	0.4	0.4	0.4	0.4	0.4	0.6	0.6	0.2	0.4	0.8	0.2	0.4	0.0	0.6	0.2
ROCKROLL	b005580	1.0	0.8	0.8	0.6	0.6	0.2	0.6	1.0	0.6	0.4	0.8	0.8	0.8	0.6	0.4	0.0	0.2	0.8
ROCKROLL	b008059	1.2	1.2	1.2	1.0	1.0	0.8	0.4	0.6	1.0	0.6	1.2	1.6	1.0	0.6	1.0	0.2	0.4	1.0
ROCKROLL	b008990	1.0	1.4	0.8	1.0	1.0	0.8	0.2	0.8	0.6	0.8	1.0	1.2	1.0	0.6	0.4	0.0	0.8	1.0
ROCKROLL	b011113	1.0	1.0	1.0	1.0	1.0	0.4	0.8	1.0	0.8	0.6	0.8	1.0	1.0	0.6	1.0	0.4	1.0	1.0
ROCKROLL	b016165	1.2	1.4	1.2	1.2	1.2	1.0	1.2	0.8	0.6	0.8	1.0	1.2	1.2	0.6	0.2	0.6	1.2	1.6
ROCKROLL	b017586	1.2	1.2	1.2	1.0	1.0	1.4	0.8	1.0	1.0	1.0	1.4	1.2	1.2	0.0	0.6	0.4	0.8	0.6
ROCKROLL	b019928	1.2	1.4	1.4	1.2	1.2	0.4	0.4	0.8	0.6	1.0	1.2	1.0	1.2	0.4	1.0	0.8	0.8	1.0
ROMANTIC	d005834	1.2	1.2	1.4	1.2	1.2	0.6	0.0	0.2	0.4	0.2	1.4	1.4	1.2	0.0	0.0	0.6	0.8	1.0
ROMANTIC	d009949	1.8	1.4	1.2	1.4	1.4	1.2	1.4	1.4	1.4	1.4	1.8	1.4	1.4	1.2	1.2	0.2	0.6	1.8
ROMANTIC	d010217	1.0	1.0	1.0	1.0	1.0	0.6	1.0	1.0	0.8	0.8	1.2	1.0	1.2	1.0	1.0	0.4	0.8	1.2
ROMANTIC	d012214	1.6	1.6	1.2	1.6	1.4	1.2	1.0	1.2	1.2	1.0	1.2	1.6	2.0	0.6	0.8	0.8	0.8	1.8
ROMANTIC	d015538	2.0	2.0	2.0	1.8	2.0	1.0	1.2	1.4	1.2	1.6	2.0	2.0	1.8	1.4	0.6	0.8	1.8	2.0
ROMANTIC	d016565	0.8	1.0	0.6	0.6	0.6	0.4	0.4	0.2	0.4	0.2	1.0	0.6	0.8	0.8	0.2	0.0	0.2	0.8
ROMANTIC	d017427	2.0	2.0	2.0	2.0	2.0	1.4	1.2	1.0	0.8	0.8	2.0	2.0	2.0	1.2	0.8	0.8	0.8	1.6
ROMANTIC	d017784	1.0	1.4	1.0	1.2	1.2	1.6	1.2	0.8	1.0	0.8	1.4	1.2	1.6	2.0	1.4	2.0	0.6	1.2
ROMANTIC	d018721	1.2	1.4	1.2	0.8	0.8	0.4	1.6	1.2	1.2	0.8	1.6	1.2	1.4	0.6	0.6	0.4	0.2	1.4
ROMANTIC	d019573	2.0	2.0	2.0	1.8	1.8	0.4	1.2	1.8	1.4	2.0	2.0	2.0	2.0	1.2	0.6	0.4	0.8	2.0

download these results as csv

Raw Scores

The raw data derived from the Evalutron 6000 human evaluations are located on the 2011:Audio Music Similarity and Retrieval Raw Data page.

Metadata and Distance Space Evaluation

The following reports provide evaluation statistics based on analysis of the distance space and metadata matches and include:

Neighbourhood clustering by artist, album and genre
Artist-filtered genre clustering
How often the triangular inequality holds
Statistics on 'hubs' (tracks similar to many tracks) and orphans (tracks that are not similar to any other tracks at N results).

Reports

STBD1 = Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
STBD2 = Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
STBD3 = Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
DM2 = Franz de Leon, Kirk Martinez
DM3 = Franz de Leon, Kirk Martinez
GKC1 = Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
HKHLL1 = Byeong-jun Han, Kyogu Lee, Ziwon Hyung, Hyunwoo Kim, Sheayun Lee
ML1 = Brian McFee, Gert Lanckriet
ML2 = Brian McFee, Gert Lanckriet
ML3 = Brian McFee, Gert Lanckriet
PS1 = Dominik Schnitzer, Tim Pohle
SSKS3 = Klaus Seyerlehner, Markus Schedl, Peter Knees, Reinhard Sonnleitner
SSPK2 = Klaus Seyerlehner, Markus Schedl, Peter Knees, Tim Pohle
STBD1 = Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
STBD2 = Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
STBD3 = Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho
YL1 = Yin-Tzu Lin, Wen-Huang Cheng, Ja-Ling Wu
ZYC2 = Dongying Zhang, Deshun Yang, Xiaoou Chen

@@ Line 33: / Line 33: @@
 	| AMS_soton2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/DM3.pdf PDF] || [http://www.iam.ecs.soton.ac.uk/ Franz de Leon], [http://www.iam.ecs.soton.ac.uk/ Kirk Martinez]
          |-
-         ! TLN3
+         ! GKC1
-	| Post-Processing 2 of Marsyas similarity results ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2010/TLN2.pdf PDF] || [http://www.cs.uvic.ca/~gtzan George Tzanetakis], [http://recherche.ircam.fr/equipes/analyse-synthese/home.html Mathieu Lagrange], [http://sness.net Steven Ness]
+	| RHYTHM_SIM ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/GKC1.pdf PDF] || [http://www.ilsp.gr Aggelos Gkiokas], [http://www.ilsp.gr Vassilis Katsouros], [http://www.ece.ntua.gr/index.php?option=com_dep&task=profile&id=12&Itemid=62&lang=en George Carayannis]
+        |-
+        ! HKHLL1
+	| MARG_SIM1 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/HKHLL1.pdf PDF] || [http://11471178.net/ Byeong-jun Han], [http://marg.snu.ac.kr/people Kyogu Lee], [http://marg.snu.ac.kr/ Ziwon Hyung], [http://mvcube.net/ Hyunwoo Kim], [http://www.bonacell.com/ Sheayun Lee]
+        |-
+        ! ML1
+	| ML1 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/ML1.pdf PDF] || [http://www-cse.ucsd.edu/~bmcfee/ Brian McFee], [http://cosmal.ucsd.edu/~gert Gert Lanckriet]
+        |-
+        ! ML2
+	| ML2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/ML2.pdf PDF] || [http://www-cse.ucsd.edu/~bmcfee/ Brian McFee], [http://cosmal.ucsd.edu/~gert Gert Lanckriet]
+        |-
+        ! ML3
+	| ML3 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/ML3.pdf PDF] || [http://www-cse.ucsd.edu/~bmcfee/ Brian McFee], [http://cosmal.ucsd.edu/~gert Gert Lanckriet]
+        |-
+        ! PS1
+	| PS09 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/PS1.pdf PDF] || [http://www.ofai.at/~dominik.schnitzer Dominik Schnitzer], [http://www.cp.jku.at/ Tim Pohle]
+        |-
+        ! SSKS3
+	| cbmr_sim ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/SSKS3.pdf PDF] || [http://www.seyerlehner.info Klaus Seyerlehner], [http://www.cp.jku.at Markus Schedl], [http://www.cp.jku.at Peter Knees], [http://www.cp.jku.at Reinhard Sonnleitner]
+        |-
+        ! SSPK2
+	| cbmr_sim_2010 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/SSPK2.pdf PDF] || [http://www.seyerlehner.info Klaus Seyerlehner], [http://www.cp.jku.at Markus Schedl], [http://www.cp.jku.at Peter Knees], [http://www.cp.jku.at/ Tim Pohle]
+        |-
+        ! STBD1
+	| AMS2011_vario ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/STBD1.pdf PDF] || [http://www.atic.uma.es Simone Sammartino], [http://www.atic.uma.es Cristina de la Bandera], [http://www.atic.uma.es Lorenzo J. Tardón], [http://www.atic.uma.es Isabel Barbancho]
+        |-
+        ! STBD2
+	| AMS2011_multi ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/STBD2.pdf PDF] || [http://www.atic.uma.es Simone Sammartino], [http://www.atic.uma.es Cristina de la Bandera], [http://www.atic.uma.es Lorenzo J. Tardón], [http://www.atic.uma.es Isabel Barbancho]
+        |-
+        ! STBD3
+	| AMS2011_f0delta ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/STBD3.pdf PDF] || [http://www.atic.uma.es Simone Sammartino], [http://www.atic.uma.es Cristina de la Bandera], [http://www.atic.uma.es Lorenzo J. Tardón], [http://www.atic.uma.es Isabel Barbancho]
+        |-
+        ! YL1
+	| SC Learning ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/YL1.pdf PDF] || [http://www.cmlab.csie.ntu.edu.tw/~known/ Yin-Tzu Lin], [http://www.citi.sinica.edu.tw/pages/whcheng/index_en.html Wen-Huang Cheng], [http://www.cmlab.csie.ntu.edu.tw/cml/dsp/prof-wu/prof-wu.html Ja-Ling Wu]
+        |-
+        ! ZYC2
+	| SUMMs for AMS ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/ZYC2.pdf PDF] || [http://www.icst.pku.edu.cn/ Dongying Zhang], [http://www.icst.pku.edu.cn/ Deshun Yang], [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen]
+        |-
 	|}
@@ Line 94: / Line 131: @@
 === Reports ===
-'''BWL1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/BWL1/report.txt Dmitry Bogdanov, Joan Serrà, Nicolas Wack, Perfecto Herrera]<br />
+'''STBD1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/STBD1.results/report.txt Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho]<br />
-'''PS1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/PS1/report.txt Tim Pohle, Dominik Schnitzer]<br />
+'''STBD2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/STBD2.results/report.txt Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho]<br />
-'''PSS1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/PSS1/report.txt Tim Pohle, Klaus Seyerlehner, Dominik Schnitzer]<br />
+'''STBD3''' = [https://music-ir.org/mirex/results/2011/ams/statistics/STBD3.results/report.txt Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho]<br />
-'''RZ1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/RZ1/report.txt Rainer Zufall]<br />
+'''DM2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/DM2.results/report.txt Franz de Leon, Kirk Martinez]<br />
-'''SSPK2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/SSPK2/report.txt Klaus Seyerlehner, Markus Schedl, Tim Pohle, Peter Knees]<br />
+'''DM3''' = [https://music-ir.org/mirex/results/2011/ams/statistics/DM3.results/report.txt Franz de Leon, Kirk Martinez]<br />
-'''TLN1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/TLN1/report.txt George Tzanetakis, Mathieu Lagrange, Steven Ness]<br />
+'''GKC1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/GKC1.results/report.txt Aggelos Gkiokas, Vassilis Katsouros, George Carayannis]<br />
-'''TLN2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/TLN2/report.txt George Tzanetakis, Mathieu Lagrange, Steven Ness]<br />
+'''HKHLL1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/HKHLL1.results/report.txt Byeong-jun Han, Kyogu Lee, Ziwon Hyung, Hyunwoo Kim, Sheayun Lee]<br />
-'''TLN3''' = [https://music-ir.org/mirex/results/2011/ams/statistics/TLN3/report.txt George Tzanetakis, Mathieu Lagrange, Steven Ness]<br />
+'''ML1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/ML1.results/report.txt Brian McFee, Gert Lanckriet]<br />
+'''ML2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/ML2.results/report.txt Brian McFee, Gert Lanckriet]<br />
-== Run Times ==
+'''ML3''' = [https://music-ir.org/mirex/results/2011/ams/statistics/ML3.results/report.txt Brian McFee, Gert Lanckriet]<br />
-<csv>2011/ams/audiosim.runtime.csv</csv>
+'''PS1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/PS1.results/report.txt Dominik Schnitzer, Tim Pohle]<br />
+'''SSKS3''' = [https://music-ir.org/mirex/results/2011/ams/statistics/SSKS3.results/report.txt Klaus Seyerlehner, Markus Schedl, Peter Knees, Reinhard Sonnleitner]<br />
+'''SSPK2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/SSPK2.results/report.txt Klaus Seyerlehner, Markus Schedl, Peter Knees, Tim Pohle]<br />
+'''STBD1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/STBD1.results/report.txt Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho]<br />
+'''STBD2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/STBD2.results/report.txt Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho]<br />
+'''STBD3''' = [https://music-ir.org/mirex/results/2011/ams/statistics/STBD3.results/report.txt Simone Sammartino, Cristina de la Bandera, Lorenzo J. Tardón, Isabel Barbancho]<br />
+'''YL1''' = [https://music-ir.org/mirex/results/2011/ams/statistics/YL1.results/report.txt Yin-Tzu Lin, Wen-Huang Cheng, Ja-Ling Wu]<br />
+'''ZYC2''' = [https://music-ir.org/mirex/results/2011/ams/statistics/ZYC2.results/report.txt Dongying Zhang, Deshun Yang, Xiaoou Chen]<br />

Difference between revisions of "2011:Audio Music Similarity and Retrieval Results"

Latest revision as of 22:29, 21 October 2011

Contents

Introduction

General Legend

Team ID

Broad Categories

Understanding Summary Measures

Human Evaluation

Overall Summary Results

Friedman's Tests

Friedman's Test (FINE Scores)

Friedman's Test (BROAD Scores)

Summary Results by Query

FINE Scores

BROAD Scores

Raw Scores

Metadata and Distance Space Evaluation

Reports

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