Sound Data Management Training » History » Version 10

Steve Welburn, 2012-07-04 10:44 PM

1 5 Steve Welburn
h1. WP1.2 Online Training Material
2 1 Steve Welburn
3 7 Steve Welburn
(back to [[Wiki]])
4 7 Steve Welburn
5 9 Steve Welburn
{{>toc}}
6 9 Steve Welburn
7 1 Steve Welburn
h2. C4DM Researcher use cases
8 1 Steve Welburn
9 1 Steve Welburn
h3. Quantitative testing - machine testing
10 1 Steve Welburn
11 1 Steve Welburn
bq. A common use-case in C4DM research is to run a newly-developed analysis algorithm on a set of audio examples and evaluate the algorithm by comparing its output with that of a human annotator. Results are then compared with published results using the same input data to determine whether the newly proposed approach makes any improvement on the state of the art.
12 1 Steve Welburn
13 1 Steve Welburn
Data involved includes:
14 1 Steve Welburn
* Software for the algorithm (which can be hosted on "Sound Software":http://www.soundsoftware.ac.uk)
15 1 Steve Welburn
* An annotated dataset against which the algorithm can be tested
16 1 Steve Welburn
* Results of applying the new algorithm and competing algorithms to the dataset
17 1 Steve Welburn
* Documentation of the testing methodology
18 1 Steve Welburn
19 1 Steve Welburn
Note that *if* other algorithms have published results using the same dataset and methodology, then results should be directly comparable between the published results and the results for the new algorithm. In this case, the methodology is already documented.
20 1 Steve Welburn
21 1 Steve Welburn
Also, if the testing is scripted, then the code used would be sufficient documentation during the research - readable documentation only being at publication.
22 1 Steve Welburn
23 1 Steve Welburn
If no suitable annotated dataset already exists, a new dataset may be created including:
24 3 Steve Welburn
* Selection of underlying (audio) data (which may be [[Copyright|copyright]] material)
25 1 Steve Welburn
* Creation of ground-truth annotations for the audio and the type of algorithm (e.g. chord sequences for chord estimation, onset times for onset detection)
26 1 Steve Welburn
27 1 Steve Welburn
h3. Qualitative testing - Listening tests
28 1 Steve Welburn
29 2 Steve Welburn
An example would be testing audio at various levels of compression using both standard techniques and a newly derived algorithm.
30 1 Steve Welburn
31 6 Steve Welburn
e.g. [[MUSHRA]] type tests.
32 1 Steve Welburn
33 1 Steve Welburn
Data involved includes:
34 1 Steve Welburn
* Software for the algorithm (which can be hosted on "Sound Software":http://www.soundsoftware.ac.uk)
35 1 Steve Welburn
* Original uncompressed audio
36 1 Steve Welburn
* Audio output of the new algorithm on the audio
37 1 Steve Welburn
* Audio output of existing algorithms on the same audio
38 1 Steve Welburn
* Documentation of the testing methodology
39 1 Steve Welburn
40 1 Steve Welburn
We note that for listening tests, the research may involve:
41 1 Steve Welburn
* Demographic details of participants
42 3 Steve Welburn
* Identifiable participants (Data Protection])
43 3 Steve Welburn
* Release forms by people taking part
44 1 Steve Welburn
45 1 Steve Welburn
and *will* involve:
46 1 Steve Welburn
* ethics-board approval
47 1 Steve Welburn
48 1 Steve Welburn
h3. Publication
49 1 Steve Welburn
50 1 Steve Welburn
Additionally, publication of results will require:
51 1 Steve Welburn
* Summarising the results
52 1 Steve Welburn
* Publishing the paper
53 8 Steve Welburn
54 8 Steve Welburn
h2. Overarching concerns
55 8 Steve Welburn
56 8 Steve Welburn
Human participation - ethics, data protection
57 8 Steve Welburn
58 8 Steve Welburn
Audio data - copyright
59 10 Steve Welburn
60 10 Steve Welburn
Storage - where ? how ? SLA ?