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At first I was hesitant because of its handling of latex, but Rolf of Mathcination pointed out this excellent tool: latex-to-wordpress. So, from now on I will be updating my new blog, High Noon GMT.

Now that I am cleaning out my office after spending half a decade here, I thought it would be interesting to compile the statistics of my peer reviewing during that time.

I have reviewed 33 papers submitted to conferences, such as ICASSP, EUSIPCO, ISMIR, and DAFx. The rate at which I recommended acceptance is over 51%!

I have reviewed at least 18 articles submitted to journals, such as IEEE Trans. Audio, Speech Lang. Proc., IEEE Sig. Process., IEEE Sig. Process. Letts., IEEE Trans. Multimedia, J. New Music, Research, and EURASIP J. Audio, Speech and Music Process. My acceptance rate is a surprising 11%. I wonder if I am being too harsh; but a brief review of the articles I have rejected tell me "no." Furthermore, looking at the recommendations of the other reviewers, I see that I am not the only one of the other two or three who recommends rejection. (Some are also "reject but encourage resubmission." :)

I have reviewed four external Master's students (all pass!).

I have examined two PhDs (all pass!).

I have reviewed one book proposal.

I have reviewed two grant proposals (one advising against and one in support).

leonid-sabaneyev-250x375.jpgAcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts. AcousticBrainz has now analyzed over 1.2 million tracks, which makes it larger than the Million Song Dataset.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This female (0.75) instrumental (0.97) tonal (0.94) track is not a danceable (0.98) Viennese Waltz (0.93). Its mood is not electronic (0.85) but definitely acoustic (1.0), definitely not party (1.0), and most certainly not happy (0.99) but not necessarily sad (0.52). Its genre is definitely electronic (1.0) jazz (0.94) ambient (0.94) classical (0.71). This track has a last.fm tag! "Genre: Jazz".

It is the Anouar Brahem Trio playing "Halfaouine"

leonid-sabaneyev-250x375.jpgAcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This tonal (0.98) G minor track is instrumental (0.77), and not danceable (0.72) with a Tango rhythm (0.77). Its mood is acoustic (0.94), not aggressive (0.94), but not relaxed (0.67) and not party (0.72). It could be sad (0.62). Its genre is ambient (0.72) electronic (0.55) jazz (0.52).

Bert's Bossa Nova by Bert Kaempfert

leonid-sabaneyev-250x375.jpgAcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This acoustic (0.86) certainly classical (1.0) track is an instrumental (0.87) that is definitely not a danceable (1.0) Tango (1.0). It is in F major and atonal (0.98). It is not party (0.96), not aggressive (0.98), but relaxed (0.94) and maybe sad (0.6).

It's Blind John Davis playing "How Long Blues"

leonid-sabaneyev-250x375.jpgAcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This is a C-major track that is again atonal (0.92), not danceable (0.96) but definitely with a Tango rhythm (1.0). It is a male (0.64) voice track (0.88). Its mood is not party (0.94), and not aggressive (0.96) but not relaxed (0.93), and happy (0.91) but maybe sad (0.63). It is likely to be classical (0.96) and/or ambient (0.8).

It is a classic Yiddish song, an excerpt of which can be heard here.
leonid-sabaneyev-250x375.jpgAcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

Here we got a C-minor tonal (0.97) track with a tempo of 164 beats per minute. It is instrumental (0.62) and female (0.74), not danceable (0.98) but maybe a Viennese Waltz rhythm (0.52). It has an acoustic mood (0.97) and is not aggressive (0.96) and not electronic (0.72). Definitely not happy (0.98) and not party (1.0), but relaxed (0.98) and sad (0.75). It is quite likely to be electronic (1.0) ambient (0.95) jazz (0.91) classical (0.76) It is "Nicht streb', o Maid" from Richard Wagner's Die Walk├╝re (Act 3, Scene 3)! Apparently, it comes from this release.
leonid-sabaneyev-250x375.jpgAcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This track is most certainly an undancable (1.0) instrumental (1.0) in D minor with dark (0.99) and atonal (0.95) ChaChaCha rhythms (0.85). Its mood is electronic (0.98), and there is no doubt it is not party (1.0) and not aggressive (1.0). It is probably not acoustic (0.90) either, and not happy (0.79) and not sad (0.87) but relaxed (0.80) and possibly aggressive (0.62). Its genre according to some is electronic (0.98) ambient (0.8), but could possibly be hip hop (0.34) jazz (0.31).

Weird Al Yankovic singing "Jerry Springer"

AcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This C# major track is certainly atonal (1.0), and is probably voice (0.94), maybe female (0.62), but absolutely danceable (1.0) with a ChaChaCha rhythm (0.5). It's timbre is dark (0.99). Its mood is electronic (0.98) and not acoustic (0.90), and definitely aggressive (1.0) and not party (1.0). Curiously, it is not happy (0.99) but not sad (0.93), and probably relaxed (0.81). It is most assuredly jazz (1.0), but could also be called electronic (0.89) rock (0.85) trance (0.35) house (0.32). Some of its last.fm genre tags are, "90S" and 20Th Century".

"Ulcer" by Swedish death metal band Comecon.
AcousticBrainz aims to automatically analyze the world's music, in partnership with MusicBrainz and "provide music technology researchers and open source hackers with a massive database of information about music." This effort is crowd sourced neatness, which means people from all over the world are contributing data by having their computer crunch through their MusicBrainz-IDed music libraries and automatically uploading all the low-level features it extracts.

I construct today's review from low- and high-level data recently extracted from a particular music track AcousticBrainz. Can you guess what it is? What characteristics it has? ("Probabilities" are in parentheses.) The answer will be revealed below tomorrow.

This instrumental (0.91) but not acoustic (0.73) track in the key of F major is certainly atonal (1.0), and likely male-gendered (0.89). It is most definitely not danceable (1.0), but also has a Tango rhythm (0.995). Its mood is electronic (0.92) party (0.64), and is definitely happy (1.0) but maybe relaxed (0.81) and might be sad (0.6). It is probably ambient (0.89) and/or blues (0.80), but could also be classical (0.45) and/or hip hop (0.38).

"The Love Scene" from Dracula (the movie) by John Williams