similar to: Realtime resampling/encoding with oggenc

Hi. I'm wondering if anyone out there can give me a little help trying to figure something out: I presently am running CentOS4.1 with GNOME as my desktop (It runs quite well, I must say!). I just have a little curiosity: I have a few audio files (.wav, .mp3 and .ogg) and I like to "preview" them. When run my mouse over the .wav files (and mp3 files) the

Hi, Can someone please comment about the below issue [root at host0040 kaushal]# file obd-demo.mp3 obd-demo.mp3: MPEG ADTS, layer III, v1, 256 kBits, 44.1 kHz, Monaural [root at host0040 kaushal]# sox obd-demo.mp3 -e stat sox: Failed reading obd-demo.mp3: Do not understand format type: mp3 [root at host0040 kaushal]# sox -V obd-demo.mp3 -r 8000 -c 1 -t ul -w vm-intro.ulaw sox: Failed reading

One thing that has always bothered me about the ogg format is the distortion of high frequency sounds - even at data rates as high 128 and 160 kbps. I find the best way around this is to resample the wav file to 48 kHz (using SoundForge 6.0) before encoding (using CDex) to ogg. It takes a while, and adds a lot of extra wear and tear on my drive, but what a difference! The result is an 80k ogg file

Will oggenc have a lowpass switch? I would prefer to lowpass at 15-16khz at -q3 for use with FM broadcasting. The additional frequencies would be chopped off anyway by the transmiters hardware lowpass filter so the encoder could use the addition bits for other purposes. It could be enforced that the lowpass can only be reduced and not increased from the default. This would stop people

Hi, Can someone please comment about the below issue [root at host0040 kaushal]# file obd-demo.mp3 obd-demo.mp3: MPEG ADTS, layer III, v1, 256 kBits, 44.1 kHz, Monaural [root at host0040 kaushal]# sox obd-demo.mp3 -e stat sox: Failed reading obd-demo.mp3: Do not understand format type: mp3 [root at host0040 kaushal]# sox -V obd-demo.mp3 -r 8000 -c 1 -t ul -w vm-intro.ulaw sox: Failed reading

After doing an informal (128k) listening test, I have concluded that I prefer Beta4 over RC2. The 16kHz low-pass on the RC2 encoder makes it sound like FM radio. Both encoders SEEM to have a couple of dB bump at 10kHz. JT --- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project homepage: http://www.xiph.org/ogg/ To unsubscribe from this list, send a message to

I'm on Centos 5.5, and would like to use sox to strip out any periods of silence > 5 seconds from a batch mp3 audio files. Googling I found sox, but it does not seem to support mp3 files by default. The man page says: .mp3 MP3 Compressed Audio MP3 audio files come from the MPEG standards for audio and video compression. They are a lossy compression format that achieves

Dr. Williams, I ran across your inquiry on one of the R-help mailing lists regarding digital filter design and implementation. I found no response to your email in the archives and was wondering if you were able to find anything. Thanks, Israel -- Israel Christie, Ph.D. Email: ichristie at gmail.com Phone: 865.766.0214 Mobile: 865.406.4615

Hi, I'm not anywhere near an expert, but I had successfully used Darkice, TwoLame, and Icast231 to netcast a mp2 stream. If it will help, here is a snip from the related area of my darkice.cfg: [icecast2-1] format = mp2 bitrateMode = cbr bitrate = 384 quality = 1.0 server = 127.0.0.1 port = 32710 password = (duh!) sampleRate =

I want to use caret to build a model with an algorithm that actually has no parameters to find. How do I stop it from repeatedly building the same model 25 times? library(caret) data(mdrr) LOGISTIC_model <- train(mdrrDescr,mdrrClass ,method='glm' ,family=binomial(link="logit") ) LOGISTIC_model 528

Dear All, I was writing a small wrapper to bootstrap a classification algorithm, but if we generate the indices in the "usual way" as: bootindex <- sample(index, N, replace = TRUE) there is a non-zero probability that all the samples belong to only one class, thus leading to problems in the fitting (or that some classes will end up with only one sample, which will be a problem

A while ago someone asked about a low-pass filter for oggenc and was told to get AFsp and filter outside of Oggenc. Well, I got it, and am totally lost (It's way more complicated than SOX) so now can anyone briefly describe what type of filter I should set up (FIR, IIR, all-pole), why one is better than the other, and if you have filter coefficient files lying around (lowpass, 19 or 20 kHz

Hi, maybe this is of interest for someone out there. I found that taking the difference between an original sample and its decoded Vorbis counterpart is a cool way to mangle sounds (especially voice samples get a nice weird touch :] ). A side effect is that the result is not only exactly what information the encoder omits, it also contains things that it adds to the sample (artifacts). Leaving

Max and List, Could you advise me if I am using the proper caret syntax to carry out leave-one-out cross validation. In the example below, I use example data from the rda package. I use caret to tune over a grid and select an optimal value. I think I am then using the optimal selection for prediction. So there are two rounds of resampling with the first one taken care of by caret's train

Hi, I'm doing some modelling (lm) for my 3rd year dissertation and I want to do some resampling, especially as I'm working with microbes, getting them to evolve resistance to antimicrobial compounds, and after each exposure I'm measuring the minimum concentration required to kill them (which I'm expecting to rise over time, or exposures), I have 5 lineages per cleaner, and

Hi, I have a time series (say "x") of 13 years showing an evident increase. I want to exclude two observations (the fourth and 10th), so I do: > trend.test(x[-c(4,10)]) where: > x[-c(4,10)] [1] 7 37 79 72 197 385 636 705 700 1500 1900 and I get: Spearman's rank correlation rho data: x[-c(4, 10)] and time(x[-c(4, 10)]) S = 4, p-value < 2.2e-16

From Sept. 25 Oct. 23, Dr. Philip Good, a former traveling lecturer for the American Statistical Association, will be giving an online seminar on practical applications of the bootstrap and permutation tests. During this 4-week internet seminar, hosted by statistics.com, participants will do interval estimation, one- , two- and k-sample comparisons, correlation, and a number of other

Hi, I have a time series (say "x") of 13 years showing an evident increase. I want to exclude two observations (the fourth and 10th), so I do: > trend.test(x[-c(4,10)]) where: > x[-c(4,10)] [1] 7 37 79 72 197 385 636 705 700 1500 1900 and I get: Spearman's rank correlation rho data: x[-c(4, 10)] and time(x[-c(4, 10)]) S = 4, p-value < 2.2e-16

Hi, I'm trying to write a code (see below) to randomly resample measurements of one variable (say here the variable "counts" in the data frame "dat") with different resampled subsample sizes. The code works fine for a single resampled subsample size (in the code below = 10). I then tried to generalize this by writing a function with a loop, where in each loop the function

Hello all R-er, I'm trying to run a resampling method on some data. The current method I have takes 2+ days or a lot of memory . I was wondering if anyone has a better suggestion. Currently I take a matrix and get the correlation matrix from it. This will be called rho.A. Each element in this will be tested against the distribution from the resampled correlation B matrix. Some example