Section 25 Always Now Raritan' title='Section 25 Always Now Raritan' />How to Start Your Own Podcast. The podcast craze of the past several years shows no signs of slowing down, and while every armchair broadcaster with a voice recorder app is eager to get in the game, creating a professional sounding podcast isnt as simple as it might seem. Heres how to create, record, and publish your own basic podcastand get people to listen. This story originally ran in June 2. August 2. 01. 7 with additional reporting from Patrick Austin. You Start, Be Ready to Commit. Before you rush into things, its important to keep in mind that podcasts take a lot of effort to get going. Theyre not just recordings of people talking not the good ones, anyway. Pat Flynn, host of the Smart Passive Income podcast, recommends you treat podcasting the same way you would any other big project Podcasting is extremely fun and exciting, but there is one thing you must do before you start podcasting Commit. You must internally commit to podcasting, as you must do with anything that is potentially beneficial but takes some time and effort to do. Its easy to assume that podcasts are easy to produce because theyre audio only, but dont be fooled. They can take up a lot of time to put together, especially at first. Also, podcasts do best when theyre released consistently. If youre interested in developing any kind of listener base, you have to be ready to release episodes on a regular basis. All in all, podcasting can be fun work, but its still work and should be treated as such. You also shouldnt expect to get rich from podcasting either. Its certainly possible to generate income from podcasting, but that usually requires advertisements and sponsorshipsboth of which youll get after youve built up a listenership big enough to make it worthwhile to advertisers. If youre not interested in starting a podcast for the fun of it or to have your voice heard, you might not get much out of it unless you already have an audience. What Youll Need. Primordial late 60s Detroit rock from SRC at the time thought of as the chief rival of the now much more reverently remembered MC5 but still a piledriving. Torrentz domain names are for sale. Send an offer to contactinventoris. Got scammed by some ebay seller, and want to fix your hacked key to its default memory to prevent data corruption on your memory stick. Well here is a simple step by. You cant start a podcast without equipment, and good equipment will go a long way. Heres what youll need Microphones Any microphone will work for recording your podcast, but listeners can usually tell the difference between low and high quality microphones. If youre not sure what to look for, our list of the five best desktop microphones is a great place to start I use four analog Audio Technica AT2. As you shop around, youll also need to decide whether you want to use a USB or analog XLR microphone. USB mics convert analog sound into digital so you can plug a USB mic directly into any computer and start recording without much hassle, but you could potentially get lower audio quality compared to analog. Considering you dont need any extra tools or devices to record with a USB mic, they can be a little cheaper in the long run. Section 25 Always Now Rar FilesAnalog microphones use XLR connectors, which means you need another device to get your audio onto your computer, but you can get higher audio quality and can use them with other sound equipment if you had a PA system or wanted to play live music, for example. Of course, if you have a gaming headset or other basic microphone around, you can easily use that too. Portable XLR Recorder optional If you plan on using analog microphones for your podcast, youll need something that captures your analog audio and converts it to digital. The Battle of Long Tan 18 August 1966 took place in a rubber plantation near Long Tan, in Phuoc Tuy Province, South Vietnam during the Vietnam War. Portable XLR recorders can capture multiple microphone channels and allow you to do basic sound level adjusting and muting on the fly. Audio files automatically get organized and stored on a memory card that you can insert into a card reader or slot in your computer. These are amazing tools, but they can be expensive. You can find them for anywhere between 1. I use a 4. 00 Zoom H6 Handy Recorder with four available analog channels. Audio Interface optional If you want to record directly to your computer with your analog microphones, youll need an audio interface. These devices allow you to plug in one or more analog microphones and will convert the analog audio to digital. Most audio interfaces will connect to your computer via USB or Firewire. Audio interfaces can cost as little as 3. You can see why a USB microphone is a cheaper option. A Computer Any Windows computer or Mac should work fine to record, edit, and upload your podcast. Thankfully, editing audio doesnt take a ton of computing power. Additionally, depending on how you choose to recorddirectly to the computer or onto a dedicated recording deviceyour computer will also need the right ports. USB microphones, for example, will obviously need an open USB port. If youre using analog microphones with a portable XLR recorder or audio interface device, youll need either a 3. USB port, or in some cases, a Firewire port. So before you spend any money on equipment, make sure you have a computer that can support it. Audio Editing Software For the actual recording and editing, youll need a Digital Audio Workstation or DAW, there are a lot of good options out there, but the licenses for some of them can cost a pretty penny, though. Licenses for professional level DAWs like Reason or Pro Tools can cost anywhere between 3. Apps like Hindenburg offer simpler audio editing software for under 1. Reaper is a fully loaded audio production app for 6. Adobes audio editing software Audition CC is available with a 1. Because of that, most people will recommend free open source programs like Audacity when youre just getting started, and thats what well use an example throughout this how to guide. Pop Filters optional The clearer your audio can sound, the better. Pop filters, while not required, are fairly cheap and can keep your plosives from making a nasty sound on your recording. If you dont want to buy any, though, you can make some of your own. You might be thinking that all this equipment is pretty expensive, and youre not wrong. However keep in mind that decent audio equipment will last forever if you take care of it. It may be expensive to get started, but after the initial purchase, youre set. Step One Narrow Your Topic and Find Your Niche. Just like blogs, there are a ton of podcasts out there. That means that you can probably find a podcast about everything under the sun already. Dont get discouragedWhile just about every broad topic is already covered, you just have to find your spin on things to make an old idea something new. Dear Lifehacker, As a side projectexperiment, Ive started my own blog. The problem is, now that I Read more Read. For example, if you wanted to make a podcast about music, ask yourself if theres an audience out there for what you want to talk about. Maybe you narrow your idea down from music in general to bluegrass specifically. Now your coverage is specific the music, people, and culture of bluegrass. Once you have your topic narrowed down, it helps to add a spin to it. Maybe you talk about bluegrass music and culture while sipping moonshine with your co hosts. Its kind of true that everything has been done before, but it hasnt all been done the way you would do it. So find an angle thats personally interesting and youll be better off. Step Two Download, Install, and Set Up Audacity. As mentioned earlier, Audacity is a great DAW for podcasting beginners. Its open source, free to use as long as you like, and is available for Windows, OS X, and Linux. Before you can jump into recording, however, there are a few tricks to getting it all set up properly Download Audacity 2. Data Compression Explained. Matt Mahoney. Copyright C 2. Dell, Inc. You are permitted to copy and distribute material from this book provided 1 any. These restrictions do not. This book may be downloaded without charge from. Last update Apr. Alejo Sanchez, Oct. Kindle and. epub other readers. About this Book. This book is for the reader who wants to understand how data compression works. Prior programming ability and some. Specific topics include 1. Information theory. Benchmarks. 3. Coding. Modeling. Fixed order bytewisebitwise, indirect. Variable order DMC, PPM, CTWContext mixing linear mixing. SSE. indirect SSE, match, PAQ. Crinkler. 5. Transforms. RLELZ7. 7 LZSS. deflate, LZMA, LZX, ROLZ, LZP, snappy, deduplicationLZW and dictionary encoding. Symbol ranking. BWT context sorting, inverse, b MSuf. Sort v. 2 and. BijectivePredictive filtering delta coding. Specialized transforms E8. E9. precompHuffman pre coding. Lossy compression. Images BMP. GIF, PNG, TIFF. MPEGAudio CD, MP3, AAC, Dolby, VorbisConclusion. Acknowledgements. References. This book is intended to be self contained. Sources are linked when appropriate. Information Theory. Data compression is the art of reducing the number of bits needed to store or transmit. Compression can be either lossless or lossy. Losslessly compressed data can. An example is 1. 84. Morse Code. Each letter of the alphabet is coded as a sequence of dots and. The most common letters in English like E and T receive the shortest codes. The least common like J, Q, X, and Z are assigned the longest codes. All data compression algorithms consist of at least a model and a coder with optional. A model estimates the probability distribution E is more. Z. The coder assigns shorter codes to the more likely symbols. There. are efficient and optimal solutions to the coding problem. However, optimal modeling. Modeling or equivalently, prediction is both an. AI problem and an art. Lossy compression discards unimportant data, for example, details of an image. An example is the 1. NTSC standard for broadcast color. TV, used until 2. The human eye is less sensitive to fine detail between colors. Thus, the color signal is transmitted with less resolution over a narrower frequency. Lossy compression consists of a transform to separate important from unimportant. The transform is an AI problem because it requires understanding what the. Information theory places hard limits on what can and cannot be compressed losslessly. There is no such thing as a universal compression algorithm that is guaranteed. In particular, it. Given a model probability distribution of your input data, the best you can do. Efficient and. optimal codes are known. Data has a universal but uncomputable probability distribution. Specifically, any. M where M is the shortest possible. M is the length of M in bits, almost independent of the. M is written. However there is no general procedure for finding. Teaching Methodology Questions Pdf there. M or even estimating M in any language. There is no algorithm that tests for randomness. No Universal Compression. This is proved by the. Suppose there were a compression algorithm that could. There are exactly. A universal compressor would. Otherwise, if two inputs compressed to the. However there are only 2n 1 binary strings shorter than n bits. In fact, the vast majority of strings cannot be compressed by very much. The fraction. of strings that can be compressed from n bits to m bits is at most 2m n. For example, less than 0. Every compressor that can compress any input must also expand some of its input. However, the expansion never needs to be more than one symbol. Any compression algorithm. The counting argument applies to systems that would recursively compress their own. In general, compressed data appears random to the algorithm that compressed. Coding is Bounded. Suppose we wish to compress the digits of, e. Assume our model is that each digit occurs with probability 0. Consider 3 possible binary codes. Digit BCD Huffman Binary. Using a BCD binary coded decimal code, would be encoded as 0. Spaces are shown for readability only. The compression ratio is 4. If the input was ASCII text, the output would be compressed. The decompresser would decode the data by dividing it into 4 bit strings. The Huffman code would. The decoder would read bits one at a time. The code is uniquely decodable because no code is a prefix of any other code. The compression ratio is 3. The binary code is not uniquely decodable. For example, 1. 11 could be decoded as. There are better codes than the Huffman code given above. For example, we could. Huffman codes to pairs of digits. There are 1. 00 pairs each with probability. We could assign 6 bit codes 0. The average code length is 6. Similarly, coding groups of 3 digits using. Shannon and Weaver 1. In this example, log. Shannon defined the expected information content or equivocation. X as its expected code length. Suppose X may. have values X1, X2. Xi has probability. Then the entropy of X is HX Elog. X i. pi log. For example, the entropy of the digits of, according. There is no smaller. The information content of a set of strings is at most the sum of the information. If X and Y are strings, then HX,Y HX. HY. If they are equal, then X and Y are independent. Knowing one string. The conditional entropy HXY HX,Y HY is the information content. X given Y. If X and Y are independent, then HXY HX. If X is a string of symbols x. X may be expressed as a product of the sequence of symbol predictions conditioned. X i pxix. 1. Likewise, the information content HX of random string X is the sum of the conditional. HX i. Hxix. Entropy is both a measure of uncertainty and a lower bound on expected compression. The entropy. of an information source is the expected limit to which you can compress it. There are efficient coding. It should be emphasized, however, that entropy can only be calculated. But in general, the model is not known. Modeling is Not Computable. We modeled the digits of as uniformly distributed and independent. Given that. model, Shannons coding theorem places a hard limit on the best compression that. However, it is possible to use a better model. The digits of. are not really random. The digits are only unknown until you compute them. An intelligent compressor might recognize the digits of and encode it as a. With our previous model, the best we could do is 1. Yet, there are very small programs. The counting argument says that most strings are not compressible. So it is a rather. English text. images, software, sensor readings, and DNA, are in fact compressible. These strings. generally have short descriptions, whether they are described in English or as a. C or x. 86 machine code. Solomonoff 1. 96. Kolmogorov 1. 96. Chaitin 1. 96. 6 independently proposed. The. algorithmic probability of a string x is defined as the. L that output x, where each program. M is weighted by 2 M and M is the length of M in bits. This probability. We call this length the. KLx of x. Algorithmic probability and complexity of a string x depend on the choice of language. L, but only by a constant that is independent of x. Suppose that M1 and M2 are encodings. L1 and L2 respectively. For example, if L1 is C, then M1 would. C that outputs x. If L2 is English, the M2 would be a description. Now it. is possible for any pair of languages to write in one language a compiler or interpreter. For example, you could write a description.