Computer Science
Sound Representation
Sound representation refers to the digital encoding of audio signals for storage, transmission, and processing. In computer science, sound representation involves converting analog sound waves into a digital format using techniques such as pulse code modulation (PCM) or other encoding methods. This allows computers to manipulate and play back audio data.
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4 Key excerpts on "Sound Representation"
eBook - PDF- Julio d'Escriván(Author)
- 2011(Publication Date)
- Cambridge University Press(Publisher)
Chapter 1 Representing and storing sound In this chapter we will describe the basic physics of sound and what an audio signal is. We will look at how we work out sound levels and, in simple terms, some of the maths behind that. We also discuss digital recording and therefore sampling. We describe different ways of representing sound and the way we perceive different frequencies. Finally, we discuss the capture and storage of sound as computer data and the most common standards for carrying digital audio. Physics of sound: the audio signal What is sound? First, a problem: to study sound properly, it would be really useful to be able to represent it visually. But sound is, well . . . sound, a sensation for the ears. When we are able to see sound, what we see is how sound affects other things: the mythical soprano who breaks a wine-glass with a high-pitched warble, or the rippling wave patterns on the surface of a metal plate on top of a loudspeaker. In the same way, to represent sound graphically we need to show how one or more of its characteristics can be visualised. It may be how its amplitude changes over time, or how the different frequencies present in the sound change over time, or, to complicate things slightly, it can be to show how loud those different frequencies are in comparison to one another. Although this is not a book on acoustics, let’s for a minute look at what sound contains that may be useful to represent visually for our purposes. Sound is a phenomenon. This means it is something we perceive, in this case, through our sense of hearing and, in fact, through our whole body (which you will know if you have been to any concerts of drone electronica!). Sound is, in fact, what we call the sensation produced by changes in air pressure as they are perceived through our whole body and more specifically through our ears. These changes are in turn generated by the interaction between a number of objects that excite each other into motion.
eBook - PDFDigital Media Processing
DSP Algorithms Using C
- Hazarathaiah Malepati(Author)
- 2010(Publication Date)
- Newnes(Publisher)
Other audio signals include machine/electronic sounds, vehicle horns, bird sounds, and so on. Audio signals are compressed using the characteristics of the human auditory system and data compression techniques. Audio compression techniques are discussed in Chapter 13. Speech signals can be considered a subset of audio signals. Speech signals contain information about the time-varying characteristics of the excitation source and the vocal tract system. Speech signals are nonstationary and at best they can be considered quasistationary over short time periods (typically 10 to 30 ms). The spectral properties of speech are thus defined over short segments. Resolution in both the temporal and spectral domains is essential for extracting the characteristics of speech signals. Speech can generally be classified as voiced, unvoiced, or mixed. Voiced speech is quasiperiodic in the time domain and harmonically structured in the frequency domain, while unvoiced speech is random-like in the time domain and occupies a broad spectrum in the frequency domain. Speech signals contain significant energy, from 200 Hz to 3.2 kHz. As mentioned previously, these signals are compressed using the characteristics of the human speech production system and auditory system, and data compression techniques. Various speech processing and compression algorithms are briefly addressed later in this chapter. 12.2 Digital Representation of Audio Signals Assuming that we have already converted sound energy into electrical energy, the next step is to digitize the analog signals. Because audio itself is analog in nature, digital systems employ sampling and quantization to convert the analog audio into digital audio. 12.2.1 Sampling and Quantization A digital representation expresses the audio signals as a sequence of symbols, usually binary numbers. This permits signal processing using digital circuits such as DSP processors and computers .
eBook - PDFThe Haskell School of Music
From Signals to Symphonies
- Paul Hudak, Donya Quick(Authors)
- 2018(Publication Date)
- Cambridge University Press(Publisher)
18 Sound and Signals In this chapter we study the fundamental nature of sound and its basic mathematical representation as a signal. We also discuss discrete digital representations of a signal, which form the basis of modern sound synthesis and audio processing. 18.1 The Nature of Sound Before studying digital audio, it’s important that we first know what sound is. In essence, sound is the rapid compression and relaxation of air traveling as a wave from the physical source of the sound ultimately to our ears. The source could be the vibration of our vocal cords (resulting in speech or singing), the vibration of a speaker cone, the vibration of a car engine, the vibration of a string in a piano or violin, the vibration of the reed in a saxophone or someone’s lips when playing a trumpet, or even the (brief and chaotic) vibrations that result when our hands come together as we clap. The “compression and relaxation” of the air (or of a coiled spring) is called a longitudinal wave, in which the vibrations occur parallel to the direction of travel of the wave. In contrast, a rope that is fixed at one end and being shaken at the other and a wave in the ocean are examples of a transverse wave, in which the rope’s or water’s movement is perpendicular to the direction the wave is traveling. If the rate and amplitude of the sound are within a suitable range, we can hear it – i.e., it is audible sound. “Hearing” results when the vibrating air waves cause our eardrum to vibrate, in turn stimulating nerves that enter our brain. Sound above our hearing range (i.e., vibration that is too quick to induce any nerve impulses) is called ultrasonic sound, and sound below our hearing range is said to be infrasonic. 262 18.1 The Nature of Sound 263 –1 –0.5 0 0.5 1 0 0.002 0.004 0.006 0.008 0.01 Amplitude Time (seconds) Sine Wave at 1,000 Hz Signal Figure 18.1 A sine wave.
eBook - PDF- Nigel Chapman, Jenny Chapman(Authors)
- 2014(Publication Date)
- Wiley(Publisher)
Pohlmann’s comments † about the nature of sound and its reproduction should be borne in mind: “Given the evident complexity of acoustical signals, it would be naïve to believe that analog or digital technologies are sufficiently advanced to capture fully and convey the complete listening experience. To complicate matters, the precise limits of human perception are not known. One thing is certain: at best, even with the most sophisticated technology, what we hear being reproduced through an audio system is an approximation of the actual sound.” Digitizing Sound The digitization of sound is a fairly straightforward example of the processes of quantization and sampling described in Chapter 2. Since these operations are carried out in electronic analogue- to-digital converters, the sound information must be converted to an electrical signal before it can be digitized. This can be done by a microphone or other transducer, such as a guitar pickup, just as it is for analogue recording or broadcasting. Increasingly, digital audio, especially music, is stored in files that can be manipulated like other data. In particular, digital audio files can be stored on servers and downloaded or distributed as “podcasts” (see Chapter 16). Digital audio players, such as Apple’s iPod, store such files on their internal hard disks or flash memory. Almost always, audio in this form is compressed. † Ken C. Pohlmann, Principles of Digital Audio, p. 5. 295 DIGITIZING SOUND CHAPTER 8 Contemporary formats for digital audio are influenced by the CD format, which dominated audio for over two decades. For instance, the sampling rate and number of quantization levels used for high-quality audio is almost always the same as that used for CD.
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