Hugo Fastl Eberhard Zwicker. Psychoacoustics. Facts and Models. With Figures and. 53 Psychoacoustics Demonstrations on CD-ROM. ABC. Psychoacoustics – Facts and Models offers a unique, comprehensive summary of DRM-free; Included format: PDF; ebooks can be used on all reading devices. Hugo Fastl Eberhard Zwicker. Psychoacoustics. Facts and Models. With Figures and. 53 Psychoacoustics Demonstrations an CD-ROM. Springer.
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superior English sources were avail- able to me. There was the wonderful review on valence theory by Van Vleck and Albert Sherman in. Sound quality and psychoacoustics have many aspects in common, since Since psychoacoustic models have been described in detail in the literature . Zwicker, E., Fastl, H. () Psychoacoustics - Facts and Models, 2nd. Ed., Springer. Fastl H., Zwicker E. Psychoacoustics. Facts and Models. Файл формата pdf; размером 11,23 МБ. Добавлен пользователем kba
The application of psychoacoustical models plane eg. They suggest this due to the fact that the more 3], voice quality analysis , audio system modeling , audio common use of lower-level auditory dimensions pitch, loudness data rate compression , room acoustics, and indeed to auditory and timbre interact with each other to such a level that they often display.
Within auditory display, psychoacoustical modeling could may confuse the user of the display. They argue that this technique be used in a similar fashion to the sound quality field with model allows the listener to develop robust mental models they can then results being used to refine candidate sounds for a display under associate with the target dimension.
Used in this worthwhile to attempt to measure interaction directly and control manner, psychoacoustical modeling should be of substantial ben- it.
However, to do this requires the assumption that lower-level efit in developing displays that are easy to interpret and pleasant auditory phenomena can be classified, generalised and modeled to listen to. More ambitiously, psychoacoustical modeling could using the techniques that Zwicker and Fastl outline. Whilst the be applied directly in the generation of multidimensional auditory accuracy of their models is open to debate, and improvements to graphs.
If the psychoacoustical models are truly reliable, then this these models continue to be made, their thrust is to indeed classify approach to auditory graphing should succeed, notwithstanding and model to a specified level of generality the lower levels of cognitive limitations. The fact that this approach is not widely auditory sensation. Therefore they may offer a solution to some adopted can be attributed to several factors, most notably the diffi- of the interaction problems Neuhoff and Heller outline.
Figure 1 culty in implementing psychoacoustical modeling and synthesis. Indeed, loudness is perhaps the most fundamental of au- Loudness Pattern ditory sensations and it is likely that existing auditory displays al- Sum area The total loudness can be ready manipulate loudness, even if they seek to maintain a constant Sones underneath acoustic output.
Thus this manipulation of loudness may be a Curve Total confound in the intended simplicity of a display. Loudness The loudness model process outlined in Figure 2 involves several stages, which often relate to the way in which the ear processes sound to stimulate the auditory nerve.
The output of auditory models is used primarily in loudness modelling, but also Figure 2: The analysis stages in a typical loudness model. In terms of its relation to signal parameters, loudness is affected by the predominant frequency of a signal eg. Music-like component or noise band , the signal bandwidth, signal duration sources, which are often used for auditory graphing, are between in the case of brief signals, of less than ms , amongst others.
Arbitrary signals may be difficult to parameterise in these terms, This paper is not about a particular auditory display, but ex- and so are good candidates for full loudness modeling. In some amines the issues around the application of psychoacoustics to circumstances, doubling or halving of loudness corresponds to a auditory graphing.
It develops this idea through an overview of 10 dB gain interval — however, this rule of thumb does not apply psychoacoustical modeling, and by way of example. The term to low frequency or quiet sounds. The present paper is concerned with can occur where increased sound pressure level is accompanied by the part of psychoacoustics that develops and employs quantitative decreased loudness.
Hence, signal gain may be used to roughly models of auditory perception. The scope of this paper is limited control loudness, but a loudness model is required if loudness is to and is concerned primarily with an outline of the various psychoa- be well controlled for a variety of signals. More precisely defined, it is a representation style of sonification.
The auditory filter scale units are 2. The In this section we briefly review the psychoacoustical models of specific loudness pattern, especially in its time-varying form, is the loudness, sharpness, roughness, fluctuation strength and pitch.
Loudness 2. Sharpness or brightness is one of the most prominent features The models draw on data gained from subjective testing and from a of timbre . Models are based on the centroid, whether it be physiological understanding of the auditory periphery.
The unit of of the signal spectrum , or the specific loudness pattern [19, loudness, the sone, is a ratio scale referenced against the sensation 1, 20]. Following Zwicker and Fastl, sharpness is modeled as a produced by a 1 kHz sine tone with a sound pressure level of 40 weighted centroid of the specific loudness pattern.
Its unit is the dB. Sharpness is a musical term often used to describe a sound with The roughness of auditory stimuli can be manipulated through a pitch slightly higher than a target pitch.
This is strongly influences such as loudness and carrier spectral content. Again, the dependency upon frequency content will have the 2.
Fluctuation Strength implication that most displays will use signals of varying sharp- Fluctuation strength describes a sensation caused by relatively slow ness in a fairly uncontrolled way. For harmonic tones, sharpness amplitude modulation within auditory filters with maximum sen- can be roughly controlled through the distribution of the harmonic sitivity at around 4 Hz.
It is easy to appreciate that the perception spectral envelope, although a sharpness model is required for scal- of the degree to which a sound is fluctuating should increase with ing.
As observed by Zwicker and Fastl, fluctuation strength know as critical band rate and g z is a weighting function that appears to be related to speech, since its amplitude modulation emphasises z for high critical band rates.
The unit of fluctuation strength is the vacil, 2. Roughness is a sensation caused by quite rapid amplitude modu- The model used by Zwicker and Fastl for calculating the fluc- lation within auditory filters.
This modulation can be caused by tuation strength of tones is summarised by Equation 3. Like the beats between two pure tone components, or by a signal with am- simple roughness model, this fluctuation strength model is based plitude or frequency modulation.
Beating within an auditory filter on the fluctuation of the excitation pattern of the ear. According to Zwicker Zwicker and Fastl also refer to a general model of fluctua- and Fastl, maximum roughness is often achieved for modulation tion strength, structured similarly to the general roughness model frequencies around 70 Hz depending on the carrier frequency.
They present as a parameter for auditory alerts. Pulse rate is often used to a set of simple models of roughness associated with a single known indicate levels of urgency in auditory alert systems . Pitch filter. This uses the time-varying excitation pattern of the ear sim- A psychoacoustical pitch ratio scale is an elusive concept because ilar to the specific loudness pattern, except that the magnitude is in of the complexity of pitch perception and cognition.
Even though many fre- Psychoacoustic quencies are present in a harmonic tone, usually the fundamental Parameter 1 frequency dominates as the pitch percept. When the fundamental Psychoacoustic frequency is masked or completely absent, the fundamental as a Parameter 2 pitch percept tends to remain.
Models of pitch perception account normalized so as to reveal and simplify for this phenomenon either explicitly through template matching representation of  or implicitly through autocorrelation .
Parncutt has ex- Parameter 1 plained many aspects of musical harmony through this psychoa- Time coustical process . Psychoacoustic Parameter 1 and In auditory display applications such as auditory graphing, var Psychoacoustic ious approaches can be made to pitch encoding, including the fre- Parameter 2 are used for redundant encoding quency ratio scale also known as logarithmic frequency distri- to increase the robustness bution, exemplified by the musical chromatic scale , the diatonic of the display major scale which has the advantage of musical familiarity , the pentatonic scale which has the advantage of relatively low disso- Time nance for any tone combinations , and the linear frequency scale Psychoacoustic which has the advantage of expressing low order integer ratios Parameter 1 as familiar harmonic intervals.
Unlike the other psychoacoustical Psychoacoustic Parameter 2 could also be scales referred to in this paper, such pitch scales are not necessarily used for encoding a psychological ratio scales, yet they can provide a range and level second data stream simultaneously of precision in data representation unavailable for the other scales.
Time 3. This ubiquity may be a cause of some of the difficulties inherent in the usage of auditory displays. Whilst 4. The algorithms involve several stages and can present iden- the implicit presentation of other sensations. In this situation it is tical results for different sound inputs. Therefore, they cannot be up to the listener to develop the skills to respond to the perceptual applied in reverse for synthesis, so the use of these models for parameter the sound designer intended to represent the data with, auditory display can present a practical challenge.
A less direct approach is to generate a large matrix of with this problem. In the first instance, we normalise other psy- sounds using traditional digital synthesis techniques, process these choacoustic sensations to control this arbitrary variance, in an at- using psychoacoustical algorithms, and thereby generate a lookup tempt to reduce the confusion caused.
In the second instance we table we can use to determine the appropriate digital synthesis manipulate this variance directly in an attempt to reinforce the rep- parameters for any given set of psychoacoustical parameters Fig- resentation parameter with psychoacoustic sensations that move ure 4 a.
Whilst this may seem a relatively trivial process, the in parallel. In the third we use the psychoacoustic sensations to implementation requires great care in preserving the orthogonality represent separate data streams.
To generate a set of candidates for this analysis process sim- ply requires a number of sounds that vary sufficiently for each 3.
Sound Quality psychoacoustic parameter to be in turn varied. This requires an understanding of to what, and over what range, the models are The use of psychoacoustical models facilitates the prediction of sensitive, as well as an understanding of the unintended effects ma- subjective qualitative response to auditory stimuli.
For example, nipulation of other parameters may induce. For instance, excessive Zwicker and Fastl present models of sensory pleasantness, based frequency modulation may reduce the perception of tonalness in on a combination of psychoacoustical parameters but dominated the produced sound.
The manipulation of amplitude modulation, by sharpness. Such models are context-dependent, but could be frequency modulation, fundamental frequency, spectral slope and developed for an auditory display application. Many studies in gain allows us a range of control over the psychoacoustic param- the field of sound quality indicate that psychoacoustical scales eters of loudness, sharpness, roughness, fluctuation strength and can better predict human evaluation of sound than physical signal pitch perception.
Table 1 describes possible synthesis parameters measurements . Figure 4: A Method for Implementation not control the psychoacoustic parameters directly, they will only loudspeakers except in very controlled conditions: their frequency be used to vary these parameters significantly enough that a useful response and level at the listener position is heavily dependent on range of psychoacoustic results are produced.
Hugo et al. Pages Hearing Area Fastl, Professor Dr. Masking Fastl, Professor Dr. Loudness Fastl, Professor Dr. Fluctuation Strength Fastl, Professor Dr.
Roughness Fastl, Professor Dr. Subjective Duration Fastl, Professor Dr. Rhythm Fastl, Professor Dr.
Binaural Hearing Fastl, Professor Dr. Examples of Application Fastl, Professor Dr. Show next xx. Read this book on SpringerLink. Recommended for you. PAGE 1.