Loudness Control Research Articles

Loudness control in pianists as exemplified in keystroke force measurements on different touches

The relationship between the key depression force on an upright piano and the level of loudness of a generated tone was examined when pianists hit a force-sensor built-in key with "struck" or "pressed" type of touch. The vertical displacement of the key, and the radiated piano sounds were also recorded. It was found that for both types of touch, simple exponential functions could adequately describe the relation of the force amplitude with the level of the piano tone as well as that of the impulse of the force with the piano tone. The impulse of the force generated before the maximum key depression moment commonly amounted to above 80% of the total impulse produced at the tone below mezzo-forte. It, however, decreased to around 60% at fortissimo, indicating a decrease in the efficiency of the force application for sound production. The two types of touch differed in their force profiles. The struck touch was characterized by a steeper initial force increase with greater fluctuations in the subsequent period than the pressed touch. The struck touch also demonstrated lower maximum force and less impulse at fortissimo. The inter-pianist variation in the force and impulse, and the "finger-noise" are also herein examined.

Toward Robotic Musicianship

We present the development of a robotic percussionist named Haile that is designed to demonstrate musicianship. We define robotic musicianship in this context as a combination of musical, perceptual, and interaction skills with the capacity to produce rich acoustic responses in a physical and visual manner. Haile listens to live human players, analyzes perceptual aspects of their playing in real time, and uses the product of this analysis to play along in a collaborative and improvisatory manner. It is designed to combine the benefits of computational power, perceptual modeling, and algorithmic music with the richness, visual interactivity, and expression of acoustic playing. We believe that combining machine listening, improvisational algorithms, and mechanical operations with human creativity and expression can lead to novel musical experiences and outcome. Haile can therefore serve as a test bed for novel forms of musical humanmachine interaction, bringing perceptual aspects of computer music into the physical world both visually and acoustically. This article presents our goals for the project and the approaches we took in design, mechanics, perception, and interaction to address these goals. After an overview of related work in musical robotics, machine musicianship, and music perception, we describe Haile's design, the development of two robotic arms that can strike different locations on a drum with controllable volume levels, applications developed for lowand high-level perceptual listening and improvisation, and two interactive compositions for humans and a robotic percussionist that use Haile's capabilities. We conclude with a description of a user study that was conducted in an effort to evaluate Haile's perceptual, mechanical, and interaction functionalities. The results of the study showed significant correlation between humans' and Haile's rhythmic perception as well as strong user satisfaction from Haile's perceptual and mechanical capabilities. The study also indicated areas for improvement, such as the need for better timbre and loudness control as well as more advanced and responsive interaction schemes.

The Characteristics of Loudness Control in Realizing Prominences by Japanese Learners of English(<Feature Articles>Current Issues in Intonational Research)

The Characteristics of Loudness Control in Realizing Prominences by Japanese Learners of English(<Feature Articles>Current Issues in Intonational Research)

Range control system

A range control system includes an input section for inputting a singing voice, a fundamental frequency extracting section for extracting a fundamental frequency of the inputted voice, and a pitch control section for performing a pitch control of the inputted voice so as to match the extracted fundamental frequency with a given frequency. The system further includes a formant extracting section for extracting a formant of the inputted voice, and a formant filter section for performing a filter operation relative to the pitch-controlled voice so that the pitch-controlled voice has a characteristic of the extracted formant. The system further includes an input loudness detecting section for detecting a first loudness of the inputted voice, and a loudness control section for controlling a second loudness of the voice subjected to the filter operation to match with the first loudness. The system further includes a music information storing section storing musical information of songs to be sung, and an automatic reproducing section for reading musical information of a selected song and outputting melody information, accompaniment information and various acoustic effect information of the selected song included in the musical information.

Classification of the acoustic environments using a psychoacoustic model

Complex digital hearing aid algorithms employ different signal processing stages, e.g., noise reduction and loudness control. Most of these stages are suitable only for special acoustic environments or need different parameter sets for different environments to assure optimum rehabilitation success. Future ‘‘intelligent’’ digital hearing aids should therefore incorporate a model of the acoustic environment to adapt the signal processing to the acoustic environment. In particular, the presence of a speech signal and of different types of ambient noise should be detectable. In this study, the perception model introduced by Dau et al. [J. Acoust. Soc. Am. 102, 2829–2919 (1996)], which was originally developed to model different psychoacoustical tasks, e.g., forward masking and modulation detection is used as a preprocessor for this type of classification algorithms. This approach seems promising, as the model includes a modulation frequency analysis which was shown to be a good estimator of speech activity [Ostendorf, Fortschritte der Akustik DAGA 98, Zürich]. First results on the classification accuracy using this model are presented.

Derivation of frequency-gain characteristics for maximizing speech reception in noise.

Hearing aid gain-assignment schemes known as "prescriptions" were not designed for fitting hearing aids that modify their frequency responses to reduce background noise interference. Rather, prescriptions were developed for hearing aids having single, fixed frequency responses and aim to optimize speech reception in relatively quiet environments. Even though prescriptions do not apply to noisy conditions specifically, they embody the trade between maximizing speech audibility and maintaining loudness comfort that is critical to frequency-gain characteristic selection independent of whether noise is present or absent. The articulation index (AI) was used to examine the extent to which prescriptions' deference to loudness comfort causes them to fall short of maximizing speech spectrum audibility, thereby revealing (roughly) the magnitude of the loudness control built into prescriptions. AIs for speech amplified by an AI-maximizing rule (MAX AI) (Rankovic, Freyman, & Zurek, 1992) and according to several prescriptions were calculated as a function of hearing loss degree and configuration for quiet and noisy conditions. In quiet, AIs for prescriptions were similar to one another when presented with the same audiogram but were drastically smaller than MAX AIs, implying that prescriptions limit speech audibility to a large extent to prevent loudness discomfort. In noise, maximizing the AI required frequency-gain characteristics that were substantially different from prescription-assigned characteristics and that were unique to each noise/audiogram combination. A loudness constraint for the MAX AI scheme was developed to account for the gain discrepancy between prescription AIs and MAX AIs observed in the quiet condition, based on the highest comfortable loudness (HCL) equations presented by Cox (1989) in combination with a loudness model (von Paulus & Zwicker, 1972). The MAX AI scheme with the new loudness control was extended to specify frequency-gain characteristics expected to be optimal for several conditions containing noise, and examples are presented.

Speech synthesis in telecommunications

A text-to-speech synthesis system that synthesizes speech from unrestricted text is discussed. The text analysis system, which includes text preprocessing, phrasing and intonation, and letter-to-phoneme conversion, is described. The analyzed text is represented by phonetic characters, stress values, minor- and major-phrase markers, and intonational descriptors. The synthesizer uses this information to compute a speech signal in several stages. The duration of the different speech events is computed, and the intonational descriptors are converted to a fundamental frequency contour. Loudness control is also generated. After these prosodic parameters have been computed, the synthesis parameters that describe the different sounds or phonemes are generated. These parameters are converted to speech by a waveform synthesizer. >

Acoustic Behaviour of Insects: An Evolutionary Perspective

Part 1 Sound questions and acoustic behaviour: alternative behaviours male spacing behaviour mate finding in females size and reproductive success selection on the calling behaviour of insects natural and sexual selection. Part 2 Acoustic strategies in aggregations: calling and co-operating leks and sprees sites for aggregations more numbers more power are females attracted to choruses? group songs and species distinctiveness - individuality in a group male agonistic behaviour with minimum contact. Part 3 Chorusing and alternating behaviour: synchrony within the chorus asynchronous choruses calling and listening crepitation alternation. Part 4 A question of sound: sound a working definition measuring sound near-field sound communication frequency and loudness control measuring substrate vibrations amplifiers and baffles noise. Part 5 Producing sound: using near-field sounds substrate-borne vibration airborne sounds. Part 6 Listening and recognizing: collecting information the mechanoreceptor the locust ears of crickets and bushcrickets moth ears the cicada car strange ears - lacewings, beetles, mantises and bugs. Part 7 Mate recognition: species specific signals homogamy unique species songs the recognition of non-like calling and courtship songs signal stability female songs and species recognition. Part 8 Sound patterns: variations and stereotypes the central control of the output feedback control linking input to output the input signal recognition central recognition song gaps and species recognition in grasshoppers. Part 9 Sound localization and distance perception: directionality in the near-field directional responses to substrate-borne vibration directional responses to airborne sound directional hearing in the Orthoptesa distance. Part 10 Avoiding predation: the detection of predation evolutionary strategies in response to birds and parasitoids calling strategies that reduce predation. Part II The evolution of acoustic communication: sexual differences in calling switching signals and changing meanings dual auditory function in acoustic moths the evolution of social signals conclusion.

A study on the method of designing a frequency-response characteristics of a loudness control circuit for sound reproduction system based on the idea of masked frequency spectrum.

A study on the method of designing a frequency-response characteristics of a loudness control circuit for sound reproduction system based on the idea of masked frequency spectrum.

A Minimal Negotiation Situation

Pairs of unacquainted male subjects listened to music via headsets controlled by a single loudness control. Post-session measures of first impressions of the other person indicated that interpersonal liking was influenced by minimal communication and curvilinearly related to the magnitude of the difference between the level of individual preference and dyadic loudness. Loudness preference was stable over a one-week period, and the preparation appears useful for studying minimal negotiations.

Audio loudness control system

First Page

Apparatus for tone generation with combined loudness and formant spectral variation

In a musical instrument having one or more tone generators in which a plurality of data words corresponding to the amplitudes of a corresponding number of evenly spaced points defining the waveform of one cycle of an audio signal are transferred sequentially from a note register to a digital-to-analog converter in repetitive cycles at a rate proportional to the pitch of the tone being generated, apparatus is provided for varying the spectral content of the tone in response to control signals. A loudness control signal causes loud tones to be produced with a greater number of harmonics than those for a soft tone. A formant control signal also causes the tones to have a time variant spectral quality.

Polyphonic tone synthesizer with loudness spectral variation

In a musical instrument having one or more tone generators in which a plurality of data words corresponding to the amplitudes of a corresponding number of evenly spaced points defining the waveform of one cycle of an audio signal are transferred sequentially from a note register to a digital-to-analog converter in repetitive cycles at a rate proportional to the pitch of the tone being generated, apparatus is provided for varying the spectral content of the tones in response to a loudness control signal. Loud tones are produced with a greater number of harmonics than those for a soft tone.

The “soft-spoken” woman II: Auditory vs non-auditory monitoring of loudness behaviors

The loudness behaviors of “soft-spoken” women were tested under four conditions of monitoring. Auditory and non-auditory feedback were manipulated so as to modify their contributions to vocal loudness control. Auditory monitoring was found to contribute most powerfully to the selection of loudness level and adjustment of level under the conditions of the present study, though non-auditory perceptions may also be employed by speakers when audible cues are modified or eliminated.

Dysarthria in multiple sclerosis.

Less than half of a series of 168 patients with multiple sclerosis presented significant speech deviations. The most frequent speech deviations observed were impaired loudness control and harshness; less frequently occurring deviations were defective articulation, restricted use of vocal variations for emphasis, poor pitch control, hypernasality, inappropriate pitch level, and breathiness. “Scanning speech” was not a prominent characteristic. Speech deviations were not solely attributable to cerebellar involvement. Their incidence was positively related to severity of neurologic involvement, becoming more prominent as additional motor systems were implicated.

A stereophonic transistor preamplifier

Designed to drive two transistor-power amplifiers previously described, this preamplifier contains all the controls necessary for stereophonic and monophonic programs. The first two of the three stages form a complementary circuit readily adaptable for the various input sources, which provides the necessary gain and equalization for low-level phonograph and tape inputs, guard voltages to reduce the capacitive effects of the input cables, and impedance transformation for high-level inputs from tuners and other tube circuitry. Loudness control is achieved by the combined effect of variable negative feedback and a novel tone-control arrangement. The frequency range, including the power amplifiers, extends from below 6 cycles to above 50 kilocycles per second.