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We examined the ability of 40 young children (aged five to eight) to understand speech (monosyllables, spondees, trochees, and trisyllables) when listening in a background of real-life classroom noise. All children had some difficulty understanding speech when the noise was at levels found in many classrooms (i.e., 65 dBA). However, at an intermediate (-6 dB SNR) level, kindergarten and grade 1 children had much more difficulty than did older children. All children performed well in quiet, with results being comparable to or slightly better than those reported in previous studies, suggesting that the task was age appropriate and well understood. These results suggest that the youngest children in the school system, whose classrooms also tend to be among he noisiest, are the most susceptible to the effects of noise.

We evaluated acoustic voice characteristics of 18 male patients undergoing radiotherapy. The subjects were seen for voice assessment preradiotherapy and at 1 month, 3 months, 6 months, and 1 year following radiotherapy. A multidimensional voice analysis computer program (IVANS, Avaaz Innovations, 1998) was employed to evaluate measures of traditional frequency and amplitude perturbation as well as time-based and linear prediction (LP) modeledr "noise" parameters of the acoustic output in conjunction with perceptual judgments of overall vocal quality. The results indicate vocal deterioration of vocal function immediately following radiotherapy with gradual and significant improvement in acoustic and perceptual features over 9 to 12 months following the radiation treatment. Measures of glottal noise demonstrated higher sensitivity than frequency-based measures of voice perturbation, and with more consistent, less variable changes in acoustical voice output from the preradiation to the 12 month postradiation periods. Future research evaluating vowel type and acoustic perturbation measures with a larger sample of subjects over a longer time period seems warranted.

We investigated how standard speech coders, currently used in modern communication systems, affect the intelligibility of the speech of persons who have common speech and voice disorders. Three standardized speech coders (viz., GSM 6.10 [RPE-LTP], FS1016 [CELP], FS1015 [LPC]) and two speech coders based on subband processing were evaluated for their performance. Coder effects were assessed by measuring the intelligibility of vowels and consonants both before and after processing by the speech coders. Native English talkers who had normal hearing identified these speech sounds. Results confirmed that (a) all coders reduce the intelligibility of spoken language; (b) these effects occur in a consistent manner, with the GSM and CELP coders providing the least degradation relative to the original unprocessed speech; and (c) coders interact with individual voices so that speech is degraded differentially for different talkers.

We investigated the abilities of four fundamental frequency (F 0 )-dependent and two F 0 -independent measures to quantify vocal noise. Two of the F 0 -dependent measures were computed in the time domain, and two were computed using spectral information from the vowel. The F 0 -independent measures were based on the linear prediction (LP) modeling of vowel samples. Tests using a database of sustained vowel samples, collected from 53 normal and 175 pathological talkers, showed that measures based on the LP model were much superior to the other measures. A classification rate of 96.5% was achieved by a parameter that quantifies the spectral flatness of the unmodeled component of the vowel sample.

Perturbation analysis of sustained vowel waveforms is used routinely in the clinical evaluation of pathological voices and in monitoring patient progress during treatment. Accurate estimation of voice fundamental frequency (FO) is essential for accurate perturbation analysis. Several algorithms have been proposed for fundamental frequency extraction. To be appropriate for clinical use, a key consideration is that an FO extraction algorithm be robust to such extraneous factors as the presence of noise and modulations in voice frequency and amplitude that are commonly associated with the voice pathologies under study. This work examines the performance of seven FO algorithms, based on the average magnitude difference function (AMDF), the input autocorrelation function (AC), the autocorrelation function of the center-clipped signal (ACC), the autocorrelation function of the inverse filtered signal (IFAC), the signal cepstrum (CEP), the Harmonic Product Spectrum (HPS) of the signal, and the waveform matching function (WM) respectively. These algorithms were evaluated using sustained vowel samples collected from normal and pathological subjects. The effect of background noise and of frequency and amplitude modulations on these algorithms was also investigated, using synthetic vowel waveforms.

An adaptive digital signal processing procedure was applied to various speech signals in three noise backgrounds. The procedure uses a modified approach to Wiener filtering to estimate a noise suppression filter which reduces the signal at frequencies most likely to be corrupted by noise. Speech intelligibility was compared with and without processing, for speech presented in three types of background noise: multitalker babble, wide-band noise, and narrow-band noise. The speech signals used were six spondaic words spoken by a male talker; 20 consonants, in an intervocalic environment, spoken by a female talker; and a passage of continuous discourse read by a female talker. Adaptive speech reception threshold (ASRT) testing was used to estimate the minimum SNR at which the spondaic words could be identified 70.7% of the time. With this test, signal processing improved performance by 11 dB in narrow-band noise for normal-hearing listeners; no statistically significant improvement was observed when listening in a background of wide-band or speech babble noise. Five of the six hearing-impaired listeners also had improved performance when listening in narrow-band noise, but minimal changes in wide-band or speech babble noise. With the consonant targets, a closed-set nonsense syllable testing procedure demonstrated that processing did not change or slightly reduced performance for all listeners. With continuous discourse all listeners demonstrated a strong preference for processed signals under most listening conditions.(ABSTRACT TRUNCATED AT 250 WORDS)

Measurement procedures using broadband noise stimuli for testing hearing aids have recently been standardized in an attempt to ensure that test results more closely reflect the ‘‘real‐world’’ performance of hearing aids. Although a number of researchers have employed coherence measures made with broadband noise stimuli to characterize the broadband distortion of hearing aids, broadband distortion measurement methods have not yet been standardized. In this paper, it is demonstrated through simulations and measurements on hearing aids that similar results are obtained when coherence is measured using maximum length sequence (MLS) and conventional unbiased statistical‐based methods. The calculation of single‐ and dual‐channel MLS coherence are also formalized. Signal‐to‐distortion ratio (SDR) measurements for two automatic signal processing hearing aids are presented.

Acoustical measures of vocal function are routinely used in the assessments of disordered voice, and for monitoring the patient's progress over the course of voice therapy. Typically, acoustic measures are extracted from sustained vowel stimuli where short-term and long-term perturbations in fundamental frequency and intensity, and the level of "glottal noise" are used to characterize the vocal function. However, acoustic measures extracted from continuous speech samples may well be required for accurate prediction of abnormal voice quality that is relevant to the client's "real world" experience. In contrast with sustained vowel research, there is relatively sparse literature on the effectiveness of acoustic measures extracted from continuous speech samples. This is partially due to the challenge of segmenting the speech signal into voiced, unvoiced, and silence periods before features can be extracted for vocal function characterization. In this paper we propose a joint time-frequency approach for classifying pathological voices using continuous speech signals that obviates the need for such segmentation. The speech signals were decomposed using an adaptive time-frequency transform algorithm, and several features such as the octave max, octave mean, energy ratio, length ratio, and frequency ratio were extracted from the decomposition parameters and analyzed using statistical pattern classification techniques. Experiments with a database consisting of continuous speech samples from 51 normal and 161 pathological talkers yielded a classification accuracy of 93.4%.

The authors describe a comprehensive, integrated, microcomputer-based facility for research on hearing aid fitting and for clinical use. The system first applies formal prescription rules to audiometric measures that have been obtained from an individual patient to predict which hearing aid amplification function is likely to provide the optimal benefit for a hearing-impaired listener. It then designs and implements a filter in a digital-signal processing (DSP) board that precisely implements the desired gain function. Speech intelligibility and listener preferences can then be measured to evaluate the prescribed hearing aid gain function, using efficient, computer-based testing procedures. The system requires an IBM/AT compatible microcomputer, an ARIEL DSP-16 board, filters and associated analog audio equipment, and a mouse. >

The accurate electroacoustic characterization of hearing aids is important for the design, assessment and fitting of these devices. With the prevalence of modern adaptive processing strategies (e.g., level-dependent frequency response, multi-band compression etc.) it has become increasingly important to evaluate hearing aids using test stimuli that are representative of the signals a hearing aid will be expected to process (e.g., speech). Nearly all current hearing aid tests use stationary test signals that can characterize only the steady-state performance of a hearing aid. The present research examines the characteristics of automatic signal processing hearing aids with natural-speech input signals that may cause the hearing aid response to time-vary. They have investigated a number of linear system identification techniques that can be used to develop time-varying models of hearing aids. Using these models, one can begin to characterize performance of hearing aids with real-world signals and explore speech-based transient distortion measures.

We investigated how standard speech coders, currently used in modern communication systems, affect the quality of the speech of persons who have common speech and voice disorders. Three standardized speech coders (GSM 6.10 RPELTP, FS1016 CELP, and FS1015 LPC) and two speech coders based on subband processing were evaluated for their performance. Coder effects were assessed by measuring the quality of speech samples both before and after processing by the speech coders. Speech quality was rated by 10 listeners with normal hearing on 28 different scales representing pitch and loudness changes, speech rate, laryngeal and resonatory dysfunction, and coder-induced distortions. Results showed that (a) nine scale items were consistently and reliably rated by the listeners; (b) all coders degraded speech quality on these nine scales, with the GSM and CELP coders providing the better quality speech; and (c) interactions between coders and individual voices did occur on several voice quality scales.

Adaptive modeling of digital hearing aids is useful in characterizing the hearing aid behavior in response to “real world” stimuli such as speech and music. Most modern hearing aids employ amplitude compression in different frequency bands for effective mapping of the wide dynamic range audio signals into the reduced dynamic range of the hearing impaired listeners. Due to the presence of independent compression channels, the conventional fullband adaptive model might not adequately characterize the performance of a multichannel compression hearing aid (MCHA). In this paper, we propose a subband adaptive modeling approach to characterize the electroacoustic performance of a MCHA. The proposed structure employs uniform, oversampled DFT filterbanks for analysis and synthesis, and the affine projection algorithm for adaptive modeling in each subband. Experiments with simulated MCHAs showed that the subband structure outperforms the fullband structure under a variety of operating conditions.

Acoustic measures of vocal function are routinely used for the assessment of disordered voice, and for monitoring patient's progress over the course of therapy. In current clinical practice, acoustic measures extracted from sustained vowels are used for vocal function characterization. However, the measures derived from continuous speech samples are required for accurate assessment of voice quality. In this paper, a time-frequency approach for pathological voice discrimination has been proposed. The speech signals were decomposed using an adaptive time-frequency transform algorithm, and the signal decomposition parameters such as the octave (scale) maximum, octave mean, energy rate, and length ratio were analyzed using the maximum likelihood method and Jack-knife algorithm for classification. A classification accuracy of 90% was obtained with a database of 40 speech signals (20 normal and 20 pathological cases).

Acoustic measures provide an objective means to describe pathological voices and are a routine component of the clinical voice examination. Because the voice sample is obtained using a microphone, microphone characteristics have the potential to influence the values of parameters obtained from a voice sample. This project examined how the choice of microphone affects key voice parameters and investigated how one might compensate for such microphone effects through filtering or by including additional parameters in the decision process. A database of 53 normal voice samples and 100 pathological voice samples was used in four experiments conducted in an anechoic chamber using four different microphones. One omnidirectional microphone and three cardioid microphones were used in these experiments. The original voice samples were presented to each microphone through a speaker located in an anechoic chamber, and the output of each microphone sampled to computer disk. Each microphone modified the frequency spectrum of the voice signal; this, in turn, affected the values of the voice parameters obtained. These microphone effects reduced the accuracy with which acoustic measures of voice could be used to discriminate pathological from normal voices. Discrimination performance improved when the microphone output was filtered to compensate for microphone frequency response. Performance also improved when spectral moment coefficient parameters were added to the vocal function parameters already in use.

Modern speech coding schemes have been developed to address the demand for economical spoken language telecommunication of acceptable quality. A variety of speech coding algorithms have been described, which compress speech to facilitate efficient transmission of spoken language over communication networks ((J.R. Deller Jr., 1993; P.E. Papamichalis, 1987). Most such speech coding algorithms are lossy in the sense that the processed speech is not identical to the original speech. As a result, some distortion is invariably introduced with any lossy speech coding strategy. For this reason, candidate coders undergo detailed evaluation to ensure that the associated speech output is of acceptable quality (S.R. Quackenbush et al., 1988). Three different coding algorithms were investigated relative to unprocessed speech: the Codebook Excited Linear Prediction (CELP), the Global System for Mobile Communications (GSM) algorithm which is a standardized speech coding algorithm in Europe, and the Linear Predictive Coding (LPC) algorithm. The specific coding schemes evaluated were MatLab implementations of NSA FS-1015 LPC-l0e; NSA FS-1016 CELP-v3.2; and ETSI GSM (A. Spanias, 1995). One of the goals of this study was to quantify the coding distortion using objective measures and to correlate these measures with speech intelligibility and subjective quality data, in the hope of identifying one or more measures that can predict the subjective results.

There is a growing trend for hearing aids to incorporate wide dynamic range compression. The input/output (I/O) hearing aid formula, presented in this report, is a general frequency‐specific mathematical approach which describes the relationship between the input level of a signal delivered to a hearing aid and the output level produced by the hearing aid. The I/O formula relates basic psychoacoustic parameters, including hearing threshold level and uncomfortable listening level, to the electroacoustic characteristics of hearing aids. The main design goal of the I/O formula was to fit the acoustic region corresponding to the ‘‘extended’’ normal auditory dynamic range into the hearing‐impaired individual’s residual auditory dynamic range. The I/O approach can be used to fit hearing aids utilizing linear gain, linear compression or curvilinear compression to a hearing‐impaired individual’s residual auditory area.

CSRE (The Canadian Speech Research Environment) is a comprehensive, microcomputer‐based system designed to support speech research using IBM/AT‐compatible micro‐computers. CSRE provides a powerful, low‐cost facility in support of speech research, using mass‐produced and widely available hardware. Functions include speech capture, editing, and replay; several alternative spectral analysis procedures, with color and surface/3‐D displays; parameter extraction/tracking and tools to automate measurement and support data logging; alternative pitch‐extraction systems; parametric speech (KLATT80) and nonspeech acoustic synthesis, with a variety of supporting productivity tools; and a comprehensive experiment generator/controller, to support behavioral testing using a variety of common testing protocols. The CSRE project is nonprofit, and relies on the cooperation of researchers at a number of institution. Version 3.0 of CSRE has been used since 1989 by researchers in 12 countries. Version 4.0 offers a wider range of functions, runs faster, uses higher resolution displays, and supports additional hardware systems, including digital signal processing boards.

Non-invasive procedures are proposed to aid the diagnosis of childhood laryngotracheal pathology and to monitor the course of such disease. The procedures capitalize on the one-to-one relationship which exists between the acoustic phenomena (stridors) associated with respiration and the configuration of the respiratory tract. Careful analysis of these acoustic patterns can thus assist in identifying and localizing constrictions, in diagnosis, and in monitoring disease severity. Based on the acoustical analysis of the stridor generated by children with congenital stridor, subglottal laryngitis, and trachea stenosis, the present paper demonstrates that a close relationship exists between the specific pathology and the spectrum of the associated respiratory stridor.

Typical measurements of electroacoustic performance of hearing aids include frequency response, compression ratio, threshold and time constants, equivalent input noise, and total harmonic distortion. These measurements employ artificial test signals and do not relate well to perceptual indices of hearing aid performance. Speech‐based electroacoustic measures provide means to quantify the real world performance of hearing aids and have been shown to correlate better with perceptual data. This paper investigates the application of system identification paradigm for deriving the speech‐based measures, where the hearing aid is modeled as a linear time‐varying system and its response to speech stimuli is predicted using a linear adaptive filter. The performance of three adaptive filtering algorithms, viz. the Least Mean Square (LMS), Normalized LMS, and the Affine Projection Algorithm (APA) was investigated using simulated and real digital hearing aids. In particular, the convergence and tracking behavior of these algorithms in modeling compression hearing aids was thoroughly investigated for a range of compression ratio and threshold parameters, and attack and release time constants. Our results show that the NLMS and APA algorithms are capable of modeling digital hearing aids under a variety of compression conditions, and are suitable for deriving speech‐based metrics of hearing aid performance.

This study investigated the effects of perceptual and production training on the abilities of adult native speakers of Spanish to identify and produce the English vowels /i, I, e, e, ae/. Testing was performed prior to and following an average of 12 h of perceptual training in a category inclusion task, then again following an average of 7.5 h of production training involving visual feedback of vowel formant (F1 and F2) values. A lagged control group of participants who were delayed in starting training showed no improvement in perception and production skills during the control period but changed equivalently during training. The mean improvement in perceptual identification accuracy for /i, I, e, e/ was 17%. The mean improvement in the intelligibility of participants productions of /I, e, ae/ following training was 11%. For both perception and production, most improvement occurred during perceptual training.

This paper considers an acoustic basis for speech intelligibility and evaluates various acoustically based speech intelligibility prediction algorithms. Earlier research indicates that speech intelligibility does not require preservation of spectral and temporal fine‐structure, but is highly dependent on the preservation of the amplitude component of the modulation spectrum [R. Drullman, J. Acoust. Soc. Am. 97, 585–592 (1995)]. This study assessed the importance of the phase component of the modulation spectrum using a 21‐alternative forced‐choice consonant perception test. Temporal and spectral fine‐structure were removed by modulating a white noise carrier with 50 Hz low‐pass filtered speech amplitude envelopes in 4, 8, or 24 discrete bands. Modulation spectrum phase was distorted by imposing a random delay in each discrete band. Behavioral results are discussed in light of intelligibility predictions generated by the articulation index [N. R. French and J. C. Steinberg, J. Acoust. Soc. Am. 19, 90–119 (...

Subjective assessments of the severity of hearing aid distortion were obtained using both rating scale and paired comparison measures, with sentence materials. Data were collected under 30 hearing aid conditions, representing a broad range of real hearing aid distortions. These data were related to a range of objective (engineering) measures of hearing aid distortion, including techniques based on pure tones (THD, IMD), measures using broadband noise stimuli having certain speech‐like characteristics, and measures derived from real speech. Data from both normal and hearing‐impaired subjects were stable and orderly, with good agreement between datasets collected using paired comparison and rating scale methods. Correlations with behavioral data were significantly better for certain speech‐based objective measures than electroacoustic measures based on noise or pure‐tone signals. [Work supported by the Natural Sciences and Engineering Research Council of Canada.]

The electroacoustic properties of many modern hearing aids change as a function of the input stimuli. One consequence is that electroacoustic measurements obtained using commercial hearing aid test systems may differ from those made with important, ‘‘real‐life’’ signals. As speech is the most important real‐life signal for most hearing aid users, tests using speech stimuli have been proposed. This paper describes one approach to such testing, using spectrograms to display speech signals in a three‐dimensional representation. Dual spectrogram displays prepared using the computerized speech research environment (CSRE) software allow speech signals at the input and output of a hearing aid to be compared. Such spectrograms are computed for a set of important phonemes extracted from running speech. The results of these analyses are evaluated for individual hearing aid users using a display which includes the user’s thresholds and loudness discomfort levels (LDLs), together with the target amplification levels ...

A mathematical model is described for mechano‐electro‐chemical transduction in hair cells. The model relates the displacement of stereocilia to the intensity of firing of fibers attached to each hair cell through a cascade of four stages. The gating stage relates hair bundle displacement to the change in conductivity of the hair cell membrane. It is described by a mechanical version of the Hodgkin–Huxley model. The electric stage relates the change in conductivity to the receptor potential through a hair cell electrical network of the Davis type. The calcium kinetics stage relates free calcium ion (Ca2+) concentration in hair cells to the receptor potential. It is assumed there are two states of calcium ions: free and bound (by buffers). The synaptic transmission stage relates free calcium concentration to the intensity of firing as described by the Hill equation. Using relevant parameters, the model simulates the behavior of low‐ and high‐spontaneous firing rate fibers, and is being implemented as a comp...

An automated dual‐channel maximum‐length sequence (MLS) test system for the electroacoustic characterization of hearing aids has been developed. This test system applies a speech‐shaped MLS acoustically to a hearing aid and measures the electro‐acoustic frequency response. This method provides results that compare favorably to those obtained using the method employed by Kates [J. M. Kates, J. Rehab. Res. Develop. 27, 255–278 (1990)] and the ANSI standard method [ANSI S3.42 (1992)]. Test results show that MLS‐based testing is significantly faster than noise‐based testing. Two signal‐biased MLS‐based testing methods have also been developed. These methods apply a bias signal to force the hearing aid into a mode of operation where the frequency response, with adaptive or subtractive bias signal cancellation, is measured using a low‐level, speech‐shaped MLS. This method has proved valuable for the characterization of automatic signal processing hearing aids. [Work supported by ORTC and OMH.]

The experiment control system is a package of computer programs that facilitate the generation and conduct of identification and discrimination experiments using speech and other complex acoustical signals. The system permits microcomputers to be used to control experimental equipment, present signals to listeners, and record and analyze responses, without preparing individual computer programs for each experiment. The package contains three general programs. The GENERATE program is used to define experimental parameters via full‐screen data entry forms. The core of the program is an entry form that allows one to specify four basic parts of an experimental trial: a warning signal, one or more stimulus presentations, the response(s) to be recorded, and any feedback to be provided after the response. Within each of these categories, a number of alternatives are permitted. The CONTROL program applies the parameters and data defined in GENERATE to run the experimental session. Typically, possible responses are displayed using high‐resolution graphics on a computer video screen and subjects respond using a computer mouse. The SCORE program analyzes output from CONTROL and displays the results as response matrices with basic statistics such as means and standard deviations, as well as row and column sums. Output is provided as a screen display and print‐ready file. ECoS is being made available to researchers as part of Version 4.0 of CSRE (the Canadian Speech Research Environment).

A common complaint of hearing aid wearers is that they have difficulty when listening in a background of noise. The ability of a digital adaptive noise reduction filter to reduce background noise without degrading speech perception has been evaluated. Each of four normal‐hearing and six hearing‐impaired subjects completed two behavioral tests of speech perception—the speech reception threshold (SRT) and the modified distinctive features differences test [DFD(m)]—and one subjective measure of listener preference (paired comparisons). Each test was performed in three types of background noise presented at a level of 65 dB: white noise, low‐pass filtered at 8.0 kHz; white noise, low‐pass filtered at 1 kHz; and multitalker speech babble. For hearing‐impaired subjects, the speech‐plus‐noise signal was filtered and amplified to provide the NAL real‐ear insertion gain. Results indicated that all subjects preferred the noise‐reduction‐processed speech‐plus‐noise signal over the unprocessed signal at positive sign...

This paper compares four alternative procedures for estimating the acoustical characteristics of speech and other complex signals: the fast Fourier transform (FFT), two autoregressive techniques (the autocorrelation and modified covariance methods), and the Cone–Kernel method. All four techniques are now widely available to researchers in Version 4.0 of the CSRE (Canadian Speech Research Environment) software system. FFT spectral estimates are characterized by many known tradeoffs: good frequency resolution is obtained at the expense of good time resolution, and vice versa. Autoregressive methods overcome some of the inherent limitations of the FFT method, but still use a quasi‐stationary approach to analyze nonstationary signals such as speech. The Cone–Kernel method offers the opportunity for both good frequency and good time resolution, and cancels many of the cross terms that have made it difficult to interpret previous approaches based on the Wigner distribution. Examples of applying the various analysis procedures to signals will be shown, including situations where the Cone–Kernel approach facilitates the interpretation of certain details of the speech signal.

Cue deletion was used to examine the contribution of various acoustic cues to the identification of the English stop consonants (/b/, /d/, /g/, /p/, /t/, /k/). Stimuli were based on tokens spoken by four talkers (two men and two women) in a syllable‐medial context (/(inverted vee) Cil /). Cues within five regions centered on the burst were examined: (1) the transition from the preceding vowel into consonant closure, (2) the closure interval, (3) the consonant release, (4) the initial transition from release to the following vowel, and (5) the final transition to the vowel. Each region either remained at the full normal amplitude or was attenuated fully (i.e., effectively replaced by silence). Four listeners who had normal hearing identified the 768 signals constructed from each of the possible combinations of attenuated and full‐amplitude regions (i.e., 32 combinations ×6 stimuli ×4 speakers). Analyses of these identification responses demonstrates the relative importance of each region, and of each combination of regions, for consonant identification. Acoustic measures explain some aspects of the confusion errors which occurred.

This article reports the results of three experiments which investigated the role of intonation in foreign accent. It was found that adult French, English and German speakers differ in the slopes (fundamental frequency divided by time) of their continuative intonation. Monolingual English and French children also differ in their continuative intonational slopes. Students who are native English speakers but attend French immersion schools, acquire appropriate French continuative intonation by age 10, but at age 16 they typically use English intonation when they speak French. A perception experiment showed that no language group chose intonation patterns with slopes based on native production data to be more native-like than those with slopes based on non-native data. Some remarks are made about language acquisition in the immersion setting and about convergence in intonational function.

Merely listening to a repeated [pha] sound tends to shorten the voice-onset time of [pha] sounds which are subsequently produced by the listener by an average of approximately 7 ms. This “adaptation” effect seems to be induced readily and to be highly reproducible. In contrast to the results with perceptual testing, listening to [ba] sounds has no effect on [pha] productions. Moreover, the voice-onset time of produced [ba] sounds is not affected by listening to [ba] or to [pha]. The production adaptation effect seems to be short lived, since voice-onset times for [pha] tokens uttered 30 s after adaptation are statistically indistinct from those uttered without adaptation. These results replicate and extend those reported by Cooper, Blumstein & Nigro (e.g. J. Phonetics, 1975), and they stand in distinction to the failure of Summerfield, Bailey & Erickson (J. Phonetics, 1980) to induce perceptuo-motor adaption.

A series of digital computer programs which facilitate the production and control of acoustic stimuli for hearing assessment and research are described. The package, which is available for PDP 11 computers under RT-11, allows sounds to be digitized, adjusted for amplitude and/or dc offset, edited while in digital form, and output to file or tape. The waveform editor package includes facilities to edit sounds in time—with some sections removed or added with temporal precision of 0.1 msec or better. Two or more sounds may also be combined for stereo or monaural (sound-on-sound) output, or two may be concatenated. Together, the programs permit a wide range of manipulations useful in preparing sound stimuli for use in hearing experiments or in clinical audiometry.