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This dissertation describes the development of an evaluation tool that can be used by an acoustican during the design stage of enclosures used for unassisted speech. Enclosures include lecture theatres, lecture halls and speech auditoriums. The tool is designed to enable Acousticians to be able to manipulate various acoustical parameters such as the geometry and the materials or construction selection to gauge the impact on speech performance. The tool can also be used to evaluate the performance of speech privacy within spaces using the Speech Transmission Index. Computer simulation tools have a number of advantages over existing methods such as physical scale models for this type of evaluation. Typical advantages are in the elimination of the difficult selection of materials with appropriate scale model acoustic performance, resolution of air absorption at scale model frequencies, reduced cost in development of the model, no storage space problems, ease of modifying and duplicating the model. Scale models also present difficulties in measuring some of the indices such as Speech Transmission Index. Whilst equipment can be purchased for the measurement of STI, scale model equivalents and the impact of the change in frequencies and modulations have not been researched or published. / Currently, there are only two methods of evaluating the Speech Transmission of an enclosure: Build a full size enclosure and test; or simulate mathematically to derive the performance. At the time this thesis was commenced there were no commercial simulation programs available that could derive Speech Transmission Index information. The evaluation tool has been implemented as a computer program, based on IBM PC type computers running Microsoft WINDOWS 3.1 or later. The implementation uses the image method for the 'ray trace' algorithm. This basic image method utilises the enhancements made by a number of authors. In particular the Transformation Matrix method and homogenous coordinates have been used to improve the speed of the algorithm. Pre-computation of mutually invisible planes allows trimming the number of possible combination of rays that need to be computed. Results of physical measurement from two case studies have been compared to results of the simulation. Good correlation between the simulations and the case studies were achieved for the Speech Transmission Index and RASTI values. The accuracy of the simulation,in terms of decay based indices, is limited by the lack of sufficient tail to the calculated number of rays. Further research and implementation of hybrid techniques utilising both the image method and more traditional ray-tracing algorithms to improve the quality of the calculated decay data are required. Investigation of techniques used in photo-realism 'ray-tracing' may result in far more realistic data which is the basic input to the Speech Transmission Index calculations.

Speech coding is a very important area of research in digital signal processing. It is a fundamental element of digital communications and has progressed at a fast pace in parallel to the increase of demands in telecommunication services and capabilities. Most of the speech coders reported in the literature are based on linear prediction (LP) analysis. Code Excited Linear Predictive (CELP) coder is a typical and popular example of this class of coders. This coder performs LP analysis of speech for extracting LP coefficients and employs an analysis-by-synthesis procedure to search a stochastic codebook to compute the excitation signal. The method used for performing LP analysis plays an important role in the design of a CELP coder. The autocorrelation method is conventionally used for LP analysis. Though this works reasonably well for noise-free (clean) speech, its performance goes down when signal is corrupted by noise. Spectral analysis of speech signals in noisy environments is an aspect of speech coding that deserves more attention. This dissertation studies the application of recently proposed robust LP analysis methods for estimating the power spectrum envelope of speech signals. These methods are the moving average, moving maximum and average threshold methods. The proposed methods will be compared to the more commonly used methods of LP analysis, such as the conventional autocorrelation method and the Spectral Envelope Estimation Vocoder (SEEVOC) method. The Linear Predictive Coding (LPC) spectrum calculated from these proposed methods are shown to be more robust. These methods work as well as the conventional methods when the speech signal is clean or has high signal-to-noise ratio. Also, these robust methods give less quantisation distortion than the conventional methods. The application of these robust methods for speech compression using the CELP coder provides better speech quality when compared to the conventional LP analysis methods.

Thesis (M.A.)--Georgia State University, 2007. / Title from file title page. Page Anderson, committee chair; Rod Watts, Leslie Jackson, committee members. Electronic text (101 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Dec. 5, 2007. Includes bibliographical references (p. 76-85).

The quality and intelligibility of single channel speech degraded by additive noise remains a challenging problem when only the noisy speech is available. An accurate estimation of the noise spectrum is important for the effective performance of speech enhancement algorithms, especially in nonstationary noise environments. This thesis addresses both two issues. First, a speech enhancement algorithm using harmonic features is introduced. A spectral weighting function is derived by constrained optimization to suppress noise in the frequency domain. Two design parameters are included in the suppression gain, namely the frequency-dependent noise-flooring parameter (FDNFP) and the gain factor. The FDNFP controls the level of admissible residual noise in the enhanced speech, while further enhancement is achieved by adaptive comb filtering using the gain factor with a peak-picking algorithm. Second, a noise estimation algorithm is proposed for nonstationary noise conditions. The speech presence probability is updated by introducing a time-frequency dependent threshold. The frequency dependent smoothing factor for noise estimation is computed based on the estimated speech presence probability in each frequency bin. This algorithm adapts quickly to nonstationary noise environments and preserves more information on weak speech phoneme. The performance of the proposed speech enhancement algorithm is evaluated in terms of Perceptual Evaluation of Speech Quality (ITU-PESQ) scores and Modified Bark Spectral Distortion (MBSD) measures, composite objective measures and listening tests. Our listening tests indicate that 16 listeners on average preferred our harmonic enhanced speech over any of three other approaches about 73% of the time. The performance of the proposed noise estimation algorithm combined with the proposed speech enhancement method in nonstionary noise environments is also tested in terms of ITU-PESQ scores and MBSD measures. Experimental results indicate that the proposed noise estimation algorithm when integrated with the harmonic enhancement method outperforms spectral subtraction, signal subspace method, a perceptually-based enhancement method with a constant noise-flooring parameter, and our original harmonic speech enhancement method in highly nonstationary noise environments.

Objective: To determine if there was an optimal language sampling context for children with hearing impairment; specifically, if any well-documented method of obtaining a language sample was superior to the others in describing the areas of language that are known to serve as a foundation for later literacy development. Participants: Nine children with hearing impairment who used oral language as their primary mode of communication from the University of Tennessee Child Hearing Services clinic were selected to participate in the study. All were from Caucasian families who spoke English as their primary language and with the exception of hearing impairment, none had other documented disorders. Method: Three language samples were taken in an interview, picture description and story retell format during one 50 minute session. Data Analysis: The language samples were analyzed for syntax and morphology, semantic, pragmatic and narrative measures which are preliteracy factors that influence later literacy acquisition. Results: A battery of language samples is needed in order to appropriately access multiple elements of language relating to literacy acquisition of children with hearing impairment. Conclusion: Through the analysis of this study, it has been determined that in order to get a comprehensive view of language in hearing impaired children who use oral language as their primary communication, a battery of language assessments should be used.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 173-186).

Thesis (Ph. D.)--Texas A&M University, 2005. / "Major Subject: Speech Communication" Title from author supplied metadata (automated record created on Feb. 23, 2007.) Vita. Abstract. Includes bibliographical references.