Speech Communication

Contains reports on seven research projects.Contract AF19(604)-2061 with Air Force Cambridge Research CenterContract N5ori-07861 with the Navy (Office of Naval Research)National Science Foundatio

A Signal Conditioner for Speech Processing

This thesis describes the design, implementation and testing of an analog signal conditioner for use in processing of speech signals. The signal conditioner provides gain and bandwidth control for the speech signal and also indicates the signal level. It is designed to be used in conjunction with a digital speech processor and has ports for a microphone or other signal source, an input signal monitoring device such as an oscilloscope, and interfaces to the digital speech processor. Signal bandwidth control is provided by a variable cutoff frequency lowpass switched capacitor filter, which is driven by a clock. In this thesis, the speech signal is examined and is related to the problem at hand. An overall description of the signal conditioner is then presented, emphasizing each of the signal conditioner is then presented, emphasizing each of the individual building blocks in the system. A description of switched capacitor filter theory and application follows, and signal conditioner system test results and conclusions are given. It was found that the system performance satisfied the desired specifications that were laid out when the system was first conceived

VOICE MODIFICATION USING DIGITAL TECHNOLOGY

This report describes the voice modification using digital technology using MATLAB software and an additional hardware prototype designed. The voice modification objective that a source voice signal is mapped into another target voice signal. Other objective of this voice modification is to create a new voice signal from a given source signal. These modifications are carried by altering the voice waveform features. By enabling the modification, it is expected that user is able to mimic other person's voice. In addition, it can be used as a reference and guidance for voice conversion. For the modification algorithm, an optimization technique for the coding is applied to suit the objective of the project [7]. The project's major activities are to develop programs using MATLAB, that enable speech signal recording, analysis, synthesis, modification, and conversion. The recording is just a simple procedure, where it can be recorded using any computer, with a microphone. Analysis of speech signal is an essential step where the speech waveform features are calculated. Here, we model a vocal tract, which resemble as a filter for the excitation signal input. This filter is designed based on source speech waveform features. The speech waveform parameters used in this analysis are excitation source model, vocal tract model and control model which consist of gain and pitch parameter. Synthesis procedure is a step to produce a synthetic voice. This synthetic voice is just the display of speech signal designed in the analysis part based on the source signal. The modification and conversion parts of the software are performed for the voice modification. The modification part enables the user to change the speech waveform parameters calculated and thus creates a new voice. The conversion part is actually performs a mapping of source speech signal to target speech signal. In this work, hardware also is designed as an additional part to demonstrate the application. The prototype designed performs the conversion process by modulating the frequency of input signal. Tests were carried on both software and hardware. The software conversion design can convert any source voice signal to target voice signal. But the output will contains some noises. The hardware model can also modify any input voice signal to another form [14]. But modification is very much limited to seven types of output voices. Here also, noises are noticed. Since the source codes of the voice conversion software are huge, it is given in Volume 2, under title Source Code of Voice Modification Software

The Fricative Sound Source Spectrum Derived From a Vocal Tract Analog.

The applications of speech synthesis for computer voice response and speech analysis present the need for highly intelligible and natural synthesized speech. In order to improve the synthesis of fricative and related sounds, the use of simple models for the source spectrum of fricative sounds is investigated. The investigation is based on the use of a vocal tract analog and experimental measurements. Measurements of the sound pressure spectra of fricative consonants are made. Simple sound pressure measurements and measurements based on the technique for measuring intensity are utilized. The fricatives studied are /f/, /th/, /s/, /sh/, and /h/. Fricative sound source spectra are determined by applying an inverse filter to the measured fricative sound pressure spectra. The inverse filtering function is derived from a vocal tract analog. The resulting fricative source spectra are fit to a truncated Fourier series. The results show that structure is evident in all the source spectra except /f/. The presence of structure was related to turbulent flows. The structure of turbulent flows is relevant since fricative sound production is induced by turbulence. The structure of turbulent flows with Reynolds number near the critical Reynolds number is dependent on the initial conditions, the boundary conditions, and on the nonlinearity of the Navier Stokes equations. These three factors are tied together by bifurcation theory which is used to explain the structure present in the fricative source spectra. Also, the possibility that the structure is a by-product of the vocal tract analog is allowed. In any case, the structure evident in the source spectra indicates the use of simple models for the source spectra of fricative sounds is in error or the vocal tract analog requires revision. The fricative source spectra determined in this study can be used in future speech synthesizers. Also, the same procedure employed in this study can be used for speech analysis of speech impaired subjects

Speaker Normalization Using Cortical Strip Maps: A Neural Model for Steady State vowel Categorization

Auditory signals of speech are speaker-dependent, but representations of language meaning are speaker-independent. The transformation from speaker-dependent to speaker-independent language representations enables speech to be learned and understood from different speakers. A neural model is presented that performs speaker normalization to generate a pitch-independent representation of speech sounds, while also preserving information about speaker identity. This speaker-invariant representation is categorized into unitized speech items, which input to sequential working memories whose distributed patterns can be categorized, or chunked, into syllable and word representations. The proposed model fits into an emerging model of auditory streaming and speech categorization. The auditory streaming and speaker normalization parts of the model both use multiple strip representations and asymmetric competitive circuits, thereby suggesting that these two circuits arose from similar neural designs. The normalized speech items are rapidly categorized and stably remembered by Adaptive Resonance Theory circuits. Simulations use synthesized steady-state vowels from the Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)] vowel database and achieve accuracy rates similar to those achieved by human listeners. These results are compared to behavioral data and other speaker normalization models.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Prosthetic Avian vocal organ controlled by a freely behaving bird based on a low dimensional model of the biomechanical periphery

pre-printBecause of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform

Analysis and correction of the helium speech effect by autoregressive signal processing

SIGLELD:D48902/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Prosthetic Avian Vocal Organ Controlled by a Freely Behaving Bird Based on a Low Dimensional Model of the Biomechanical Periphery

Because of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform

Physiologically driven avian vocal synthesizer

Journal ArticleIn this work, we build an electronic syrinx, i.e., a programmable electronic device capable of integrating biomechanical model equations for the avian vocal organ in order to synthesize song. This vocal prosthesis is controlled by the bird's neural instructions to respiratory and the syringeal motor systems, thus opening great potential for studying motor control and its modification by sensory feedback mechanisms. Furthermore, a well-functioning subject-controlled vocal prosthesis can lay the foundation for similar devices in humans and thus provide directly health-related data and procedures

Preliminary candidate advanced avionics system for general aviation

An integrated avionics system design was carried out to the level which indicates subsystem function, and the methods of overall system integration. Sufficient detail was included to allow identification of possible system component technologies, and to perform reliability, modularity, maintainability, cost, and risk analysis upon the system design. Retrofit to older aircraft, availability of this system to the single engine two place aircraft, was considered