This paper describes an embedded sinusoidal transform codec that is scalable not only in bit-rate, but also in sampling rate. In a representative implementation, the system produces an embedded bit-stream at 3.2 and 6.4 kbit/s for telephone-bandwidth speech, and scales up to 9.6 kbit/s for 16 kHz sampled wideband speech. The 3.2 kbit/s codec is a sinusoidal transform codec with synthetic phases. The 6.4 kbit/s codec adds resolution to the spectral envelope and transmits measured phases of the eight lowest harmonics. The 9.6 kbit/s codec adds information in the 4 to 8 kHz band to provide higher quality wideband speech.

A dual rate embedded sinusoidal transform coder is described in which a core 14th order allpole coder operating at 2400 b/s is augmented with a set of channel gain residuals in order to operate at the higher 4800 b/s rate. The channel. Gains are a set of non-uniformly spaced samples of the spline envelope and constitute a lowpass estimate of the short-time vocal tract magnitude spectrum. The channel gain residuals represent the difference between the spline envelope and the quantized 14th order allpole spectrum at the channel gain frequencies. The channel gain residuals are coded using pitch dependent scalar quantization. Informal listening indicates that the quality of the embedded coder at 4800 b/s is comparable to that of an existing high quality 4800 b/s allpole coder.

The sinusoidal transform coder (STC) is a vocoding technique that has been evolving over the past few years which represents speech as a harmonic set of sinewaves and has demonstrated synthetic speech of good quality at rates from 2400 b/s to 4800 b/s. Previously, a cepstral model was used to code the sinewave amplitudes. This paper reports on a new approach that fits an allpole model to the sine-wave amplitudes and coding is done in terms of both scalar- and vector-quantization of the line spectral frequencies (LSFs). A new measure is developed to objectively quantify the quantizer design performance.>

In the context of a sinusoidal representation for speech waveforms, it is shown that synthetic speech of high quality can be obtained using a parametric model for the sine-wave phases, hence obviating the need to code the phases at low data rates. It was found that if a synthetic linear phase term was computed based on the time of occurrence of an artificially generated sequence of pitch pulses, then high-quality voiced speech reconstruction was possible. For unvoiced speech, the modeling study showed that the sine-wave phases were essentially uniformly distributed random variables.>

It is shown that it is possible to code the parameters of the sinusoidal transform coder (STC) according to Government Standard FS-1015. To accommodate the standard, the voicing probability was quantized to 1 b, and the selection of the voicing threshold was a major focus of the experimental work. Preliminary experiments with the various interoperability configurations have indicated a potential improvement in quality in the fully interoperable STC/STC and LPC/STC modes (C2, D2).>

A technique for estimating the pitch of a speech waveform is developed. It fits a harmonic set of sine waves to the input data using a mean-squared-error (MSE) criterion. By exploiting a sinusoidal model for the input speech waveform, a pitch estimation criterion is derived that is inherently unambiguous, uses pitch-adaptive resolution, uses small-signal suppression to provide enhanced discrimination, and uses amplitude compression to eliminate the effects of pitch-formant interaction. The normalized minimum mean squared error proves to be a powerful discriminant for estimating the likelihood that a given frame of speech is voiced.>

Noise reduction is performed in the context of a high-quality harmonic zero-phase sine-wave analysis/synthesis system which is characterized by sine-wave amplitudes, a voicing probability, and a fundamental frequency. Least-squared error estimation of a harmonic sine-wave representation leads to a soft decision template estimate consisting of sine-wave amplitudes and a voicing probability. The least-squares solution is modified to use template-matching with nearest neighbors. The reconstruction is improved by using the modified least-squares solution only in spectral regions with low signal-to-noise ratio. The results, although preliminary, provide evidence that harmonic zero-phase sine-wave analysis/synthesis, combined with effective estimation of sine-wave amplitudes and probability of voicing, offers a promising approach to noise reduction. >

It has been shown that an analysis-synthesis system based on a sinusoidal representation leads to synthetic speech that is essentially perceptually indistinguishable from the original. A change in speech quality has been observed, however, when the phase relation of the sine waves is altered. This occurs in practice when sine waves are processed for speech enhancement and for speech coding. A description is given of a zero-phase sinusoidal analysis-synthesis system which generates natural-sounding speech without the requirement of vocal tract phase. The method provides a basis for improving sound quality by providing different levels of phase coherence in speech reconstruction for time-scale modification, for a baseline system for coding, and for reducing the peak-to-RMS ratio by dispersion.>

A technique for sine-wave synthesis is described that uses the fast Fourier transform overlap-add method at a 100 Hz rate based on sine-wave parameter coded at a 50 Hz rate. This technique leads to an implementation requiring less than one-half the computational power of a digital-signal-processor chip. The synthesis method implicitly introduces a frequency jitter which renders the encoded synthetic speech more natural. For speech computed by additive acoustic noise, the synthesizer, in conjunction with straightforward noise suppression, greatly improve the quality of the synthetic speech, rendering the sinusoidal transform coder (STC) algorithm a truly robust system. More recent architecture studies of the STC algorithm suggests that an entire implementation requires no more than two ADSP2 100 chips.>

A sinusoidal-based analysis/synthesis system is used to apply radar signal design solutions to the problem of dispersing the phase of a speech waveform. Integrated with dynamic range compression, the resulting system can give a significant reduction in peak/RMS ratio with acceptable loss in quality. The spectral information in the resulting processed speech waveform is embedded primarily within the zero crossings of the modified waveform, rather than the waveform shape. Consequently, this dispersion technique also serves as a preprocessor for waveform clipping, allowing considerably deeper thresholding than can be tolerated on the original waveform.>

It has been shown [1] that an analysis/synthesis system based on a sinusoidal representation leads to synthetic speech that is essentially indistinguishable from the original. By exploiting the peak-to-peak correlation of the sine-wave amplitudes [2], a harmonic model for the sine-wave frequencies, and a predictive model for the sine-wave phases [3], it has also been shown that the sine-wave parameters can be coded at 8 kbps. In this paper a new technique is described for coding the sine-wave amplitudes based on the idea of a pitch-adaptive channel vocoder. Using this amplitude-coding strategy and operating at a total bit rate of 4.8 kbps, it was possible to code and transmit enough phase information so that very intelligible, natural sounding speech could be synthesized. This 4.8 kbps system has been implemented in real-time and has achieved a Diagnostic Rhyme Test (DRT) score of 95. At 2.4 kbps no explicit phase information could be coded, but by phase-locking all of the sine waves to the fundamental, by adding a pitch-adaptive quadratic phase, and by adding a voicing dependent random phase to each sine wave, natural sounding synthetic speech could be obtained. This new system is currently being implemented in real-time so that intelligibility tests can be performed.

This paper describes a new method of deconvolving the vocal cord excitation and vocal tract system response. The technique relies on a sine-wave representation of the speech waveform and forms the basis of an analysis-synthesis method which yields synthetic speech essentially indistinguishable from the original. Unlike an earlier sinusoidal analysis-synthesis technique that used a minimum-phase system estimate, the approach in this paper generates a "mixed-phase" system estimate and thus an improved decomposition of excitation and system components. Since a mixed-phase system estimate is removed from the speech waveform, the resulting excitation residual is less dispersed than the previous sinusoidal-based excitation estimate or the more commonly used linear prediction residual. A method of time-varying linear filtering is given as an alternative to sinusoidal reconstruction, similar to conventional time-domain synthesis used in certain vocoders, but without the requirement of pitch and voicing decisions. Finally, speech modification with a mixed-phase system estimate is shown to be capable of more closely preserving waveform shape in time-scale and pitch transformations than the earlier approach.

In the context of a sinusoidal representation for speech waveforms [1-4], it is shown that the excitation sine-wave phases can be modelled as a linear function of frequency, the slope being determined by the onset time of the underlying pitch pulse. An algorithm for estimating the pitch onset time from the original sine-wave parameters is derived. The new phase model has been used to improve the coding efficiency of the sinusoidal transform coder (STC) and for compensating phase errors introduced by the quantization of the sine-wave frequencies.

In this paper a sinusoidal model for the speech waveform is used to develop a new analysis/synthesis technique that is characterized by the amplitudes, frequencies, and phases of the component sine waves. The resulting synthetic waveform preserves the waveform shape and is essentially perceptually indistinguishable from the original speech. Furthermore, in the presence of noise the perceptual characteristics of the speech and the noise are maintained. Based on this system, a coder operating at 8 kbps is developed that codes the amplitudes and phases of each of the sine wave components and uses a harmonic model to code all of the frequencies. Since not all of the phases can be coded, a high frequency regeneration technique is developed that exploits the properties of the sinusoidal representation of the coded baseband signal. Based on a relatively limited data base, computer simulation has demonstrated that coded speech of good quality can be achieved. A real-time simulation is being developed to provide a more thorough evaluation of the algorithm.

This paper presents a new speech analysis/synthesis technique based on a sinusoidal representation of the speech production mechanism but which is independent of pitch and the voiced/unvoiced speech state. The resulting synthetic speech preserves the waveform shape and is essentially perceptually indistinguishable from the original. The method provides the basis for a general class of speech transformations and is successfully applied to time-scale modification, frequency scaling, and scaling of pitch. Furthermore, these modifications can be performed with a time-varying rate of change, allowing, for example, continuous adjustment of a speaker's fundamental frequency and rate of articulation. Although the analysis/synthesis system was originally designed for single-speaker signals, it is equally capable of recovering and modifying nonspeech signals such as music, multi-speakers, marine biologic sounds, and speech in the presence of interferences such as noise and musical backgrounds.

In this paper a sinusoidal model for the speech waveform is used to develop a new synthesis technique that requires specification of only the amplitudes and frequencies of the component sine waves. These parameters are estimated from the short-time spectral magnitude. The resulting synthetic waveform preserves the short-time spectral magnitude during rapid movements of spectral energy such as voiced/unvoiced transitions, and yields speech of very high quality and intelligibility. The approach is sufficiently flexible to also allow for high-quality time-scale modification with the option of time-varying scaling. Finally, results are given for some initial experiments that explore the possibility of magnitude-only waveform coding at 8 kbps.

A series of experiments were performed to determine (1) the effects of using an energy-based endpoint detector and a conventional isolated word recognition system when the input speech is noisy and (2) the effects of placing a noise suppression prefilter in tandem with the word recognizer in an attempt to remove the noise prior to recognition. It was found that the system consisting of the prefilter working in tandem with the word recognizer increased word recognition accuracy.

A formant-based analysis technique has been developed that avoids some of the problems inherent in formant tracking by fitting a second order spectrum to separate subbands of the measured spectrum. Synthesis is performed using a high quality channel vocoder for which the modulator gains are set by sampling the envelope obtained from the formant-based analysis. By using a fixed bandwidth versus frequency rule, the number of parameters to be transmitted has been limited to the resonant frequency and gain of each of three subbands. By using 4-bit logarithmic coding and frame-fill interpolation methods, successful vocoding at 800 bps has been achieved.

As developed by Atal and Schroeder [1], conventional Adaptive Predictive Coding (APC) of speech employs both vocal tract and pitch prediction to achieve a low energy, spectrally flattened residual. Errors in the pitch predictor can result in clipping errors which can propagate in the system for relatively long periods of time and degrade the quality of the synthesized speech. Makhoul and Berouti [2] have developed a high quality 16 kbps APC system which eliminates the pitch predictor by using a multi-level variable rate quantizer. In order to achieve comparable quality at even lower data rates, a split band APC (SBAPC) structure is proposed which employs the multi-level quantizer on the low frequency portion of the residual and a 1-bit quantizer on the high frequency portion of the residual.

A real time implementation of a system for enhancement of speech in additive acoustic noise is described. The technique used is to perform a spectral decomposition of noisy speech via channel vocoder filter bank analysis and to attenuate each spectral component depending on how much the measured speech plus noise power exceeds an estimate of the background noise. A two state model for the speech event (speech absent or speech present) is applied in determining the maximum likelihood estimator of the speech power. This model has resulted in a new class of suppression curves which permits a tradeoff of noise suppression against speech distortion. Experiments utilizing the real time implementation have shown that the noise can be made imperceptible by proper choice of the suppression factor. Integration of the noise suppression filter into the analysis section of a narrowband vocoder is described. This combined system represents an integrated robust vocoder structure where acoustic noise can be suppressed prior to pitch estimation and determination of the modulator gains.

The problem of estimating the pitch period of a speech waveform contaminated by acoustically coupled background noise is formulated to include the properties of the spectral envelope by postulating a state-variable model for the speech generation process. Applying the maximum likelihood estimation technique, the optimum processor uses a Kalman filter preprocessor to flatten the spectrum. The resulting signal is then passed through a bank of comb filters and the optimum pitch corresponds to the comb filter for which the output energy is smallest. The Kalman prefilter reduces to an LPC filter only when the speech is generated by an all-pole process and the signal-to-noise ratio is large. For the low signal-to-noise ratio case, a parallel formant speech generation model is more likely to lead to practical numerical algorithms for estimating the spectral coefficients.

The Schwarz inequality is used to derive the Barankin lower bounds on the covariance matrix of unbiased estimates of a vector parameter. The bound is applied to communications and radar problems in which the unknown parameter is embedded in a signal of known form and observed in the presence of additive white Gaussian noise. Within this context it is shown that the Barankin bound reduces to the Cramér-Rao bound when the signal-to-noise ratio (SNR) is large. However, as the SNR is reduced beyond a critical value, the Barankin bound deviates radically from the Cramér-Rao bound, exhibiting the so-called threshold effect. The bounds were applied to the linear FM waveform, and within the resulting class of bounds it was possible to select one that led to a closed-form expression for the lower bound on the variance of an unbiased range estimate. This expression clearly demonstrates the threshold behavior one must expect when using a nonlinear modulation system. Tighter bounds were easily obtained, but these had to be evaluated numerically. The sidelobe structure of the linear FM compressed pulse leads to a significant increase in the variance of the estimate. For a practical linear FM pulse of 1-\mu sduration and 40-MHz bandwidth, the radar must operate at an SNR greater than 10 dB if meaningful unbiased range estimates are to be obtained.

In a multiple-target environment a radar signal processor often uses weighting filters that are not matched to the transmitted waveform. In this paper the mean-square range-estimation error, the detection Signal-to-noise ratio (SNR), and the effects of sidelobes are expressed in terms of the impulse response of an arbitrary mismatched filter. It is desired to find that impulse response that results in the minimum range-estimate variance subject to preassigned constraints on the side-lobes and the detection SNR. It is shown that for detecting the radar target and estimating its range, the form of the optimum filter is a modified transversal equalizer. If only detection is required, the optimum filter reduces to the transversal equalizer. Certain parameters upon which the solution depends can be found by solving a nonlinear programming problem. Numerical results are given for an interesting class of transmitted waveforms.

Alternative structures for the optimum detection of Gaussian signals in Gaussian noise are derived that can be interpreted in terms of minimum-mean-squared-error (MMSE) estimators of signal and noise. The realization is useful when the statistics of the signal or noise or both are unknown since the detector can be implemented in an adaptive mode by using tapped delay lines whose weights are adjusted recursively to yield the minimum-mean-squared-error estimate of certain components of the incoming waveforms.

In this correspondence we review some of the difficulties associated with the commonly used bandwidth constraints in the time domain. Then we derive a constraint in state-space, which guarantees that the signal design will result in a waveform having a certain percentage of its energy within a specified frequency band.

A form of Barankin's greatest lower bound on estimation error [7] is obtained, which is easy to compute and easy to interpret. This gives a lower bound on estimation error for non-linear modulation systems in an additive Gaussian noise back-ground. Threshold effects are included. This bound is applied to a set of pulse-position modulation waveforms designed to reduce threshold effects. It is shown that these signals do, in fact, offer reduced threshold levels (e.g.,\approx 3.5dB) with very small (\approx \frac{1}{2}dB) degradation in large signal performance.

A computer-oriented algorithm is developed for designing optimum waveforms for a pulse-position-modulation communication system. Nonlinear modulation threshold effects are incorporated directly into the design by introducing constraints on the sidelobe peaks of the autocorrelation function. The search is performed over the class of signals satisfying constraints on average power, peak power, and bandwidth. The optimum signal in this class is the one whose autocorrelation function has the sharpest central peak while the sidelobe peaks are below the specified constraint level. Numerical results for a realistic problem are presented, and the effect of introducing the correlation and peak power constraints is studied. It is shown that a large reduction in the sidelobe peaks is possible with relatively little loss in the sharpness of the central peak.