The present invention concerns a model of the acoustic sound channel associated with the human phonation system and/or music instruments and which has been realized by means of an electrical filter system.
Furthermore, the invention concerns new types of applications of models according to the invention, and a speech synthesizer applying models according to the invention.
The invention also concerns a filter circuit for the modelling of an acoustic sound channel.
In its most typical form, this invention is associated with speech synthesis and with the artificial producing of speech by electronic methods.
One object of the invention is to create a new model for modelling e.g. the acoustic characteristics of the human speech mechanism, or the producing of speech. Models produced by the method may also be used in speech recognition, in estimating the parameters of a genuine speech signal and in so-called Vocoder apparatus, in which speech messages are transferred with the aid of speech signal analysis and synthesis with a minor amount of information e.g. over a low information rate channel, at the same time endeavouring to maintain the highest possible level of speech quality and intelligibility.
Since the model of the invention is intended to be suitable for the modelling of events taking place in an acoustic tube in general, the invention is also applicable to electronic music synthesizers.
The methods of prior art serving the artificial producing of speech are divisible into two main groups. By the methods of the first group only such speech messages can be produced which have at some earlier time been analyzed, encoded and recorded from corresponding genuine speech productions. Best known among these procedures are PCM (Pulse Code Modulation), DPCM (Differential Pulse Code Modulation), DM (Delta Modulation) and ADPCM (Adaptive Differential Pulse Code Modulation). A feature common to these methods of prior art is that they are closely associated with signal theory and with the general signal processing methods worked out on its basis and therefore imply no detailed knowledge of the character or mode of generation of the speech signal.
The second group consists of those methods of prior art in which no genuine speech signal has been recorded, neither as such or in coded form, instead of which the speech is generated by the aid of apparatus modelling the functions of the human speech mechanism. First, from genuine speech are analyzed its recurrent and comparatively invariant elements, phonetic units or phonemes and variants thereof, or phoneme variants, in varying phonetic environments. In the speech synthesizing step, the electronic counterpart of the human speech system, which is referred to as a terminal analog, is so controlled that phonemes and combinations of phonemes equivalent to genuine speech can be formed. To date, these are the only methods by which it has been possible to produce synthetic speech from unrestricted text.
In the territory between the said two groups of methods of prior art is located Linear Predictive Coding, LPC, /1/ J. D. Markel, A. H. Gray Jr.: Linear Prediction of Speech, New York, Springer-Verlag 1976. Differing from other coding methods, this procedure necessitates utilization of a model of speech producing. The starting assumption in linear prediction is that the speech signal is produced by a linear system, to its input being supplied a regular succession of pulses for sonant and a random succession of pulses for unvoiced speech sounds. It is usual to employ as transfer function to be identified, an all-pole model (cf. cascade model). With the aid of speech signal analysis, estimates are calculable for the coefficients (a.sub.i) in the denominator polynomial of the transfer function. The higher the degree of this polynomial (which is also the degree of the prediction), the higher is the precision with which the speech signal can be provided with the aid of the coefficient a.sub.i.
The filter coefficients a.sub.i are however nonperspicuous from the phonetic point of view. To realize a digital filter using these coefficients is also problematic, for instance in view of the filter hardware structures and of stability considerations. It is partly owing to these reasons that one has begun in linear predicting to use a lattice filter having a corresponding transfer function but provided with a different inner structure and using coefficients of different type.
In a lattice filter of prior art, bidirectionally acting and structurally identical elements are connected in cascade. With certain preconditions, this filter type can be made to correspond to the transfer line model of a sound channel composed of homogeneous tubes with equal length. The filter coefficients b.sub.i will then correspond to the coefficients of reflection (.vertline.b.sub.i .vertline.&lt;1). The coefficients b.sub.i are determinable from the speech signal by means of the so-called PARCOR (Partial Correlation) method. Even though the coefficients of reflection b.sub.i are more closely associated with speech production, i.e., with the articulatory aspect, generation of these coefficients by regular synthesis principles has also turned out to be difficult.
It is thus understood that speech synthesis apparatus of the terminal analog type, known in prior art, implies that speech production is modelled starting out from an acoustic-phonetic basis. For the acoustic phonation system, consisting of larynx, pharynx and oral and nasal cavities, an electronic counterpart has to be found of which the transfer function conforms to the transfer function of the acoustic system in all and any enunciating situations. Such a time-variant filter is referred to as a terminal analog because its overall transfer function from input to output, or between the terminals, aims at analogy with the corresponding acoustic transfer function of the human phonation system. The central component of the terminal analog is called the sound channel model. As known, this is in use e.g. in vowel sounds and partly also when synthesizing other sounds, depending on the type of model that is being used.
Since the human phonation system is extremely complex of its acoustical properties, a number of simplifications and approximations must be made when formulating models for practical applications. A problem of principle which figures centrally in such model formulation is that the sound channel is a subdivided system with an acoustic transfer function composed of transcendental functions. Creation of a corresponding terminal analog arrangement using lumped electrical components requires that the acoustic transfer function can be approximated with the aid of rational, meromorphic functions.
Another centrally important point is the controllability of the model, that is the number and type of control parameters required in the model to the purpose of creating speech, and the degree in which the group of control parameters meets the requirements of optimal, "orthogonal" and phonetically clear-cut selection.
As known in the prior art, in constructing sound channel models, the acoustic sound channel is simplified by assuming it to be a straight homogeneous tube, and for this the transfer line equations are calculated (cf. /2/ G. Fant: Acoustic Theory of Speech Production, the Hague, Mouton 1970, Chapters 1.2 and 1.3; and /3/ J. L. Flanagan: Speech Analysis Synthesis and Perception, Berlin, Springer-Verlag 1972, p. 214-228). The assumption is made that the tube has low losses and is closed at one end; the glottis, or the opening between the vocal cords, closed; and the other end opening into the free field. The acoustic load at the mouth opening may be simply modelled either by a short circuit or by a finite impedance Z.sub.r. The acoustic transfer function that is being approximated will then have the form: ##EQU2## where
y (s)=.alpha.+j.beta.=propagation coefficient
.alpha.=attenuation factor
.beta.=.omega./c=phase factor
.omega.=angular frequency
c=velocity of sound
Z.sub.r =radiation load impedance
Z.sub.o =characteristic impedance of the channel
l=length of the channel.
Assuming that the losses of the channel are minor and that the channel terminates in short circuit (Z.sub.r =0), or that the channel is lossless and Z.sub.r is resistive, Equation (1) becomes: ##EQU3## where A, a and k are real. The logarithmic amplitude graph of the absolute value of the transfer function H.sub.A (.omega.) is shown in FIG. 7. The homogeneous sound channel chosen as starting point for the approximation is most nearly equivalent to the situation encountered when pronouncing a neutral vowel (.omega.). The profile of the sound channel and its transfer function are altered for other vowel sounds.