Data processing: speech signal processing – linguistics – language – Speech signal processing – Synthesis
Reexamination Certificate
2001-06-01
2004-10-12
Dorvil, Richemond (Department: 2654)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Synthesis
C704S263000, C704S269000, C704S264000
Reexamination Certificate
active
06804649
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to the field of voice synthesis and, more particularly to improving the expressivity of voiced sounds generated by a voice synthesiser.
2. Description of the Prior Art
In the last few years there has been tremendous progress in the development of voice synthesisers, especially in the context of text-to-speech (TTS) synthesisers. There are two main fundamental approaches to voice synthesis, the sampling approach (sometimes referred to as the concatenative or diphone-based approach) and the source-filter (or “articulatory” approach). In this respect see “Computer Sound Synthesis for the Electronic Musician” by E. R. Miranda, Focal Press, Oxford, UK, 1998.
The sampling approach makes use of an indexed database of digitally recorded short spoken segments, such as syllables, for example. When it is desired to produce an utterance, a playback engine then assembles the required words by sequentially combining the appropriate recorded short segments. In certain systems, some form of analysis is performed on the recorded sounds in order to enable them to be represented more effectively in the database. In others, the short spoken segments are recorded in encoded form: for example, in U.S. Pat. No. 3,982,070 and U.S. Pat. No. 3,995,116 the stored signals are the coefficients required by a phase vocoder in order to regenerate the sounds in question.
The sampling approach to voice synthesis is the approach that is generally preferred for building TTS systems and, indeed, it is the core technology used by most computer-speech systems currently on the market.
The source-filter approach produces sounds from scratch by mimicking the functioning of the human vocal tract—see FIG.
1
. The source-filter model is based upon the insight that the production of vocal sounds can be simulated by generating a raw source signal that is subsequently moulded by a complex filter arrangement. In this context see, for example, “Software for a Cascade/Parallel Formant Synthesiser” by D. Klatt from the Journal of the Acoustical Society of America, 63(2), pp. 971-995, 1980.
In humans, the raw sound source corresponds to the outcome from the vibrations created by the glottis (opening between the vocal chords) and the complex filter corresponds to the vocal tract “tube”. The complex filter can be implemented in various ways. In general terms, the vocal tract is considered as a tube (with a side-branch for the nose) sub-divided into a number of cross-sections whose individual resonances are simulated by the filters.
In order to facilitate the specification of the parameters for these filters, the system is normally furnished with an interface that converts articulatory information (e.g. the positions of the tongue, jaw and lips during utterance of particular sounds) into filter parameters; hence the reason the source-filter model is sometimes referred to as the articulatory model (see “Articulatory Model for the Study of Speech Production” by P. Mermelstein from the Journal of the Acoustical Society of America, 53(4), pp. 1070-1082, 1973). Utterances are then produced by telling the program how to move from one set of articulatory positions to the next, similar to a key-frame visual animation. In other words, a control unit controls the generation of a synthesised utterance by setting the parameters of the sound source(s) and the filters for each of a succession of time periods, in a manner which indicates how the system moves from one set of “articulatory positions”, and source sounds, to the next in successive time periods.
There is a need for an improved voice synthesiser for use in research into the fundamental mechanisms of language evolution. Such research is being performed, for example, in order to improve the linguistic abilities of computer and robotic systems. One of these fundamental mechanisms involves the emergence of phonetic and prosodic repertoires. The study of these mechanisms requires a voice synthesiser that is able to: i) support evolutionary research paradigms, such as self-organisation and modularity, ii) support a unified form of knowledge representation for both vocal production and perception (so as to be able to support the assumption that the abilities to speak and to listen share the same sensory-motor mechanisms), and iii) speak and sing expressively (including emotion and paralinguistic features).
Synthesisers based on the sampling approach do not suit any of the three basic needs indicated above. Conversely, the source-filter approach is compatible with requirements i) and ii) above, but the systems that have been proposed so far need to be improved in order to best fulfil requirement iii).
The present inventor has found that the articulatory simulation used in conventional voice synthesisers based on the source-filter approach works satisfactorily for the filter part of the synthesiser but the importance of the source signal has been largely overlooked. Substantial improvements in the quality and flexibility of source-filter synthesis can be made by addressing the importance of the glottis more carefully.
The standard practice is to implement the source component using two generators: one generator of white noise (to simulate the production of consonants) and one generator of a periodic harmonic pulse (to simulate the production of vowels). The general structure of a voice synthesiser of this conventional type is illustrated in FIG.
2
. By carefully controlling the amount of signal that each generator sends to the filters, one can roughly simulate whether the vocal folds are tensioned (for vowels) or not (for consonants). The main limitations with this method are:
a) The mixing of the noise signal with the pulse signal does not sound realistic: the noise and pulse signals do not blend well together because they are of a completely different nature. Moreover, the rapid switches from noise to pulse, and vice-versa (needed to make words with consonants and vowels) often produces a “buzzy” voice.
b) The spectrum of the pulse signal is composed of harmonics of its fundamental frequency (i.e. FO, 2*FO, 2*(2*FO), 2*(2*(2*FO)) etc.). This implies a source signal whose components cannot vary before entering the filters, thus holding back the timbre quality of the voice.
c) The spectrum of the pulse signal has a fixed envelope where the energy of each of its harmonics decreases exponentially by −6 dB as they double in frequency. A source signal that always has the same spectral shape undermines the flexibility to produce timbral nuances in the voice. Also, high frequency formants are prejudiced in the case where they need to be of higher energy value than the lower ones.
d) In addition to b) and c) above, the spectrum of the source signal lacks a dynamical trajectory: both frequency distances between the spectral components and their amplitudes are static from the outset to the end of a given time period. This lack of time-varying attributes impoverishes the prosody of the synthesised voice.
A particular speech synthesizer based on the source-filter approach has been proposed in U.S. Pat. No. 5,528,726 (Cook), in which different glottal source signals are synthesized. In this speech synthesizer, the filter arrangement uses a digital waveguide network and a parameter library is employed that stores sets of waveguide junction control parameters and associated glottal source signal parameters for generating sets of predefined speech signals. In this system, the basic glottal pulse making up the different glottal source signals is approximated by a waveform which begins as a raised cosine waveshape but then continues in a straight-line portion (closing edge) leading down to zero and remaining at zero for the rest of the period. The different glottal source signals are formed by varying the beginning and ending points of the closing edge, with fixed opening slope and time. Rather than storing representations of these different glottal source signals, the Cook system stores parameters of a Fourier series r
Dorvil Richemond
Frommer William S.
Frommer & Lawrence & Haug LLP
Nolan Daniel
Simon Darren M.
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