Formant-based speech synthesizer employing demi-syllable concatenation with independent cross fade in the filter parameter and source domains

Abstract

The concatenative speech synthesizer employs demi-syllable subword units to generate speech. The synthesizer is based on a source-filter model that uses source signals that correspond closely to the human glottal source and that uses filter parameters that correspond closely to the human vocal tract. Concatenation of the demi-syllable units is facilitated by two separate cross face techniques, one applied in the time domain in the demi-syllable source signal waveforms, and one applied in the frequency domain by interpolating the corresponding filter parameters of the concatenated demi-syllables. The dual cross fade technique results in natural sounding synthesis that avoids time-domain glitches without degrading or smearing characteristic resonances in the filter domain.

Description

BACKGROUND AND SUMMARY OF THE INVENTION[0001]The present invention relates generally to speech synthesis and more particularly to a concatenative synthesizer based on a source-filter model in which the source signal and filter parameters are generated by independent cross fade mechanisms.[0002]Modern day speech synthesis involves many tradeoffs. For limited vocabulary applications, it is usually feasible to store entire words as digital samples to be concatenated into sentences for playback. Given a good prosody algorithm to place the stress on the appropriate words, these systems tend to sound quite natural, because the individual words can be accurate reproductions of actual human speech. However, for larger vocabularies it is not feasible to store complete word samples of actual human speech. Therefore, a number of speech synthesis have been experimenting with breaking speech into smaller units and concatenating those units into words, phrases and ultimately sentences.[0003]Unfor...

AI Technical Summary

Benefits of technology

[0006]Our synthesis technique involves identifying and extracting the formants from an actual speech signal (labeled to identify approximate demi-syllable areas) and then using this information to construct demi-syllable segments each represented by a set of filter parameters and a source signal waveform. The invention provides a novel cross fade technique to smoothly concatenate consecutive demi-syllable segments. Unlike conventional blending techniques, our system allows us to perform cross fade in the filter parameter domain while simultaneously but independently performing “cross fade” (parameter interpolation) of the source waveforms in the time domain. The filter parameters model vocal tract effects, while the source waveforms model the global source. The technique has the advantage of restricting prosodic modification to only the glottal source, if desired. This can reduce distortion usually associated with the conventional blending techniques.

Problems solved by technology

However, for larger vocabularies it is not feasible to store complete word samples of actual human speech.

Unfortunately, when concatenating sub-word units, speech synthesis must confront several very difficult problems.

However, such versatile sub-word units often do not concatenate well.

During playback of concatenated sub-word units, there is often a very noticeable distortion or glitch where the sub-word units are joined.

Also, since the sub-word units must be modified in pitch and duration, to realize the intended prosodic pattern, most often a distortion is incurred from current techniques for making these modifications.

Finally, since most speech segments are influenced strongly by neighboring segments, there is not a simple set of concatenation units (such as phonemes or diphones) which can adequately represent human speech.

A number of speech synthesists have suggested various solutions to the above concatenation problems, but so far no one has successfully solve the problem.

Human speech generates complex time-varying waveforms that defy simple signal processing solutions.

The syllable is a natural unit for this purpose, but choosing the syllable requires a large amount of memory.

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