We propose a new excitation source signal for VOCODERs and an all-pass impulse response for post-processing of synthetic sounds and pre-processing of natural sounds for data-augmentation. The proposed signals are variants of velvet noise, which is a sparse discrete signal consisting of a few non-zero (1 or -1) elements and sounds smoother than Gaussian white noise. One of the proposed variants, FVN (Frequency domain Velvet Noise) applies the procedure to generate a velvet noise on the cyclic frequency domain of DFT (Discrete Fourier Transform). Then, by smoothing the generated signal to design the phase of an all-pass filter followed by inverse Fourier transform yields the proposed FVN. Temporally variable frequency weighted mixing of FVN generated by frozen and shuffled random number provides a unified excitation signal which can span from random noise to a repetitive pulse train. The other variant, which is an all-pass impulse response, significantly reduces "buzzy" impression of VOCODER output by filtering. Finally, we will discuss applications of the proposed signal for watermarking and psychoacoustic research.
One efficient method for reducing the buzzy'' impression is to randomize the phase. Group delay manipulation used in legacy-STRAIGHT was successful for reducing this impression @cite_43 . The log domain pulse model (LDPM) also uses phase manipulation @cite_15 . However, such manipulation results smearing of the signal in the time domain. Although time windowing solves this smearing problem, it introduces other problem, power spectral modification due to the statistical fluctuation of the truncated signal. An element signal of the proposed FVN (Frequency domain Velvet Noise) has an excellent time-frequency localization made possible by a six-term cosine series introduced for antialiasing glottal excitation models @cite_22 . Also, because it is an all-pass filter's impulse response, it is free from statistical fluctuation in power spectrum of the processed signal.
@cite_43 @cite_15 @cite_22
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Abstract A set of simple new procedures has been developed to enable the real-time manipulation of speech parameters. The proposed method uses pitch-adaptive spectral analysis combined with a surface reconstruction method in the time–frequency region. The method also consists of a fundamental frequency (F0) extraction using instantaneous frequency calculation based on a new concept called fundamentalness'. The proposed procedures preserve the details of time–frequency surfaces while almost perfectly removing fine structures due to signal periodicity. This close-to-perfect elimination of interferences and smooth F0 trajectory allow for over 600 manipulation of such speech parameters as pitch, vocal tract length, and speaking rate, while maintaining high reproductive quality. We formulated and implemented a procedure to generate aliasing-free excitation source signals. It uses a new antialiasing filter in the continuous time domain followed by an IIR digital filter for response equalization. We introduced a cosine-series-based general design procedure for the new antialiasing function. We applied this new procedure to implement the antialiased Fujisaki-Ljungqvist model. We also applied it to revise our previous implementation of the antialiased Fant-Liljencrants model. A combination of these signals and a lattice implementation of the time varying vocal tract model provides a reliable and flexible basis to test fo extractors and source aperiodicity analysis methods. MATLAB implementations of these antialiased excitation source models are available as part of our open source tools for speech science.