Instants Of Significant Excitation Research Articles

Pitch synchronous and glottal closure based speech analysis for language recognition

This paper explores pitch synchronous and glottal closure (GC) based spectral features for analyzing the language specific information present in speech. For determining pitch cycles (for pitch synchronous analysis) and GC regions, instants of significant excitation (ISE) are used. The ISE correspond to the instants of glottal closure (epochs) in the case of voiced speech, and some random excitations like onset of burst in the case of nonvoiced speech. For analyzing the language specific information in the proposed features, Indian language speech database (IITKGP-MLILSC) is used. Gaussian mixture models are used to capture the language specific information from the proposed features. Proposed pitch synchronous and glottal closure spectral features are evaluated using language recognition studies. The evaluation results indicate that language recognition performance is better with pitch synchronous and GC based spectral features compared to conventional spectral features derived through block processing. GC based spectral features are found to be more robust against degradations due to background noise. Performance of proposed features is also analyzed on standard Oregon Graduate Institute Multi-Language Telephone-based Speech (OGI-MLTS) database.

Non-uniform time scale modification using instants of significant excitation and vowel onset points

In this paper, a non-uniform time scale modification (TSM) method is proposed for increasing or decreasing speech rate. The proposed method modifies the durations of vowel and pause segments by different modification factors. Vowel segments are modified by factors based on their identities, and pause segments by uniform factors based on the desired speaking rate. Consonant and transition (consonant-to-vowel) segments are not modified in the proposed TSM. These modification factors are derived from the analysis of slow and fast speech collected from professional radio artists. In the proposed TSM method, vowel onset points (VOPs) are used to mark the consonant, transition and vowel regions, and instants of significant excitation (ISE) are used to perform TSM as required. The VOPs indicate the instants at which the onsets of vowels take place. The ISE, also known as epochs, indicate the instants of glottal closure during voiced speech, and some random excitations such as burst onset during non-voiced speech. In this work, VOPs are determined using multiple sources of evidence from excitation source, spectral peaks, modulation spectrum and uniformity in epoch intervals. The ISEs are determined using a zero-frequency filter method. The performance of the proposed non-uniform TSM scheme is compared with uniform and existing non-uniform TSM schemes using epoch and time domain pitch synchronous overlap and add (TD-PSOLA) methods.

Two speaker speech separation by LP residual weighting and harmonics enhancement

This paper presents a method for separating speech of individual speakers from the combined speech of two speakers. The main objective of this work is to demonstrate the significance of the combined excitation source based temporal processing and short-time spectrum based spectral processing method for the separation of speech produced by individual speakers. Speech in a two speaker environment is simultaneously collected over two spatially separated microphones. The speech signals are first subjected to excitation source information (linear prediction residual) based temporal processing. In temporal processing, speech of each speaker is enhanced with respect to the other by relatively emphasizing the speech around the instants of significant excitation of desired speaker by deriving speaker-specific weight function. To further improve the separation, the temporally processed speech is subjected to spectral processing. This involves enhancing the regions around the pitch and harmonic peaks of short time spectra computed from the temporally processed speech. To do so the pitch estimate is obtained from the temporally processed speech. The performance of the proposed method is evaluated using (i) objective quality measures: percentage of energy loss, percentage of noise residue, the signal-to-noise ratio (SNR) gain and perceptual evaluation of speech quality (PESQ), and (ii) subjective quality measure: mean opinion score (MOS). Experimental results are reported for both real and synthetic speech mixtures. The SNR gain and MOS values show that the proposed combined temporal and spectral processing method provides an average improvement in the performance of 5.83% and 8.06% respectively, compared to the best performing individual temporal or spectral processing methods.

Real Time Prosody Modification

Real time prosody modification involves changing the prosody parameters such as pitch, duration and intensity of speech in real time without affecting the intelligibility and naturalness. In this paper prosody modification is performed using instants of significant excitation (ISE) of the vocal tract system during production of speech. In the conventional prosody modification system the ISE are computed using group delay function, and it is computationally intensive task. In this paper, we propose computationally efficient methods to determine the ISE suitable for prosody modification in interactive (real time) applications. The overall computational time for the prosody modification by using the proposed method is compared with the conventional prosody modification method which uses the group delay function for computing the ISE.

Duration modification using glottal closure instants and vowel onset points

This paper proposes a method for duration (time scale) modification using glottal closure instants (GCI, also known as instants of significant excitation) and vowel onset points (VOP). In general, most of the time scale modification methods attempt to vary the duration of speech segments uniformly over all regions. But it is observed that consonant regions and transition regions between a consonant and the following vowel, and between two consonant regions do not vary appreciably with speaking rate. The proposed method implements the duration modification without changing the durations of the transition and consonant regions. Vowel onset points are used to identify the transition and consonant regions. A VOP is the instant at which the onset of the vowel takes place, which corresponds to the transition from a consonant to the following vowel in most cases. The VOPs are computed using the Hilbert envelope of linear prediction (LP) residual. The instants of significant excitation correspond to the instants of glottal closure (epochs) in the case of voiced speech, and to some random excitations, like the onset of burst, in the case of nonvoiced speech. Manipulation of duration is achieved by modifying the duration of the LP residual with the help of instants of significant excitation as pitch markers. The modified residual is used to excite the time-varying filter whose parameters are derived from the original speech signal. Perceptual quality of the synthesized speech is found to be natural. Performance of the proposed method is compared with the method, where the duration of speech is modified uniformly over all regions. Samples of speech signals for different modification factors is available for listening at http://sit.iitkgp.ernet.in/~ksrao/result.html.

Voice conversion by mapping the speaker-specific features using pitch synchronous approach

The basic goal of the voice conversion system is to modify the speaker-specific characteristics, keeping the message and the environmental information contained in the speech signal intact. Speaker characteristics reflect in speech at different levels, such as, the shape of the glottal pulse (excitation source characteristics), the shape of the vocal tract (vocal tract system characteristics) and the long-term features (suprasegmental or prosodic characteristics). In this paper, we are proposing neural network models for developing mapping functions at each level. The features used for developing the mapping functions are extracted using pitch synchronous analysis. Pitch synchronous analysis provides the estimation of accurate vocal tract parameters, by analyzing the speech signal independently in each pitch period without influenced by the adjacent pitch cycles. In this work, the instants of significant excitation are used as pitch markers to perform the pitch synchronous analysis. The instants of significant excitation correspond to the instants of glottal closure (epochs) in the case of voiced speech, and to some random excitations like onset of burst in the case of nonvoiced speech. Instants of significant excitation are computed from the linear prediction (LP) residual of speech signals by using the property of average group-delay of minimum phase signals. In this paper, line spectral frequencies (LSFs) are used for representing the vocal tract characteristics, and for developing its associated mapping function. LP residual of the speech signal is viewed as excitation source, and the residual samples around the instant of glottal closure are used for mapping. Prosodic parameters at syllable and phrase levels are used for deriving the mapping function. Source and system level mapping functions are derived pitch synchronously, and the incorporation of target prosodic parameters is performed pitch synchronously using instants of significant excitation. The performance of the voice conversion system is evaluated using listening tests. The prediction accuracy of the mapping functions (neural network models) used at different levels in the proposed voice conversion system is further evaluated using objective measures such as deviation ( D i ) , root mean square error ( μ RMSE ) and correlation coefficient ( γ X , Y ). The proposed approach (i.e., mapping and modification of parameters using pitch synchronous approach) used for voice conversion is shown to be performed better compared to the earlier method (mapping the vocal tract parameters using block processing) proposed by the author.