A quantitative assessment of group delay methods for identifying glottal closures in voiced speech

Published versio

A Quantitative Assessment of Group Delay Methods for Identifying Glottal Closures in Voiced Speech

Abstract-Measures based on the group delay of the LPC residual have been used by a number of authors to identify the time instants of glottal closure in voiced speech. In this paper, we discuss the theoretical properties of three such measures and we also present a new measure having useful properties. We give a quantitative assessment of each measure's ability to detect glottal closure instants evaluated using a speech database that includes a direct measurement of glottal activity from a Laryngograph/EGG signal. We find that when using a fixed-length analysis window, the best measures can detect the instant of glottal closure in 97% of larynx cycles with a standard deviation of 0.6 ms and that in 9% of these cycles an additional excitation instant is found that normally corresponds to glottal opening. We show that some improvement in detection rate may be obtained if the analysis window length is adapted to the speech pitch. If the measures are applied to the preemphasized speech instead of to the LPC residual, we find that the timing accuracy worsens but the detection rate improves slightly. We assess the computational cost of evaluating the measures and we present new recursive algorithms that give a substantial reduction in computation in all cases

A Quantitative Assessment of Group Delay Methods for Identifying Glottal Closures in Voiced Speech

Abstract-Measures based on the group delay of the LPC residual have been used by a number of authors to identify the time instants of glottal closure in voiced speech. In this paper, we discuss the theoretical properties of three such measures and we also present a new measure having useful properties. We give a quantitative assessment of each measure's ability to detect glottal closure instants evaluated using a speech database that includes a direct measurement of glottal activity from a Laryngograph/EGG signal. We find that when using a fixed-length analysis window, the best measures can detect the instant of glottal closure in 97% of larynx cycles with a standard deviation of 0.6 ms and that in 9% of these cycles an additional excitation instant is found that normally corresponds to glottal opening. We show that some improvement in detection rate may be obtained if the analysis window length is adapted to the speech pitch. If the measures are applied to the preemphasized speech instead of to the LPC residual, we find that the timing accuracy worsens but the detection rate improves slightly. We assess the computational cost of evaluating the measures and we present new recursive algorithms that give a substantial reduction in computation in all cases

Estimation of glottal closure instants in voiced speech using the DYPSA algorithm

Published versio

Glottal-synchronous speech processing

Glottal-synchronous speech processing is a field of speech science where the pseudoperiodicity of voiced speech is exploited. Traditionally, speech processing involves segmenting and processing short speech frames of predefined length; this may fail to exploit the inherent periodic structure of voiced speech which glottal-synchronous speech frames have the potential to harness. Glottal-synchronous frames are often derived from the glottal closure instants (GCIs) and glottal opening instants (GOIs). The SIGMA algorithm was developed for the detection of GCIs and GOIs from the Electroglottograph signal with a measured accuracy of up to 99.59%. For GCI and GOI detection from speech signals, the YAGA algorithm provides a measured accuracy of up to 99.84%. Multichannel speech-based approaches are shown to be more robust to reverberation than single-channel algorithms. The GCIs are applied to real-world applications including speech dereverberation, where SNR is improved by up to 5 dB, and to prosodic manipulation where the importance of voicing detection in glottal-synchronous algorithms is demonstrated by subjective testing. The GCIs are further exploited in a new area of data-driven speech modelling, providing new insights into speech production and a set of tools to aid deployment into real-world applications. The technique is shown to be applicable in areas of speech coding, identification and artificial bandwidth extension of telephone speec

Experimental phonetic study of the timing of voicing in English obstruents

The treatment given to the timing of voicing in three areas of phonetic research -- phonetic taxonomy, speech production modelling, and speech synthesis -- Is considered in the light of an acoustic study of the timing of voicing in British English obstruents. In each case, it is found to be deficient. The underlying cause is the difficulty in applying a rigid segmental approach to an aspect of speech production characterised by important inter-articulator asynchronies, coupled to the limited quantitative data available concerning the systematic properties of the timing of voicing in languages. It is argued that the categories and labels used to describe the timing of voicing In obstruents are Inadequate for fulfilling the descriptive goals of phonetic theory. One possible alternative descriptive strategy is proposed, based on incorporating aspects of the parametric organisation of speech into the descriptive framework. Within the domain of speech production modelling, no satisfactory account has been given of fine-grained variability of the timing of voicing not capable of explanation in terms of general properties of motor programming and utterance execution. The experimental results support claims In the literature that the phonetic control of an utterance may be somewhat less abstract than has been suggestdd in some previous reports. A schematic outline is given, of one way in which the timing of voicing could be controlled in speech production. The success of a speech synthesis-by-rule system depends to a great extent on a comprehensive encoding of the systematic phonetic characteristics of the target language. Only limited success has been achieved in the past thirty years. A set of rules is proposed for generating more naturalistic patterns of voicing in obstruents, reflecting those observed in the experimental component of this study. Consideration Is given to strategies for evaluating the effect of fine-grained phonetic rules In speech synthesis

Hilbert phase methods for glottal activity detection

The 2 pi discontinuities found in the wrapped Hilbert phase of the bandpass-filtered analytic DEGG signal provide accurate candidate locations of glottal closure instances (GCIs). Pruning these GCI candidates with an automatically determined amplitude threshold, found by iteratively removing from the full signal the inlier samples within a fraction of its standard deviation until converged, yields a 99.6% accurate detection system with a false alarm rate of 0.17%. This simpler algorithm, named Glottal Activity Detector For Laryngeal Input (GADFLI), outperforms the state-of-the-art SIGMA algorithm for GCI detection, which has a 94.2% detection rate, but a 5.46% false alarm rate. Performance metrics were computed over the entire APLAWD database, using an extensive, hand-verified markings database of 10,944 waveforms. A related proposed algorithm, QuickGCI, also makes use of Hilbert phase discontinuities, and does not require a thresholding post-processing step for GCI selection. Its performance is nearly as good as GADFLI. Both proposed algorithms operate using the electroglottographic signal or acoustic speech signal