9,306 research outputs found
ACCDIST: A Metric for comparing speakers' accents
This paper introduces a new metric for the quantitative assessment of the similarity of speakers' accents. The ACCDIST metric is based on the correlation of inter-segment distance tables across speakers or groups. Basing the metric on segment similarity within a speaker ensures that it is sensitive to the speaker's pronunciation system rather than to his or her voice characteristics. The metric is shown to have an error rate of only 11% on the accent classification of speakers into 14 English regional accents of the British Isles, half the error rate of a metric based on spectral information directly. The metric may also be useful for cluster analysis of accent groups
Speech vocoding for laboratory phonology
Using phonological speech vocoding, we propose a platform for exploring
relations between phonology and speech processing, and in broader terms, for
exploring relations between the abstract and physical structures of a speech
signal. Our goal is to make a step towards bridging phonology and speech
processing and to contribute to the program of Laboratory Phonology. We show
three application examples for laboratory phonology: compositional phonological
speech modelling, a comparison of phonological systems and an experimental
phonological parametric text-to-speech (TTS) system. The featural
representations of the following three phonological systems are considered in
this work: (i) Government Phonology (GP), (ii) the Sound Pattern of English
(SPE), and (iii) the extended SPE (eSPE). Comparing GP- and eSPE-based vocoded
speech, we conclude that the latter achieves slightly better results than the
former. However, GP - the most compact phonological speech representation -
performs comparably to the systems with a higher number of phonological
features. The parametric TTS based on phonological speech representation, and
trained from an unlabelled audiobook in an unsupervised manner, achieves
intelligibility of 85% of the state-of-the-art parametric speech synthesis. We
envision that the presented approach paves the way for researchers in both
fields to form meaningful hypotheses that are explicitly testable using the
concepts developed and exemplified in this paper. On the one hand, laboratory
phonologists might test the applied concepts of their theoretical models, and
on the other hand, the speech processing community may utilize the concepts
developed for the theoretical phonological models for improvements of the
current state-of-the-art applications
Towards Automatic Speech Identification from Vocal Tract Shape Dynamics in Real-time MRI
Vocal tract configurations play a vital role in generating distinguishable
speech sounds, by modulating the airflow and creating different resonant
cavities in speech production. They contain abundant information that can be
utilized to better understand the underlying speech production mechanism. As a
step towards automatic mapping of vocal tract shape geometry to acoustics, this
paper employs effective video action recognition techniques, like Long-term
Recurrent Convolutional Networks (LRCN) models, to identify different
vowel-consonant-vowel (VCV) sequences from dynamic shaping of the vocal tract.
Such a model typically combines a CNN based deep hierarchical visual feature
extractor with Recurrent Networks, that ideally makes the network
spatio-temporally deep enough to learn the sequential dynamics of a short video
clip for video classification tasks. We use a database consisting of 2D
real-time MRI of vocal tract shaping during VCV utterances by 17 speakers. The
comparative performances of this class of algorithms under various parameter
settings and for various classification tasks are discussed. Interestingly, the
results show a marked difference in the model performance in the context of
speech classification with respect to generic sequence or video classification
tasks.Comment: To appear in the INTERSPEECH 2018 Proceeding
Pauses and the temporal structure of speech
Natural-sounding speech synthesis requires close control over the temporal structure of the speech flow. This includes a full predictive scheme for the durational structure and in particuliar the prolongation of final syllables of lexemes as well as for the pausal structure in the utterance. In this chapter, a description of the temporal structure and the summary of the numerous factors that modify it are presented. In the second part, predictive schemes for the temporal structure of speech ("performance structures") are introduced, and their potential for characterising the overall prosodic structure of speech is demonstrated
Reducing Audible Spectral Discontinuities
In this paper, a common problem in diphone synthesis is discussed, viz., the occurrence of audible discontinuities at diphone boundaries. Informal observations show that spectral mismatch is most likely the cause of this phenomenon.We first set out to find an objective spectral measure for discontinuity. To this end, several spectral distance measures are related to the results of a listening experiment. Then, we studied the feasibility of extending the diphone database with context-sensitive diphones to reduce the occurrence of audible discontinuities. The number of additional diphones is limited by clustering consonant contexts that have a similar effect on the surrounding vowels on the basis of the best performing distance measure. A listening experiment has shown that the addition of these context-sensitive diphones significantly reduces the amount of audible discontinuities
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