37 research outputs found
On the effect of changes in fundamental frequency and vocal effort in naive listener's speaker recognition
Vocal intensity: acoustic and articulatory correlates
Analyses of jaw movement(obtained by Electromagnetic Articulography) and acoustics show that loud speech is an intricate phenomenon. Besides involving higher intensity and subglottal pressure it affects jaw movements as well as fundamental frequency and especially first formants. It is argued that all these effects serve the purpose of enhancing perceptual salience
Towards a new level of annotation detail of multilingual speech corpora
The aim of this paper is to highlight the actual need for corpora that have been annotated based on acoustic information. The acoustic information should be coded in features or properties and is needed to inform further processing systems, i.e. to present a basis for a speech recognition system using linguistic information. Feature annotation of existing corpora in combination with segmental annotation can provide a powerful training material for speech recognition systems, but will as well challenge the further processing of features to segments and syllables. We present here the theoretical preliminaries for our multilingual feature extraction system, that we are currently working on
Some implications for gestural underspecification as a result of the analysis of German /t/ assimilation
As can be shown for English data, the assimilation of the alveolar stop can result from an increased gestural overlap of the following oral closure gesture. Our experiment with German synthetic speech showed similar results. Further, it suggests that it is neccessary to complete the gestural specification of the glottal state. A voiced stop should be represented not only by an oral gesture, but by a glottal one as well
Articulatory-acoustic Feature Recognition: Comparison of Machine Learning and HMM methods
HMMs are the dominating technique used in speech recognition today since they perform well in overall phone recognition. In this paper, we show the comparison of HMM methods and machine learning techniques, such as neural networks, decision trees and ensemble classifiers with boosting and bagging in the task of articulatory-acoustic feature classification. The experimental results show that HMM methods work well for the classification of such features as vocalic. However, decision tree and bagging outperform HMMs for the fricative classification task since the data skewness is much higher than for the feature vocalic classification task. This demonstrates that HMMs do not perform as well as decision trees and bagging in highly skewed data settings
Jaw and Order
It is well-accepted that the jaw plays an active role in influencing vowel height. The general aim of the current study is to further investigate the extent to which the jaw is active in producing consonantal distinctions, with specific focus on coronal consonants. Therefore, tongue tip and jaw positions are compared for the German coronal consonants Is, J, t, d, n, 1/, that is, consonants having the same active articulators (apical/laminal) but differing in manner of articulation. In order to test the stability of articulatory positions for each of these coronal consonants, a natural perturbation paradigm was introduced by recording two levels of vocal effort: comfortable, and loud without shouting. Tongue and jaw movements of five speakers of German were recorded by means of EMMA during /aCa/ sequences. By analyzing the tongue tip and jaw positions and their spatial variability we found that (1) the jaw's contribution to these consonants varies with manner of articulation, and (2) for all coronal consonants the positions are stable across loudness conditions except for those of the nasal. Results are discussed with respect to the tasks of the jaw, and the possible articulatory adjustments that may accompany louder speech
Analysis of tongue configuration in multi-speaker, multi-volume MRI data
MRI data of German vowels and consonants was acquired for 9 speakers. In this paper tongue contours for the vowels were analyzed using the three-mode factor analysis technique PARAFAC. After some difficulties, probably related to what constitutes an adequate speaker sample for this three-mode technique to work, a stable two-factor solution was extracted that explained about 90% of the variance. Factor 1 roughly captured the dimension low back to high front; Factor 2 that from mid front to high back. These factors are compared with earlier models based on PARAFAC. These analyses were based on midsagittal contours; the paper concludes by illustrating from coronal and axial sections how non-midline information could be incorporated into this approach
A Multilingual Phonological Resource Toolkit for Ubiquitous Speech Technology
This paper outlines the generation process of a specifi computational linguistic representation termed the Multilingual Time Map, conceptually a multi-tape finit state transducer encoding linguistic data at different levels of granularity. The fi st component acquires phonological data from syllable labeled speech data, the second component define feature profiles the third component generates feature hierarchies and augments the acquired data with the define feature profiles and the fourth component displays the Multilingual Time Map as a graph
Formant Trajectory Dynamics in Swabian Diphthongs
The vowel quality in some diphthongs of Swabian (an upper german dialect) was determined by measurement of first and second formant values. A minimal contrast could be shown between two different diphthong qualities […], where for Standard German only one is assumed, viz. /ai/. The two diphthong qualities differ only slightly in onset and offset vowel quality, so a better understanding of their relationship was expected from an examination of their dynamic aspects. Our preliminary results suggest that there is indeed a difference in the temporal structure of the two diphthongs