Measurement of temporal changes in vocal tract area function from 3D cine-MRI data

Abstract

A 3D cine-MRI technique was developed based on a synchronized sampling method [Masaki et al., J. Acoust. Soc. Jpn. E 20, 375-379 (1999)] to measure the temporal changes in the vocal tract area function during a short utterance /aiueo/ in Japanese. A time series of head-neck volumes was obtained after 640 repetitions of the utterance produced by a male speaker, from which area functions were extracted frame-by-frame. A region-based analysis showed that the volumes of the front and back cavities tend to change reciprocally and that the areas near the larynx and posterior edge of the hard palate were almost constant throughout the utterance. The lower four formants were calculated from all the area functions and compared with those of natural speech sounds. The mean absolute percent error between calculated and measured formants among all the frames was 4.5%. The comparison of vocal tract shapes for the five vowels with those from the static MRI method suggested a problem of MRI observation of the vocal tract: data from static MRI tend to result in a deviation from natural vocal tract geometry because of the gravity effect.

Vocal tract resonances in speech, singing, and playing musical instruments

“…Singers produce the singers formant by keeping the larynx low and by narrowing the epilaryngeal tube-a constriction in the vocal tract just above the larynx (Sundberg, 1974;Imagawa et al, 2003;Dang and Honda, 1997;Kitamura et al, 2005;Takemoto et al, 2006aTakemoto et al, , 2006b). Of course, R3, R4, and R5 are properties of the tract as a whole, rather than just of the epilaryngeal tube (Sundberg, 1974).…”

A Technique to Reduce Motion Artifact for Externally Triggered Cine-MRI(EC-MRI) Based on Detecting the Onset of the Articulated Word with Spectral Analysis

“…However, motion artifacts result from inconsistencies among the many utterance repetitions this technique requires. 13,14 In particular, image quality is seriously damaged by contamination of MR imaging data from irregular motion during acquisition that aŠects the central region of the k-space. In this study, we proposed a new method to improve the quality of the resulting images of EC-MRI by reducing acoustic noise in the subject's speech sound data, detecting exact onset time of each utterance, and rearranging the k-space based on the detected onset time.…”

“…15 However, a remaining problem is inconsistency in the subject's repetitive utterances that leads to motion artifact in the resulting movie of MR images. 13,14 At present, we can only reduce this motion artifact using classical and passive methods, such as averaging data obtained in multiple EC-MRI sessions, which requires more utterance repetitions that might fatigue subjects.…”

Analysing and Understanding the Singing Voice: Recent Progress and Open Questions

“…From this image, the shape of the vocal tract may be estimated and, using a model, the acoustic properties of the tract may be calculated e.g. [82,83]. For analysing the singing voice, this has the complications that MRI images are usually acquired with the subject lying down, which may change the vocal geometry, and in the presence of high levels of noise.…”