Reconstruction of articulatory movements during neutral speech from those during whispered speech

Meenakshi, G.; Ghosh, Prasanta Kumar

doi:10.1121/1.5039750

Cited by 5 publications

(2 citation statements)

References 31 publications

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“…Data obtained through these sensor positions allow to estimate variations in lip aperture or lip protrusion that are phonetically relevant (e.g., production of bilabial stops as compared to fricatives, or between rounded and unrounded vowels). In some cases, such as when a study focuses on lip movements specifically, more lip sensors are attached, namely at the right and/or left lip corners (e.g., Meenakshi & Ghosh, 2018;Rong et al, 2012;Cler, Lee, Mittelman, Stepp, & Bohland, 2017).…”

Section: Use and Positioningmentioning

confidence: 99%

A review of data collection practices using electromagnetic articulography

Rebernik

Jacobi

Jonkers

et al. 2021

Laboratory Phonology: Journal of the Association for Laboratory Phonology

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This paper reviews data collection practices in electromagnetic articulography (EMA) studies, with a focus on sensor placement. We first introduce electromagnetic articulography as a method. We then focus on existing data collection practices. Our overview is based on a literature review of 905 publications from a large variety of journals and conferences, identified through a systematic keyword search in Google Scholar. The review shows that experimental designs vary greatly, which in turn may limit researchers' ability to compare results across studies. Finally, we describe an EMA data collection procedure that includes an articulatory-driven strategy for determining where to position sensors on the tongue without causing discomfort to the participant. We also evaluate three approaches for preparing (NDI Wave) EMA sensors reported in the literature with respect to the duration the sensors remain attached to the tongue: 1) attaching out-of-thebox sensors, 2) attaching sensors coated in latex, and 3) attaching sensors coated in latex with an additional latex flap. Results indicate no clear general effect of sensor preparation type on adhesion duration. A subsequent exploratory analysis reveals that sensors with the additional flap tend to adhere for shorter times than the other two types, but that this pattern is inverted for the most posterior tongue sensor.

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Section: Use and Positioningmentioning

confidence: 99%

A review of data collection practices using electromagnetic articulography

Rebernik

Jacobi

Jonkers

et al. 2021

Laboratory Phonology: Journal of the Association for Laboratory Phonology

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“…Motivated by the methodology proposed in [29], we consider a set of M training utterances for N, F and S speaking rates, each comprising articulatory movement data from K articulators. Let R stand for either F or S rate movements.…”

Section: Learning the Transformation Functionsmentioning

confidence: 99%

Relating Articulatory Motions in Different Speaking Rates

Singh¹,

Meenakshi

Ghosh

2018

Interspeech 2018

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Movements of articulators (e.g., tongue, lips and jaw) in different speaking rates are related in a complex manner. In this work, we examine the underlying function to transform articulatory movements involved in producing speech at a neutral speaking rate into those at fast and slow speaking rates (N2F and N2S). For this we use articulatory movement data collected from five subjects using an Electromagnetic articulograph at neutral, fast and slow speaking rates. As candidate transformation functions (TF), we use affine transformations with a diagonal matrix and a full matrix and a nonlinear function modeled by a deep neural network (DNN). Since the duration of an utterance in different speaking rates would typically be unequal, it is required to time align the articulatory movement trajectories, which, in turn, affects the TF learnt. Therefore, we propose an iterative algorithm to alternately optimize for the TF and the time alignments. Subject specific experiments reveal that while N2F transformation can be well described by an affine transformation with a full matrix, N2S transformation is better represented by a more complex nonlinear function modeled by a DNN. This could be because subjects exhibit gross articulatory movements during fast speech and hyper-articulate while producing slow speech.

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Silent Speech Interfaces for Speech Restoration: A Review

et al. 2020

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This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-acoustic biosignals generated by the human body during speech production to enable communication whenever normal verbal communication is not possible or not desirable. In this review, we focus on the first case and present latest SSI research aimed at providing new alternative and augmentative communication methods for persons with severe speech disorders. SSIs can employ a variety of biosignals to enable silent communication, such as electrophysiological recordings of neural activity, electromyographic (EMG) recordings of vocal tract movements or the direct tracking of articulator movements using imaging techniques. Depending on the disorder, some sensing techniques may be better suited than others to capture speech-related information. For instance, EMG and imaging techniques are well suited for laryngectomised patients, whose vocal tract remains almost intact but are unable to speak after the removal of the vocal folds, but fail for severely paralysed individuals. From the biosignals, SSIs decode the intended message, using automatic speech recognition or speech synthesis algorithms. Despite considerable advances in recent years, most present-day SSIs have only been validated in laboratory settings for healthy users. Thus, as discussed in this paper, a number of challenges remain to be addressed in future research before SSIs can be promoted to real-world applications. If these issues can be addressed successfully, future SSIs will improve the lives of persons with severe speech impairments by restoring their communication capabilities.

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Reconstruction of articulatory movements during neutral speech from those during whispered speech

Cited by 5 publications

References 31 publications

A review of data collection practices using electromagnetic articulography

A review of data collection practices using electromagnetic articulography

Relating Articulatory Motions in Different Speaking Rates

Silent Speech Interfaces for Speech Restoration: A Review

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