CSEM Scientific and Technical Report 2008

Vocal Aid for Laryngectomees
P. Renevey, O. Schleusing, R. Vetter, P. Theurillat, M. Correvon, J. M. Solà i Carós
After an operation of laryngectomy (partial or total removal of the vocal folds) the quality of the residual voice is significantly degraded. The project
Larynx aims at the development of a non-invasive voice restoration system that improves the quality of speech in real time while preserving original
idiosyncrasies of the original voice. The recent advances of this research activity are presented in the following.
People who have undergone laryngectomy, to treat laryngeal
cancer, loose the ability to speak. The vocal function can be
recovered partially through medical rehabilitation, although,
with a loss of speech intensity, a poor quality of the pitch
(fundamental frequency of speech) and large variations in the
energy of producing speech signals.
To overcome these deficiencies, a vocal aid system has been
designed and developed. This system aims at restoring in
real-time the quality of speech by the use of digital signal
processing techniques [1] . The proposed restoration approach
is mainly based on an autoregressive analysis of speech
signal that separates the excitation signal (produced by the
lungs and the larynx) and the articulation (produced by
resonances in the oral and nasal cavities). These components
are then restored separately and merged afterwards to get the
restored speech signal (see Figure 1). Such an approach
preserves the idiosyncrasies from the original voice while
improving its overall quality.
Figure 1: Block diagram and illustrative example of the targeted vocal
aid system for laryngectomees.
Previous research activities have highlighted two key issues
for restoring voices of good quality. These points are namely
the estimation of the fundamental frequency during voiced
speech (e.g. vowels) and the detection of these voiced
segments. Therefore, recent work performed in the framework
of this activity has been focused on these two aspects.
Fundamental frequency refers to the vibration frequency of the
vocal folds during voiced sounds. Such sounds are produced
when the speaker closes his vocal folds. The air expelled from
the lungs forces a way through the folds and makes them
vibrate. The tension applied to the folds controls the frequency
of vibration and introduces variations around its mean values
(e.g. accentuation or singing). The correct estimation of the
fundamental frequency and of its variations are of great
importance for the achievement of restoring voice that sounds
natural. After a laryngectomy, these vibrations are no more
produced by the vocal folds (removed by the surgical
operation) but by the remaining flesh structure of the larynx. It
results in a vibration of poor quality with frequent breakdown
of energy and frequency. Under these circumstances,
classical approaches fail to estimate it correctly. Different
methods for pitch estimation in pathological voices have been
developed and analyzed in respect to their performances and
feasibility in a real-time environment. A new method called
Adaptive Wavetable Oscillators, has shown in a large variety
of experiments, that it can out-perform more complex methods
when applied to synthetic and healthy speech signals,
especially with varying levels of additive noise being present.
In subjective listening tests the presented method performs
similar to more complex and established methods. Due to the
fact that it is remarkably inexpensive from the computational
point of view, the method bears a great potential for
employment in mobile, embedded applications [2, 3] .
An algorithm for the detection of voiced segments, based on
Hidden Markov Model, has been developed and evaluated.
This classification system, trained specifically for each subject,
has been shown to obtain adequate performances for the
planned system. Classification of pathological voices obtains
results that are comparable to those obtained with healthy
voices up to an expected small reduction of the performances.
The requirement of a specific training for each user is only a
minor drawback because a session of recording and
adjustments would be required to match the patient voice and
the desired restored voice characteristics.
The presented solutions represent a step forward in
developing a complete operational vocal aid system. The
ongoing work now consists of the integration of the proposed
solution in the complete restoration algorithm and its
implementation in a real-time demonstration platform
developed by HEIG-VD.
The partners of the project are the University of Applied
Science in Yverdon (HEIG-VD – responsible for the
development of the real-time platform), the University Hospital
in Lausanne (CHUV – responsible for the medical issues) and
the Swiss Institute for Technology in Lausanne (EPFL –
supporting CSEM for the signal processing tasks).
This work was jointly funded by the Gebert Rüf Stiftung and
OncoSuisse. CSEM thanks them for their support.
[1] R. Vetter, J. Cornuz, P. Vuadens, J. M. Solà i Carós, P. Renevey,
“Method and System for Converting Voice”, European Patent EP
1 710 788 A1, 2006
[2] F. N. Reale, J. M. Solà i Carós, P. Renevey, R. Vetter,
“Restoration of Natural Prosody in Pathological Voices”, Swiss
Society for Biomedical Engineering (SSBE), Annual Meeting
2007, Neuchâtel
[3] O. Schleusing, R. Vetter, P. Renevey, J. Krauss, F.N. Reale,
V. Schweizer and J.-M. Vesin, “Restoration of Prosody in
Tracheoesophageal Speech by a Multi-Resolution Approach”,
submitted to IASTED Software Engineering Conference 2009,
Innsbruck
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