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			<subfield code="a">ARTICLE</subfield>
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			<subfield code="a">Honnet_SPECOM_2018/IDIAP</subfield>
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		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Intonation modelling using a muscle model and perceptually weighted matching pursuit</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Honnet, Pierre-Edouard</subfield>
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		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Gerazov, Branislav</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Gjoreski, Aleksandar</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Garner, Philip N.</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/papers/2017/Honnet_SPECOM_2018.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
		</datafield>
		<datafield tag="773" ind1=" " ind2=" ">
			<subfield code="p">Speech Communication</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2018</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2=" ">
			<subfield code="u">https://doi.org/10.1016/j.specom.2017.10.004</subfield>
			<subfield code="z">URL</subfield>
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		<datafield tag="024" ind1="7" ind2=" ">
			<subfield code="a">10.1016/j.specom.2017.10.004</subfield>
			<subfield code="2">doi</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">We propose a physiologically based intonation model using perceptual relevance. Motivated by speech synthesis from a
speech-to-speech translation (S2ST) point of view, we aim at a language independent way of modelling intonation. The
model presented in this paper can be seen as a generalisation of the command response (CR) model, albeit with the same
modelling power. It is an additive model which decomposes intonation contours into a sum of critically damped system
impulse responses. To decompose the intonation contour, we use a weighted correlation based atom decomposition
algorithm (WCAD) built around a matching pursuit framework. The algorithm allows for an arbitrary precision to
be reached using an iterative procedure that adds more elementary atoms to the model. Experiments are presented
demonstrating that this generalised CR (GCR) model is able to model intonation as would be expected. Experiments
also show that the model produces a similar number of parameters or elements as the CR model. We conclude that
the GCR model is appropriate as an engineering solution for modelling prosody, and hope that it is a contribution to a
deeper scientific understanding of the neurobiological process of intonation.</subfield>
		</datafield>
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