Download Expression in Speech: Analysis and Synthesis by Mark Tatham PDF
By Mark Tatham
All human speech has expression. it really is a part of the 'humanness' of speech, and is a top quality listeners anticipate finding. with out expression, speech sounds useless and synthetic. get rid of expression, and what is left is the naked bones of the meant message, yet not one of the emotions which encompass the message. the aim of this ebook is to offer learn studying expressive content material in speech with the intention to simulating expression in machine speech. people converse expressively with one another in dialog: now within the machine age there's a perceived want for machines to speak expressively with people in discussion.
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Extra info for Expression in Speech: Analysis and Synthesis
Example text
The lowest level of the network has objects of extrinsic allophonic size (Tatham 1971), the highest of sentence size or greater (though these are prosodic, not syntactic domains). Elements within the network all contribute to the plan, rather than just the output layer: it is as though the derivational history of the output layer lives within it. It is important to remember that the layout of a model is initially aimed to make the thinking behind it and its workings clear and transparent. Later we may want to claim some special status for the layout of the model, for example that it reflects some independently verifiable cognitive or physical structure within the human being.
We chose to mention the Holmes system, not because it was the best or the worst, but because it was the most accessible and customizable system of the period. But notwithstanding the early pioneer work in text-to-speech or rule-based synthesis systems, more recent systems developed since the 1980s are more detailed and versatile. 1 Traditional units for synthesis Since our method of describing expression in speech rests on a clear identification of two stages in speech production in the human being, planning and rendering (see Chapter 16), our computational model must be testable on a synthesizer which itself makes just such a distinction.
What assumptions about the data are being made? Assumptions about the data are perfectly legitimate provided they are explicit and expressed in terms preferably of testable hypotheses. So, it might be assumed that the acoustic signal does indeed encode expressiveness (even though this looks obvious). But the assumption should go on to propose how testing might be done in terms of a hypothesis: ‘Anger is expressed by speaking louder and slower’ could be a testable hypothesis, for example. But ‘Let’s see how anger is encoded’ is much less secure an approach.