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A signal distance classifier can now be constructed as follows:

1.Record a vowel /a:/ or /i:/ and select a time window of suitable length. It is recommended to select a window which has sufficient signal energy.

2.Calculate the zero-crossing rate of the recorded signal.

3.Calculate the derivative of the recorded signal using Equation 14.10.

4.Calculate the zero-crossing rate of the differentiated signal.

5.Form the feature vector describing the vowel /a:/ or /i:/ using the zerocrossing rates obtained in steps 2 and 4.

6.Repeat steps 1–5 until you have a sufficient data for both /a:/ and /i:/.

7.From this data, compute the means of the vectors for the two classes separately. These means will be used as the representatives ra and ri of the two classes, as discussed in Section 14.3.1.

8.Write an algorithm which calculates the distances d(ra, x) and d(ri, x) between a given two-dimensional feature vector x and the representatives

computed in step 7.

All these steps could be performed manually. However, there are advantages in writing a computer program to implement them. It should now be possible to classify an “unknown” sound as /a:/ or /i:/ using the decision rule given in Equation 14.5.

P.3 Project in concatenative speech synthesis.

Experiments in diphone concatenation can be used to improve understanding of the problems in the acoustic component of a TTS system. However, the preparation of a complete diphone set would require excessive effort. Therefore the tutorial “Speech Synthesis” (Hoffmann et al. 1999b) is recommended instead. It can be found at the following URL:

http://www.ias.et.tu-dresden.de/sprache/lehre/multimedia/tutorial/ index.html

One section of this tutorial offers a selection of carrier words. You should define the boundaries of the diphones contained in these words in an interactive way and combine these diphones in an arbitrary way to form new words.

References

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Further Reading

Books

Furui, S., 2001: Digital Speech Processing, Synthesis, and Recognition. Second edition, Marcel Dekker, New York

Holmes, J.N., 1988. Speech synthesis and Recognition. London: Chapman and Hall. German translation by G. Ruske published in 1991, Oldenbourg Verlag, München und Wien

Jurafsky, D., and Martin, J.H., 2000. Speech and Language Processing. Prentice Hall, New Jersey

Selected Periodicals in Speech Technology

IEEE Transactions on Speech and Audio Processing. A publication of the IEEE Signal Processing Society. IEEE, New York

Speech Communication. A publication of the European Association for Signal Processing (EURASIP) and of the International Speech Communication Association (ISCA). Elsevier Science B. V., Amsterdam

Computer Speech and Language. Academic Press/Elsevier, Amsterdam etc

554 14 Speech, Text and Braille Conversion Technology

International Journal of Speech Technology. Published in association with the Applied Voice Input/Output Society (AVIOS). Kluwer Academic Publishers, Norwell, MA

Leading Conferences in Speech Technology

EUROSPEECH (European Conference on Speech Communication and Technology). An Interspeech event

ICSLP (International Conference on Spoken Language Processing). An Interspeech Event ICASSP (IEEE International Conference on Acoustics, Speech, and Signal Processing) ICPhS (International Congress on Phonetic Sciences)

Resources

The following web sites give information on general aspects of speech and language technology. For further details, see the URLs cited in the text and the tables. Although the author considers the external web sites referred to in this chapter useful, he does not vouch for their accuracy.