Polyphone decision tree specialization for language adaptation

Author

Schultz, T. ; Waibel, A.

Author_Institution

Interactive Syst. Labs., Karlsruhe Univ., Germany

Volume

3

fYear

2000

fDate

2000

Firstpage

1707

Abstract

With the distribution of speech technology products all over the world, the fast and efficient portability to new target languages becomes a practical concern. The authors explore the relative effectiveness of adapting multilingual LVCSR systems to a new target language with limited adaptation data. For this purpose they introduce a polyphone decision tree specialization method. Several recognition results are presented based on mono- and multilingual recognizers. These recognizers are developed in the framework of the project GlobalPhone. In this project we investigate speech recognition in 15 languages: Arabic, Mandarin and Shanghai Chinese, Croatian, English, French, German, Japanese, Korean, Portuguese, Russian, Spanish, Swedish, Tamil, and Turkish

Keywords

decision trees; language translation; natural languages; speech recognition; Arabic; Croatian; English; French; German; GlobalPhone; Japanese; Korean; Mandarin; Portuguese; Russian; Shanghai Chinese; Spanish; Swedish; Tamil; Turkish; adaptation data; language adaptation; multilingual LVCSR systems; multilingual recognizers; polyphone decision tree specialization; polyphone decision tree specialization method; recognition results; speech recognition; speech technology product distribution; target language; target languages; Context modeling; Databases; Decision trees; Erbium; Hidden Markov models; Natural languages; Power system modeling; Speech; Target recognition; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1520-6149

Print_ISBN

0-7803-6293-4

Type

conf

DOI

10.1109/ICASSP.2000.862080

Filename

862080