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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Real World Approaches for Multilingual and Non-Native Speech Recognition

Real World Approaches for Multilingual and Non-Native Speech Recognition

Raab, Martin

Paperback

Series: Studien Zur Mustererkennung, Book 32

General Computers

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ISBN10: 3832524460
ISBN13: 9783832524463
Publisher: Logos Verlag Berlin
Published: Apr 26 2010
Pages: 168
Weight: 0.40
Height: 0.48 Width: 5.68 Depth: 8.04
Language: English
In theory multiple languages can be recognized just as one language. However, current state of the art speech recognition systems are based on statistical models with many parameters. Extending such models to multiple languages requires more resources. Therefore a lot of research in the area of multilingual speech recognition has proposed techniques to reduce this need for more resources through parameter tying across languages. This work shows that tying at the density level of Hidden Markov Model based speech recognizers offers the greatest flexibility for the design of a multilingual acoustic model. Furthermore, new algorithms are designed and tested for a fast and efficient creation of systems for many different language combinations. These algorithms base on the addition of only relevant Gaussians and on the projection of a Gaussian mixture distribution to new sets of Gaussians. The positive aspects of the architecture proposed in this work are that non-native accent recognition fruitfully applies knowledge about the mother language of the speakers and that an optimal resource allocation for each language can be guaranteed through an online adaptation to the current tasks.

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