| Paper: | SP-P3.14 (ICASSP 2003 Paper) | ||
| Session: | Topics in Speaker and Langauge Recognition | ||
| Time: | Tuesday, May 18, 15:30 - 17:30 | ||
| Presentation: | Poster (ICASSP 2003 Presentation) | ||
| Topic: | Speech Processing: Language Identification | ||
| Title: | SCALABLE NEURAL NETWORK BASED LANGUAGE IDENTIFICATION FROM WRITTEN TEXT | ||
| Authors: | Jilei Tian; Nokia Research Center | ||
| Janne Suontausta; Nokia Research Center | |||
| Abstract: | Automatic language identification is an integral part of multilin-gual automatic speech recognition and synthesis systems. In this paper, we propose a novel scalable method for neural network based language identification from written text. The developed algorithm is further deployed in a multilingual ASR system. The developed algorithm is particularly proposed for embedded im-plementation platforms with sparse memory resources. With the proposed approach, both high language identification as well as recognition rates are achieved across several languages with a compact size of the language identification model. The major benefit of the approach is that the neural network based language identification model can be scaled to meet the memory require-ments set by the target platform while maintaining the language identification accuracy of the baseline system. The experiments show that the suggested scalable approach can save more than 50% memory while the performance is comparable to that of the base-line system. The performance is also verified in a multilingual speech recognition task. | ||
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