摘要 针对传统的Katz方法会出现折扣系数大于1或者无法计算的情况，将Simple Good Turing中对出现次数对数域的平滑思想用于Katz方法中，结合回退模型，提出一种改进的Katz算法，并将该方法应用于基于Lattice的语音识别系统中，分析不同语言学模型对生成的Lattice结构的影响和基于该结构的识别性能的影响．实验表明，应用改进的Katz算法针对访谈节目的识别性能最高可以达到60.90%，优于传统Katz方法．
Abstract：In traditional Katz approach, the discount coefficients may be greater than 1, or can not be calculated in some serious conditions. To avoid the above problem, the smoothing idea in log domain of Simple GoodTuring combined with backoff model is proposed in the modified Katz approach. The proposed approach is further applied in speech recognition system based on lattice. The analysis of the effects on the structure and performance of lattice with different language model is given. Experiments show that compared with traditional Katz approach, the modified Katz approach can enhance the system performance. The best recognition rate can achieve 60.90% for the corpus from interview program.
张磊, 陆冬, 项学智. 改进的Katz算法及其在基于Lattice识别系统中的应用[J]. 模式识别与人工智能, 2011, 24(2): 249-254.
ZHANG Lei, LU Dong, XIANG Xue-Zhi. Modified Katz Approach and Its Application in Speech Recognition Based on Lattice. , 2011, 24(2): 249-254.
2011, Vol. 24 
