Speaker-Independent Word Recognition Based on Recognition of Phonemes and Adaptation to Speakers

研究项目取得的成果总结如下：1。音素的识别我们的研究重点是提高音素的识别率，因为音素在结构分析中起着重要的作用。作为候选词或闭包的验证。结果，在识别元音、元音、鼻音和爆破音方面取得了一些显著的进步。对于元音，我们开发了一种新的基于元音二元关系模型的识别技术。我们开发了一种强大的词识别技术，它由两部分组成。第一部分是我们在字符识别研究中提出的一种模式匹配方法，即联想模式匹配，它在单词的粗略分类中达到了很高的准确率。第二部分是结构分析，即基于音位识别的词变体。我们发现日语元音在其特征空间中表现的二元关系几乎可以看作是独立于说话者的，并开发了上述1中提到的元音识别技术。在对候选词进行验证的过程中，使用元音识别技术可以达到对说话人的适应。单词识别实验将该技术应用于10位男性说话者产生的212个单词，获得了前所未有的识别率，即到第一个候选人的准确率为98.2%，到第二个候选人的准确率为99.6%。然而，这些结果是通过基于1中所述元音识别的结构分析获得的。由于我们的技术还不能在结构分析中使用音素识别，因此采用了D.P.方法。这是一个特征问题。

The results obtained in the research project are summarized as follows.1. Recognition of phonemesOur research stressed on improving the recognition rate of phonemes from the viwe-point that they play an important role in the structural analysis,i.e., verificatgion of words or closes as chandidates. As a result some significant improvements have been obtained especially in recognition of vowels, vowels, nasals and plosives. As for vowels we have developed a new recognition technique based on a binary relational model of vowels.2. Word recognition We have daveloped a powerful technique for word recognition which consists of two parts. The first part is concerned with such a pattern matching method called as an associative pattern matching developed in our research on character recognition and attains a high accuracy in rough classification of words. The second part is concerned with a structural analyusis, that is, varification of the words based on phonem recognition.3. Adaptation to speakerWe have found the binary relations between Japanese vowels represented in their feature space that can be looked as almost independent on speakers and developed the vowel recognition technique mentioned above in 1.. An adaptation to speakers could be attained by using the vowel recognition technique in the process of verification of words given as candidates.4. Recognition ExperimentsThe word recognition technique was applied to 212 words produced by 10 mals speakers, and attained higher recognition rates that had everf obtained, that is, the percentage accuracy up to the 1st condidate was 98.2% and that up to the 2nd one 99.6%. However, these results was obtained by using the structural analysis basedc on the vowel recognition stated in 1. and the method of D.P. since our technique was not yet able to use phoneme recognition in the structural analysis. This is a feature problem.