Construction of a corpus of elderly Japanese speech for analysis and recognition

Tokushima UniversityAichi Prefectural UniversityUniversity of YamanashiLREC 2018 Special Speech Sessions "Speech Resources Collection in Real-World Situations"; Phoenix Seagaia Conference Center, Miyazaki; 2018-05-09We have constructed a new speech data corpus using the utterances of 100 elderly Japanese people, in order to improve the accuracy of automatic recognition of the speech of older people. Humanoid robots are being developed for use in elder care nursing facilities because interaction with such robots is expected to help clients maintain their cognitive abilities, as well as provide them with companionship. In order for these robots to interact with the elderly through spoken dialogue, a high performance speech recognition system for the speech of elderly people is needed. To develop such a system, we recorded speech uttered by 100 elderly Japanese who had an average age of 77.2, most of them living in nursing homes. Another corpus of elderly Japanese speech called S-JNAS (Seniors-Japanese Newspaper Article Sentences) has been developed previously, but the average age of the participants was 67.6. Since the target age for nursing home care is around 75, much higher than that of most of the S-JNAS samples, we felt a more representative corpus was needed. In this study we compare the performance of our new corpus with both the Japanese read speech corpus JNAS (Japanese Newspaper Article Speech), which consists of adult speech, and with the S-JNAS, the senior version of JNAS, by conducting speech recognition experiments. Data from the JNAS, S-JNAS and CSJ (Corpus of Spontaneous Japanese) was used as training data for the acoustic models, respectively. We then used our new corpus to adapt the acoustic models to elderly speech, but we were unable to achieve sufficient performance when attempting to recognize elderly speech. Based on our experimental results, we believe that development of a corpus of spontaneous elderly speech and/or special acoustic adaptation methods will likely be necessary to improve the recognition performance of dialog systems for the elderly