start-ver=1.4 cd-journal=joma no-vol= cd-vols= no-issue= article-no= start-page=2464 end-page=2468 dt-received= dt-revised= dt-accepted= dt-pub-year=2018 dt-pub=20180902 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Naturalness Improvement Algorithm for Reconstructed Glossectomy Patient's Speech Using Spectral Differential Modification in Voice Conversion en-subtitle= kn-subtitle= en-abstract= kn-abstract= In this paper, we propose an algorithm to improve the naturalness of the reconstructed glossectomy patient's speech that is generated by voice conversion to enhance the intelligibility of speech uttered by patients with a wide glossectomy. While existing VC algorithms make it possible to improve intelligibility and naturalness, the result is still not satisfying. To solve the continuing problems, we propose to directly modify the speech waveforms using a spectrum differential. The motivation is that glossectomy patients mainly have problems in their vocal tract, not in their vocal cords. The proposed algorithm requires no source parameter extractions for speech synthesis, so there are no errors in source parameter extractions and we are able to make the best use of the original source characteristics. In terms of spectrum conversion, we evaluate with both GMM and DNN. Subjective evaluations show that our algorithm can synthesize more natural speech than the vocoder-based method. Judging from observations of the spectrogram, power in high-frequency bands of fricatives and stops is reconstructed to be similar to that of natural speech. en-copyright= kn-copyright= en-aut-name=MurakamiHiroki en-aut-sei=Murakami en-aut-mei=Hiroki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=HaraSunao en-aut-sei=Hara en-aut-mei=Sunao kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=AbeMasanobu en-aut-sei=Abe en-aut-mei=Masanobu kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=SatoMasaaki en-aut-sei=Sato en-aut-mei=Masaaki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=MinagiShogo en-aut-sei=Minagi en-aut-mei=Shogo kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= affil-num=1 en-affil= kn-affil= affil-num=2 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil= affil-num=3 en-affil=Graduate School of Natural Science and Technology, Okayama University kn-affil= affil-num=4 en-affil=Graduate School of Medicine Dentistry and Pharmaceutical Sciences, Okayama University kn-affil= affil-num=5 en-affil=Graduate School of Medicine Dentistry and Pharmaceutical Sciences, Okayama University kn-affil= en-keyword=voice conversion kn-keyword=voice conversion en-keyword=speech intelligibility kn-keyword=speech intelligibility en-keyword=glossectomy kn-keyword=glossectomy en-keyword=spectral differential kn-keyword=spectral differential en-keyword=neural network kn-keyword=neural network END