{"date_updated":"2022-01-06T06:51:08Z","language":[{"iso":"eng"}],"abstract":[{"text":"Four methods were used to reduce the error rate of a continuous-density hidden Markov-model-based speech recognizer on the TI/NIST connected-digits recognition task. Energy thresholding sets a lower limit on the energy in each frequency channel to suppress spurious distortion accumulation caused by random noise. This led to an improvement in error rate by 15%. Spectrum normalization was used to compensate for across-speaker variations, resulting in an additional improvement by 20%. The acoustic resolution was increased up to 32 component densities per mixture. Each doubling of the number of component densities yielded a reduction in error rate by roughly 20%. Linear discriminant analysis was used for improved feature selection. A single class-independent transformation matrix was applied to a large input vector consisting of several adjacent frames, resulting in an improvement by 20% for high acoustic resolution. The final string error rate was 0.84%.","lang":"eng"}],"publication":"ICASSP, Minneapolis","title":"Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/1993/ICASSP_1993_Haeb_paper.pdf"}],"user_id":"44006","author":[{"first_name":"Reinhold","id":"242","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"},{"first_name":"Dieter","last_name":"Geller","full_name":"Geller, Dieter"},{"first_name":"Hermann","last_name":"Ney","full_name":"Ney, Hermann"}],"year":"1993","date_created":"2019-07-12T05:28:16Z","status":"public","_id":"11788","department":[{"_id":"54"}],"type":"conference","oa":"1","citation":{"ama":"Haeb-Umbach R, Geller D, Ney H. Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities. In: <i>ICASSP, Minneapolis</i>. ; 1993.","bibtex":"@inproceedings{Haeb-Umbach_Geller_Ney_1993, title={Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities}, booktitle={ICASSP, Minneapolis}, author={Haeb-Umbach, Reinhold and Geller, Dieter and Ney, Hermann}, year={1993} }","ieee":"R. Haeb-Umbach, D. Geller, and H. Ney, “Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities,” in <i>ICASSP, Minneapolis</i>, 1993.","short":"R. Haeb-Umbach, D. Geller, H. Ney, in: ICASSP, Minneapolis, 1993.","apa":"Haeb-Umbach, R., Geller, D., &#38; Ney, H. (1993). Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities. In <i>ICASSP, Minneapolis</i>.","mla":"Haeb-Umbach, Reinhold, et al. “Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities.” <i>ICASSP, Minneapolis</i>, 1993.","chicago":"Haeb-Umbach, Reinhold, Dieter Geller, and Hermann Ney. “Improvements in Connected Digit Recognition Using Linear Discriminant Analysis and Mixture Densities.” In <i>ICASSP, Minneapolis</i>, 1993."}}