TY - CHAP A1 - Haderlein, Tino A1 - Riedhammer, Korbinian A1 - Maier, Andreas A1 - Nöth, Elmar A1 - Toy, Hikmet A1 - Rosanowski, Frank T1 - An Automatic Version of the Post-Laryngectomy Telephone Test T2 - TSD 2007, 10th International Conference on Text, Speech and Dialogue, Proceedings, Pilsen, Czech Republic, September 2007. N2 - Tracheoesophageal (TE) speech is a possibility to restore the ability to speak after total laryngectomy, i.e. the removal of the larynx. The quality of the substitute voice has to be evaluated during therapy. For the intelligibility evaluation of German speakers over telephone, the Post-Laryngectomy Telephone Test (PLTT) was defined. Each patient reads out 20 of 400 different monosyllabic words and 5 out of 100 sentences. A human listener writes down the words and sentences understood and computes an overall score. This paper presents a means of objective and automatic evaluation that can replace the subjective method. The scores of 11 naïve raters for a set of 31 test speakers were compared to the word recognition rate of speech recognizers. Correlation values of about 0.9 were reached. KW - Automatic Speech Recognition KW - Mono Poly KW - Total Laryngectomy KW - Speech Recognition System KW - Automatic Evaluation Y1 - 2007 SP - 238 EP - 245 PB - Springer-Verlag ER - TY - CHAP A1 - Nöth, Elmar A1 - Maier, Andreas A1 - Haderlein, Tino A1 - Riedhammer, Korbinian A1 - Rosanowski, Frank A1 - Schuster, Maria T1 - Automatic Evaluation of Pathologic Speech - from Research to Routine Clinical Use T2 - TSD 2007, 10th International Conference on Text, Speech and Dialogue, Pilsen, Czech Republic, September 2007. N2 - Previously we have shown that ASR technology can be used to objectively evaluate pathologic speech. Here we report on progress for routine clinical use: 1) We introduce an easy-to-use recording and evaluation environment. 2) We confirm our previous results for a larger group of patients. 3) We show that telephone speech can be analyzed with the same methods with only a small loss of agreement with human experts. 4) We show that prosodic information leads to more robust results. 5) We show that text reference instead of transliteration can be used for evaluation. Using word accuracy of a speech recognizer and prosodic features as features for SVM regression, we achieve a correlation of .90 between the automatic analysis and human experts. KW - Automatic Speech Recognition KW - Pathologic Speech KW - Automatic Evaluation KW - Prosodic Feature KW - Speech Recognizer Y1 - 2007 SP - 294 EP - 301 PB - Springer-Verlag ER -