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The tracheoesophageal (TE) substitute voice is currently state–of–the–art treatment to restore the ability to speak after laryngectomy. The intelligibility while talking over a telephone is an important clinical factor, as it is a crucial part of the patients’ social life. An objective way to rate the intelligibility of substitute voices when talking over a telephone is desirable to improve the post–laryngectomy speech therapy. An automatic speech recognition (ASR) system was applied to 41 high quality recordings of post–laryngectomy patients. The ASR system was trained with normal, non–pathologic speech. It yielded a word accuracy (WA) of 36.9%±18.0%; compared to the intelligibility rating of a group of human experts the ASR system had a correlation coefficient of -.88. After downsampling the 41 recordings to telephone quality, the ASR system reached a WA of 26.4%±13.9% leading to a correlation coefficient of -.80. These results confirm that an ASR system can be used for objective intelligibility rating over the telephone.
Die tracheoösophageale Ersatzstimme: Automatische Verständlichkeitsbewertung über das Telefon
(2006)
Die tracheoösophageale Ersatzstimme TE ist heute "state of the art" der Stimmrehabilitation nach einer Laryngektomie. In dieser Studie, einem Teilprojekt eines von der Deutschen Krebshilfe geförderten Forschungsvorhabens, ging es um die objektive Bewertung des Behandlungsfortschritts. Untersucht wurden 41 Laryngektomierte mit einer TE (Provox-Stimmventilprothese) durchgeführt. Ziel der Studie war es, die Verständlichkeit im Gespräch und am Telefon objektiv zu beurteilen und zu vergleichen, um den Patienten in der Zukunft die telefonische Evaluation von zuhause aus zu ermöglichen. Zur Bewertung diente ein für Marktzwecke professionalisiertes automatisches Spracherkennungssystem. Es wurden zunächst Nahbesprechungsaufnahmen des "Nordwind und Sonne"-Textes von fünf Experten hinsichtlich ihrer Verständlichkeit beurteilt. Aus diesen Aufnahmen entstanden durch Abspielen über ein Telefon simulierte Telefonaufnahmen. Zielkriterium der automatischen Analyse war die Wortakkuratheit WA, die mit der an Schulnoten orientierten Stimmbewertung durch die Experten korreliert wurde. Die Studie ergab eine Korrelation von -0,82 für die Nahbesprechungs- und -0,69 für die Telefonaufnahmen. Die Ergebnisse zeigen, dass die automatische Verständlichkeitsbewertung von Ersatzstimmen auch per Telefon prinzipiell möglich ist. Möglichkeiten, die Qualitätsverluste durch die Telefonübertragung und die somit niedrigere Korrelation zu kompensieren, werden aufgezeigt.
For many aspects of speech therapy an objective evaluation of the intelligibility of a patient's speech is needed. We investigate the evaluation of the intelligibility of speech by means of automatic speech recognition. Previous studies have shown that measures like word accuracy are consistent with human experts' ratings. To ease the patient's burden, it is highly desirable to conduct the assessment via phone. However, the telephone channel influences the quality of the speech signal which negatively affects the results. To reduce inaccuracies, we propose a combination of two speech recognizers. Experiments on two sets of pathological speech show that the combination results in consistent improvements in the correlation between the automatic evaluation and the ratings by human experts. Furthermore, the approach leads to reductions of 10% and 25% of the maximum error of the intelligibility measure.
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.
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.
In früheren Arbeiten wurde gezeigt, dass automatische Spracherkennungsverfahren verwendet werden können, um die Verständlichkeit von Sprechern mit tracheoösophagealer Ersatzstimme (TE-Stimme) automatisch zu bewerten [1,2]. In diesem Beitrag wird eine automatische Version des Postlaryngektomie-Telefontests (PLTT, [3]) vorgestellt, der einen eingeführten Standardtest für die Verständlichkeit über das Telefon darstellt.
Rooted in multi-document summarization, maximum marginal relevance (MMR) is a widely used algorithm for meeting summarization (MS). A major problem in extractive MS using MMR is finding a proper query: the centroid based query which is commonly used in the absence of a manually specified query, can not significantly outperform a simple baseline system. We introduce a simple yet robust algorithm to automatically extract keyphrases (KP) from a meeting which can then be used as a query in the MMR algorithm. We show that the KP based system significantly outperforms both baseline and centroid based systems. As human refined KPs show even better summarization performance, we outline how to integrate the KP approach into a graphical user interface allowing interactive summarization to match the user's needs in terms of summary length and topic focus.
The CALO meeting assistant provides for distributed meeting capture, annotation, automatic transcription and semantic analysis of multiparty meetings, and is part of the larger CALO personal assistant system. This paper summarizes the CALO-MA architecture and its speech recognition and understanding components, which include real-time and offline speech transcription, dialog act segmentation and tagging, question-answer pair identification, action item recognition, decision extraction, and summarization.
Despite considerable work in automatic meeting summarization over the last few years, comparing results remains difficult due to varied task conditions and evaluations. To address this issue, we present a method for determining the best possible extractive summary given an evaluation metric like ROUGE. Our oracle system is based on a knapsack-packing framework, and though NP-Hard, can be solved nearly optimally by a genetic algorithm. To frame new research results in a meaningful context, we suggest presenting our oracle results alongside two simple baselines. We show oracle and baseline results for a variety of evaluation scenarios that have recently appeared in this field.