Combined Acoustic and Pronunciation Modelling for Non-Native Speech Recognition

In this paper, we present several adaptation methods for non-native speech recognition. We have tested pronunciation modelling, MLLR and MAP non-native pronunciation adaptation and HMM models retraining on the HIWIRE foreign accented English speech database. The ``phonetic confusion'' scheme we have developed consists in associating to each spoken phone several sequences of confused phones. In our experiments, we have used different combinations of acoustic models representing the canonical and the foreign pronunciations: spoken and native models, models adapted to the non-native accent with MAP and MLLR. The joint use of pronunciation modelling and acoustic adaptation led to further improvements in recognition accuracy. The best combination of the above mentioned techniques resulted in a relative word error reduction ranging from 46% to 71%

Phase sensitive Brillouin scattering measurements with a novel magneto-optic modulator

A recently reported phase sensitive Brillouin light scattering technique is improved by use of a magnetic modulator. This modulator is based on Brillouin light scattering in a thin ferrite film. Using this magnetic modulator in time- and space Brillouin light scattering measurements we have increased phase contrast and excluded influence of optical inhomogeneities in the sample. We also demonstrate that the quality of the resulting interference patterns can be improved by data postprocessing using the simultaneously recorded information about the reference light

DNN-Based Semantic Model for Rescoring N-best Speech Recognition List

The word error rate (WER) of an automatic speech recognition (ASR) system increases when a mismatch occurs between the training and the testing conditions due to the noise, etc. In this case, the acoustic information can be less reliable. This work aims to improve ASR by modeling long-term semantic relations to compensate for distorted acoustic features. We propose to perform this through rescoring of the ASR N-best hypotheses list. To achieve this, we train a deep neural network (DNN). Our DNN rescoring model is aimed at selecting hypotheses that have better semantic consistency and therefore lower WER. We investigate two types of representations as part of input features to our DNN model: static word embeddings (from word2vec) and dynamic contextual embeddings (from BERT). Acoustic and linguistic features are also included. We perform experiments on the publicly available dataset TED-LIUM mixed with real noise. The proposed rescoring approaches give significant improvement of the WER over the ASR system without rescoring models in two noisy conditions and with n-gram and RNNLM

Legal update, Canada: PIPEDA’s Secure Electronic Signature Regulations have been published

Barbara McIsaac QC and Howard R Fohr bring readers up-to-date with the secure electronic signature regulations that have been recently published, and provide an outline of the main provisions of the regulations

Legal update, Canada: PIPEDA’s Secure Electronic Signature Regulations have been published

Barbara McIsaac QC and Howard R Fohr bring readers up-to-date with the secure electronic signature regulations that have been recently published, and provide an outline of the main provisions of the regulations

Kunst zur Sprache bringen: Planung und Umsetzung von erfahrungsorientiertem Lernen im Museum mit der mobilen Applikation Actionbound

er Besuch des außerschulischen Lernortes Kunstmuseum stelltLehrkräftesowohl für Deutsch als Zweitsprache als auch für Deutsch als Fremdsprachevor die Herausforderung, Werke vorab auszuwählen und didaktisch-methodische Vorbereitungen sozu treffen, dass die visuellen und sprachlichen Fähigkeiten der Lernenden sowie Prinzipien der Handlungs-und Erfahrungsorientierung berücksichtigt werden. Kennen Lehrendekreative Methoden zur Erschließung der Kunst und dazu mediale Umsetzungsmöglichkeiten, bereichert der Museumsbesuch durch neue Erfahrungen und weitere Anlässe für die spätere Kommunikation im Klassenraum. Der nachfolgende Beitrag setzt sich mit der Frage auseinander, wie DaFZ-LehrkräfteUnterricht am außerschulischen Lernort Kunstmuseum planen und mit Unterstützung der mobilen Applikation Actionboundrealisieren können. Dazu werden die Einsatzmöglichkeiten des Smartphones zur Auseinandersetzung mit Bildern anhand von erprobten Beispielen beleuchtet und diskutiert