Seminar "Selected Topics in Human Language Technology and Pattern Recognition"

Registration for the seminar

Prerequisites for participation in the seminar

• Bachelor students: Einführung in das wissenschaftliche Arbeiten (Proseminar)
• Master students: Bachelor degree
• Attendance of at least one of the lectures (Introduction to) Pattern Recognition and Neural Networks, (Introduction to) Statistical Classification, (Introduction to) Automatic Speech Recognition, or (Introduction to) Statistical Methods in Natural Language Processing, or evidence of equivalent knowledge.
• For successful participants of the above lectures, the possibility of a seminar talk is guaranteed.

Seminar format and important dates

• Proposals: initial proposals (report's content page) have to be submitted by email to your supervisors by April 6, 2015. At this time participants must arrange an appointment with the individual supervisor.
• Article: must be submitted at least 1 month prior to the trial presentation date, but not later than May 17, 2015 to the individual supervisor in electronic form (PDF).
  
• Presentation slides: must be submitted at least 1 week prior to the trial presentation date to the individual supervisor in electronic form (PDF).
• Trial presentations: at least 2 weeks prior to the actual presentation date. Please refer to your individual supervisor to schedule your trial presentation.
• Seminar presentations:will be scheduled after the kick-off meeting, see comments above on seminar mode.
• Final (corrected) articles and presentation slides: must be submitted 2 weeks after the presentation date at the latest to the individual supervisor in electronic form (PDF).
• Compulsory attendance: in order to receive a certificate participants must attend all presentation sessions.
• Ethical Guidelines:The Computer Science Department of RWTH Aachen University has adopted ethical guidelines for the authoring of academic work such as seminar reports. Each student has to comply with these guidelines. In this regard, you, as a seminar attendant, have to sign a declaration of compliance, in which you assert that your work complies with the guidelines, that all references used are properly cited, and that the report was done autonomously by yourself. We ask you do download the guidelines and submit the declaration together with your seminar report and talk to your individual supervisor. You also find a German version of the guidelines and a German version of the declaration you may use as well.

Note: failure to meet deadlines, absence without permission from compulsory sessions (presentations and preliminary meeting as announced by email to each participating student), or dropping out of the seminar after more than 3 weeks after the kick-off meeting (i.e. after March 23, 2015) results in the grade 5.0/not appeared.

Topics, relevant references and participants

1. D. Yu, L. Deng: Automatic Speech Recognition: A Deep Learning Approach, Springer-Verlag, London 2015, 321 pages.
2. X. He, L. Deng: Discriminative Learning for Speech Recognition: Theory and Practice, Morgan and Claypool Publishers, 2008, 112 pages.
3. A. Graves, S. Fernandez, F. Gomez, J. Schmidhuber: "Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks," in Proc. 23rd Intern. Conf. on Machine Learning (ICML), pp. 369-376, Pittsburgh, PA, 2006.
4. H. Schwenk: "Continuous Space Language Models," in Computer Speech & Language, Vol. 21, No. 3, pp. 492-518, 2007.
5. T. Mikolov, M. Karafiát, L. Burget, J. Cernocký, S. Khudanpur: "Recurrent Neural Network based Language Model," in Proc. Interspeech 2010, pp. 1045-1048, Makuhari, Chiba, Japan, Sept. 2010.
6. T. Mikolov, S. Kombrink, L. Burget, J. Cernocký, S. Khudanpur: "Extensions of Recurrent Neural Network Language Model," in Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing (ICASSP), pp. 5528-5531, Prague, Czech Republic, May 2011.

1. Automatic Speech Recognition: Introduction and Applications [1, Sec. 1] (NN; Betreuer: Christian Oberdörfer)
   
2. Gaussian Mixture HMMs [1, Secs. 2 & 3] (NN; Betreuer: Christian Oberdörfer)
3. Discriminative Training of Generative Models [2] (NN; Betreuer: Ralf Schlüter)
   
4. Deep Neural Networks [1, Sec. 4] (Chebbi; Betreuer: Tamer Alkhouli)
   Vortrag: 08.06.2015
5. Advanced Model Initialization [1, Sec. 5] (Sun; Betreuer: Tamer Alkhouli)
   Vortrag: 22.06.2015
6. DNN Hybrid Modeling [1, Sec. 6] (Gleim; Betreuer: Eugen Beck)
   Vortrag: 15.06.2015
7. Training and Decoding Speedup [1, Sec. 7] (NN; Betreuer: Eugen Beck)
8. DNN Sequence-Discriminative Training [1, Sec. 8] (NN; Betreuer: Albert Zeyer)
9. CTC-Training [3] (Ellers; Betreuer: Albert Zeyer)
   Vortrag: 15.06.2015
10. Feature Representation Learning in DNNs [1, Sec. 9] (NN; Betreuer: Zoltan Tüske)
    Vortrag: 22.06.2015
11. Tandem Modeling [1, Sec. 10] (Stanchev; Betreuer: Zoltan Tüske)
    Vortrag: 22.06.2015
12. DNN Adaptation [1, Sec. 11] (Rogner; Betreuer: Pavel Golik)
    Vortrag: 29.06.2015
13. Representation Sharing and Transfer in DNNs [1, Sec. 12] (Niu; Betreuer: Pavel Golik)
    Vortrag: 29.06.2015
14. Recurrent and Convolutional Neural Networks [1, Secs. 13 and 15.1.7] (Wang; Betreuer: Harald Hanselmann)
    Vortrag: 29.06.2015
15. Computational Networks [1, Sec. 14] (Boldbaatar; Betreuer: Harald Hanselmann)
    Vortrag: 06.07.2015
16. Feed-Forward Neural Network-based Language Modeling [4] (Schwaiger; Betreuer: Kazuki Irie)
    Vortrag: 06.07.2015
17. Recurrent Neural Network-based Language Modeling [5] and [6] (Zhang; Betreuer: Kazuki Irie)
    Vortrag: 06.07.2015

Guidelines for the article and presentation

• Online LaTeX-Documentation:

• LaTeX: "A document preparation system"
• LaTeX help 1.1
• The Not So Short Introduction to LaTeX
  
  
• LaTeX 2e for authors

• Document Templates:

• Article Template (164kB),  contains the template and all necessary files in tar format (or here 53kB in zip format).
• Presentation Slide Template (4.9MB), a zip file containing the template and all necessary graphics as well as the institute’s style template.

• Guidelines for articles and presentation slides:

• The aim of the seminar for the participants is to learn the following:
• to tackle a topic and to expand knowledge
• to critically analyze the literature
  
  
• to hold a presentation
  
  
• Take notice of references to other topics in the seminar and discuss topics with one another!
  
  
• Take care to stay within your own topic. To this end participants should be aware of the other topics in the seminar. If applicable, cross-reference other articles and presentations.
  
  

• Important: As part of the introduction, a slide should outline the most important literature used for the presentation. In addition, the presentation should clearly indicate which literature the particular elements of the presentation refer to.
  
  
• Take notice of references to other topics in the seminar and discuss topics with one another!
  
  
• Participants are expected to seek out additional literature on their topic. Assistance with the literature search is available at the faculty’s library. Access to literature is naturally also available at the Lehrstuhl Informatik 6 library.
• Notation/Mathematical Formulas: consistent, correct notation is essential. When necessary, differing notation from various literature sources is to be modified or standardized in order to be clear and consistent. The lectures held by the Lehrstuhl Informatik 6 should provide a guide as to what appropriate notation should look like.
  
  
• Tables must have titles (appearing above the table).
• Figures must have captions (appearing below the figure).
  
  
• In the case that no adequate translation of an English technical term is available, the term should be used unchanged.
• Articles and presentation slides can also be prepared in English.
  
  
• Completeness: acknowledge all literature and sources.
  
  
• Referencing must conform to the standard described in the article template.
• Examples should be used to illustrate points.
• Examples should be as complex as necessary but as simple as possible.
• Slides should be used as presentation aids and not to replace the role of the presenter; specifically, slides should:
• illustrate important points and relationships;
• remind the audience (and the presenter) of important aspects and considerations;
  
  
• give the audience an overview of the presentation.
  
  
• Slides should not contain chunks of text or complicated sentences; rather they should consist of succinct words and terms.
• Use illustrations where appropriate - a picture says a thousand words!
• Abbreviations should be defined at the first usage in the manner demonstrated in the following example: "[...] at the Rheinisch-Westfälischen Technischen Hochschule (RWTH) there are [...]".
  
  
• Take care to stay within your own topic. To this end participants should be aware of the other topics in the seminar. If applicable, cross-reference other articles and presentations.
• Usage of fonts, typefaces and colors in presentation slides must be consistent and appropriate. Such means should serve to clarify points or relationships, not be applied needlessly or at random.
  
  
• Care should be taken when selecting fonts for presentation slides (also within diagrams) to ensure legibility on a projector even for those seated far from the screen.

Contact

Dr. Ralf Schlüter
RWTH Aachen
Lehrstuhl Informatik 6
Ahornstr. 55
52056 Aachen Raum 6125b
Telefon: 0241 / 80-21612
E-Mail: schlueter@cs.rwth-aachen.de

Last modified: 2015-06-29 11:03:43 Disclaimer.