Projekt Sprachtechnologie

Formalia

• Instructors: User.WolfgangMenzel, User.TimoBaumann, User.ArneKoehn
• Mixed project (MSc/BSc)
• Thursdays, 12:30-17:45 (lunch break 13:15-13:45, another 15' break)
• F-429 (and F-432), we'll usually start in F-429 and then continue in the Lab
• grading based on active participation, spot talks, and final project report, self management in the group
• Anwesenheitsliste

Proposed project outline

Subtitles for videos are crucial for the hard-of-hearing and can also help normal listener in noisy environments, when consuming video in a foreign language, or to digest complex descriptions. Automatic subtitling requires multiple steps (speech recognition, text preparation and segmentation, time-alignment of text) for result in meaningful subtitles. In a previous project we have worked on time-alignment of text, in this project we would like to focus on the text preparation and segmentation based on speech recognition output.

Aspects of good and bad subtitles

• presence of hesitations/fillers
• repairs/hesitations
  • structure: reparandum, repair marker (quatsch/ähm/falsch/...), reparans/alteration
  • different types
    • modification
    • fresh start of sentence
    • 'abridged repairs' (repair marker only)
  • approaches
    • patterns in transcript [Heeman '94]
    • (PoS -)Tagging [Heeman '96]
    • statistical parser [Charniak '01]
  • mark reparandum instead of deleting it?
• "de-normalize" numbers (precondition for text-processing software to work correctly)
• chunking of subtitles wrt. syntactical chunking
  • focus on sentence structure instead of speech timing
  • rephrase/simplify/"finalize" the structure
• punctuation (in particular sentence boundaries)
  • have a look at https://github.com/ottokart/punctuator
  • how about question marks? should there be question marks?
  • CMUSphinx, forum post about german language model
• length of subtitles
  • one "idea" per subtitle
  • prefer one-line subtitles (what if the "idea" is too long)
  • cut too long lines into two lines
• use colors to mark importance? → helpful for debugging?
• precise timing of subtitles → not so important as it's not important for our target audience(s)

Literature and other links

Various Documents

• FromTranscriptToSubtitles -- What needs do be adjusted (Results Week 2)
• EvaluationCriteria -- What do we want to evaluate in the end?
• Redmine -- Project for tasks and stuff
• TranscriptionGuidelines -- "Hang the code, and hang the rules. They're more like guidelines anyway."
• Presentation

Timeline

Date	What	Who
28.4	Everyone adds a milestone for their workgroup	everyone
28.4	Infrastructure: Repo + Redmine	?
5.5	Get an evaluation framework running with videos + subtitles	Jasper?
5.5	parser in old project should be fixed / replaced	Michael
19.5.	Pfingstferien	everyone
30.6	Buffer + Evaluation Phase	everyone
14.7.	Presentation	everyone

Status 2016-05-12 (before the session)

• post-processing with Language Models (Kolja): in progress, but unsure whether fixable
• post-processing with LSTMs (Theresa): in progress, not working yet
• de-normalization (Felix): using MaryTTS stuff, works well; next: multi-token abbreviations
• extend the main readme of the prosub code (Felix): works
• chunkify module in Python (Michael): works just partially (for English); searches optimal solution
• chunkify module in Java (Tore): works just partially (for German); doesn't find optimal solution?
• evaluation framework (Björn): web evaluation framework is running
• repairs/fillers (Khooshal): repairs, simple algorithms work, context-ones more difficult (German)

Workgroups

What	who
Fillers + Repairs	Khooshal, Wladimir
Punctuation, Capitalization	Kolja, Theresa
Denormalization	Felix?
Framework, old project (Parser ...)	Michael, Felix
Chunking	Tore, Antonia
Optional: shortening subtitles, tagging meta-information (audience questions)

Work items towards good subtitles

• a framework for web-based subtitle evaluation!!
  • Jasper takes a look at BeaqleJS (or alternatives)
• set up some framework of interaction (codepaths and data structures)
  • read through last year's report EVERYONE!
  • Felix and Michael look into last year's repository and framework
• getting everyone to become familiar with Git, decide on programming language(s)?
• finding/fixing repairs (vs. simply skipping all fillers)
  • literature search and/or existing implementations and/or algorithmic approaches in literature (Kolja and Khooshal add links)
  • Papers we found in the first session
    • Detecting and correcting speech repairs
    • Detecting speech repairs incrementally using a noisy channel approach
    • Correction of Disfluencies in Spontaneous Speech using a Noisy-Channel Approach (this is long)
    • A System for Labeling Self-Repairs in Speech
    • A TAG-based noisy channel model of speech repairs
• punctuation recovery
  • Theresa looks at the literature on punctuation recovery (the stuff cited by the sphinx postprocessing framework)
  • Kolja continues the effort on language modelling (i.e., getting the existing tool to work)
• de-normalizing numbers, abbreviations, etc.
  • Felix will work on that (probably based on MaryTTS stuff)
• finding the right length for subtitles (mostly syntactically motivated)

Good for whom/for what situation?

• hearing-impaired persons? → they won't know the congruence anyway
  • [irrelevant discussion of the weather] → mark that, but still spell it out
  • ask Benjamin Kuffel about his preferences/requirements?
    • Antonia and Theresa will ask whether he's interested in an interview (and prepare the interview)
• turn lecturer's speech into a textual form → will improve anyway
  • translation of subtitles is probably much easier than translation of transcripts
• searchability of a lecture → display of search results
• second-language listeners / dialectal differences → stronger congruence between timing/what is said and subtitles
• display subtitles to "normal" students → NOPE, they already use their visual channel for the slides