Thursday, May 16, 2013

LDC May 2013 Newsletter

 
New publications



LDC at ICASSP 2013

LDC will be at ICASSP 2013, the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The event will be held over May 26-31 and we look forward to interacting with members of this community at our exhibit table and during our poster and paper presentations:
Tuesday, May 28, 15:30 - 17:30, Poster Area D
ARTICULATORY TRAJECTORIES FOR LARGE-VOCABULARY SPEECH RECOGNITION
Authors: Vikramjit Mitra, Wen Wang, Andreas Stolcke, Hosung Nam, Colleen Richey, Jiahong Yuan (LDC), Mark Liberman (LDC)
Tuesday, May 28, 16:30 - 16:50, Room 2011
SCALE-SPACE EXPANSION OF ACOUSTIC FEATURES IMPROVES SPEECH EVENT DETECTION
Authors: Neville Ryant, Jiahong Yuan, Mark Liberman (all LDC)
Wednesday, May 29, 15:20 - 17:20, Poster Area D
USING MULTIPLE VERSIONS OF SPEECH INPUT IN PHONE RECOGNITION
Authors: Mark Liberman (LDC), Jiahong Yuan (LDC), Andreas Stolcke, Wen Wang, Vikramjit Mitra
Please look for LDC’s exhibition at Booth #53 in the Vancouver Convention Centre. We hope to see you there!


Early renewing members save on fees

To date just over 100 organizations have joined for Membership Year (MY) 2013.   For the sixth straight year, LDC's early renewal discount program has resulted in significant savings for our members.  Organizations that renewed membership or joined early for MY2013 saved over US$50,000! MY 2012 members are still eligible for a 5% discount when renewing for MY2013. This discount will apply throughout 2013.

Organizations joining LDC can take advantage of membership benefits including free membership year data as well as discounts on older LDC corpora.  For-profit members can use most LDC data for commercial applications.  Please visit our
Members FAQ for further information.

Commercial use and LDC data

Has your company obtained an LDC database as a non-member?  For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases.  Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose.  LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. In the case of a small group of corpora such as American National Corpus (ANC) Second Release (LDC2005T35), Buckwalter Arabic Morphological Analyzer Version 2.0 (LDC2004L02), CELEX2 (LDC96L14) and all CSLU corpora, commercial licenses must be obtained separately from the owners of the data even if an organization is a for-profit member.

New publications

(1) GALE Arabic-English Parallel Aligned Treebank -- Newswire (LDC2013T10) was developed by LDC and contains 267,520 tokens of word aligned Arabic and English parallel text with treebank annotations. This material was used as training data in the DARPA GALE  (Global Autonomous Language Exploitation) program. Parallel aligned treebanks are treebanks annotated with morphological and syntactic structures aligned at the sentence level and the sub-sentence level. Such data sets are useful for natural language processing and related fields, including automatic word alignment system training and evaluation, transfer-rule extraction, word sense disambiguation, translation lexicon extraction and cultural heritage and cross-linguistic studies. With respect to machine translation system development, parallel aligned treebanks may improve system performance with enhanced syntactic parsers, better rules and knowledge about language pairs and reduced word error rate.

In this release, the source Arabic data was translated into English. Arabic and English treebank annotations were performed independently. The parallel texts were then word aligned. The material in this corpus corresponds to the Arabic treebanked data appearing in Arabic Treebank: Part 3 v 3.2 (LDC2010T08) (ATB) and to the English treebanked data in English Translation Treebank: An-Nahar Newswire (LDC2012T02).

The source data consists of Arabic newswire from the Lebanese publication An Nahar collected by LDC in 2002. All data is encoded as UTF-8. A count of files, words, tokens and segments is below.

Language
Files
Words
Tokens
Segments
Arabic
364
182,351
267,520
7,711

Note: Word count is based on the untokenized Arabic source and token count is based on the ATB-tokenized Arabic source.

The purpose of the GALE word alignment task was to find correspondences between words, phrases or groups of words in a set of parallel texts. Arabic-English word alignment annotation consisted of the following tasks:
Identifying different types of links: translated (correct or incorrect) and not translated (correct or incorrect)
Identifying sentence segments not suitable for annotation, e.g., blank segments, incorrectly-segmented segments, segments with foreign languages
Tagging unmatched words attached to other words or phrases
GALE Arabic-English Parallel Aligned Treebank -- Newswire is distributed via web download. 2013 Subscription Members will automatically receive two copies of this data on disc. 2013 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.

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(2) MADCAT Phase 2 Training Set (LDC2013T09) contains all training data created by LDC to support Phase 2 of the DARPA MADCAT (Multilingual Automatic Document Classification Analysis and Translation)Program. The data in this release consists of handwritten Arabic documents, scanned at high resolution and annotated for the physical coordinates of each line and token. Digital transcripts and English translations of each document are also provided, with the various content and annotation layers integrated in a single MADCAT XML output. 

The goal of the MADCAT program is to automatically convert foreign text images into English transcripts. MADCAT Phase 2 data was collected from Arabic source documents in three genres: newswire, weblog and newsgroup text. Arabic speaking scribes copied documents by hand, following specific instructions on writing style (fast, normal, careful), writing implement (pen, pencil) and paper (lined, unlined). Prior to assignment, source documents were processed to optimize their appearance for the handwriting task, which resulted in some original source documents being broken into multiple pages for handwriting. Each resulting handwritten page was assigned to up to five independent scribes, using different writing conditions. 

The handwritten, transcribed documents were checked for quality and completeness, then each page was scanned at a high resolution (600 dpi, greyscale) to create a digital version of the handwritten document. The scanned images were then annotated to indicate the physical coordinates of each line and token. Explicit reading order was also labeled, along with any errors produced by the scribes when copying the text. The annotation results in GEDI XML output files (gedi.xml), which include ground truth annotations and source transcripts.

The final step was to produce a unified data format that takes multiple data streams and generates a single MADCAT XML output file with all required information. The resulting madcat.xml file has these distinct components: (1) a text layer that consists of the source text, tokenization and sentence segmentation, (2)  an image layer that consist of bounding boxes, (3) a scribe demographic layer that consists of scribe ID and partition (train/test) and (4) a document metadata layer. 

This release includes 27,814 annotation files in both GEDI XML and MADCAT XML formats (gedi.xml and madcat.xml) along with their corresponding scanned image files in TIFF format.

MADCAT Phase 2 Training Set is distributed on six DVD-ROM. 2013 Subscription Members will automatically receive two copies of this data on disc. 2013 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.

Wednesday, May 15, 2013

LDC TextPenn Project: Call for Participation

LDC's new TextPenn project will collect and annotate text messaging and chat data in English, Egyptian Arabic and Chinese. We are currently recruiting participants to donate their existing text messages and/or participate in new conversations. Participants who contribute at least 50 messages are entered into a weekly drawing to win $300.

You can learn more about the project or sign up to participate at
https://textpenn.ldc.upenn.edu/textpenn