LDC 2015 March Newsletter

Spring 2015 LDC Data Scholarship recipients

2001 HUB5 English Evaluation update

New publications:

GALE Chinese-English Parallel Aligned Treebank -- Training

GALE Phase 3 and 4 Arabic Broadcast Conversation ParallelText

Mandarin-English Code-Switching in South-East Asia

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Spring 2015 LDC Data Scholarship recipients

Congratulations to the recipients of LDC's Spring 2015 data scholarships:

Christopher Kotfila ~ State University of New York, Albany (USA), PhD Candidate, Informatics. Christopher has been awarded copies of Message Understanding Conference and ACE 2005 SpatialML for his work in named entity extraction.  
  
Ilia Markov ~ National Polytechnic University (Mexico), PhD candidate, Computer Science. Ilia has been awarded a copy of the ETS Corpus of Non-Native Written English for his work in native language identification    

Matthew Nelson ~ Georgia State University (USA), MA candidate, Applied Linguistics. Matthew has been awarded a copy of TIMIT and Nationwide Speech for his work in speaker perception.   

Meladianos Polykarpos ~ Athens University of Economics and Business (Greece), PhD candidate, Informatics. Meladianos has been awarded a copy of TDT5 Text and Topics/Annotations for his work in information retrieval.  

Benjamin Schloss ~ Pennsylvania State University (USA), PhD candidate, Psychology. B
Benjamin has been awarded a copy of the ETS Corpus of Non-Native Written English for his work in semantics.

For program information visit the Data Scholarship page.

2001 HUB5 English Evaluation update

2001 HUB5 English Evaluation (LDC2002S13) now includes corresponding transcriptions.  The transcripts are available as part of the web download for this data.  Additionally, all HUB5 English catalog entries have been updated to reflect LDC's current standards for documentation and metadata.

New publications:

(1) GALE Chinese-English Parallel Aligned Treebank -- Training was developed by LDC and contains 229,249 tokens of word aligned Chinese and English parallel text with treebank annotations. This material was used as training data in the DARPA GALE (Global Autonomous Language Exploitation) program.

The Chinese source data was translated into English. Chinese and English treebank annotations were performed independently. The parallel texts were then word aligned. The material in this release corresponds to portions of the Chinese treebanked data in Chinese Treebank 6.0 (LDC2007T36) (CTB), OntoNotes 3.0 (LDC2009T24) and OntoNotes 4.0 (LDC2011T03).

This release consists of Chinese source broadcast programming (China Central TV, Phoenix TV), newswire (Xinhua News Agency) and web data collected by LDC. The distribution by genre, words, character tokens, treebank tokens and segments appears below:

Genre	Files	Words	CharTokens	CTBTokens	Segments
bc	10	57,571	86,356	60,270	3,328
nw	172	64,337	96,505	57,722	2,092
wb	86	30,925	46,388	31,240	1,321
Total	268	152,833	229,249	149,232	6,741

Note that all token counts are based on the Chinese data only. One token is equivalent to one character and one word is equivalent to 1.5 characters.

The Chinese word alignment task consisted of the following components:

• Identifying, aligning, and tagging eight different types of links
• Identifying, attaching, and tagging local-level unmatched words
• Identifying and tagging sentence/discourse-level unmatched words
• Identifying and tagging all instances of Chinese 的 (DE) except when they were a part of a semantic link

This release contains nine types of files - Chinese raw source files, English raw translation files, Chinese character tokenized files, Chinese CTB tokenized files, English tokenized files, Chinese treebank files, English treebank files, character-based word alignment files, and CTB-based word alignment files.

GALE Chinese-English Parallel Aligned Treebank -- Training is distributed via web download.  2015 Subscription Members will automatically receive two copies of this corpus on disc.  2015 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) GALE Phase 3 and 4 Arabic Broadcast Conversation Parallel Text was developed by LDC. Along with other corpora, the parallel text in this release comprised training data for Phases 3 and 4 of the DARPA GALE (Global Autonomous Language Exploitation) Program. This corpus contains Modern Standard Arabic source text and corresponding English translations selected from broadcast conversation data collected by LDC between 2006 and 2008 and transcribed and translated by LDC or under its direction.

GALE Phase 3 and 4 Arabic Broadcast Conversation Parallel Text includes 55 source-translation document pairs, comprising 280,535 words of Arabic source text and its English translation. Data is drawn from 22 distinct Arabic programs broadcast between 2006 and 2008. Broadcast conversation programming is generally more interactive than traditional news broadcasts and includes talk shows, interviews, call-in programs and roundtables.

The files in this release were transcribed by LDC staff and/or transcription vendors under contract to LDC in accordance with the Quick Rich Transcription guidelines developed by LDC. Transcribers indicated sentence boundaries in addition to transcribing the text. The transcribed and segmented files were reformatted into a human-readable translation format and assigned to translation vendors. Translators followed LDC's Arabic to English translation guidelines. Bilingual LDC staff performed quality control procedures on the completed translations.

GALE Phase 3 and 4 Arabic Broadcast Conversation Parallel Text is distributed via web download.  2015 Subscription Members will automatically receive two copies of this corpus on disc.  2015 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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(3) Mandarin-English Code-Switching in South-East Asia was developed by Nanyang Technological University and Universiti Sains Malaysia in Singapore and Malaysia, respectively. It is comprised of approximately 192 hours of Mandarin-English code-switching speech from 156 speakers with associated transcripts.

Code-switching refers to the practice of shifting between languages or language varieties during conversation. This corpus focuses on the shift between Mandarin and English by Malaysian and Singaporean speakers. Speakers engaged in unscripted conversations and interviews. In the conversational speech segments, two speakers conversed freely with each other. The interviews consisted of questions from an interviewer and answers from an interviewee; only the interviewee's speech was recorded. Topics discussed range from hobbies, friends, and daily activities.

The speakers were gender-balanced (49.7% female, 50.3% male) and between 19 and 33 years of age. Over 60% of the speakers were Singaporean; the rest were Malaysian.

The speech recordings were conducted in a quiet room using several microphones and recording devices. Details about the recording conditions are contained in the documentation provided with this release. The audio files in this corpus are 16KHz, 16-bit recordings in flac compressed wav format between 20 and 120 minutes in length.

Selected segments of the audio recordings were transcribed. Most of those segments contain code-switching utterances.

Mandarin-English Code-Switching in South-East Asia is distributed on two DVD-ROM.  2015 Subscription Members will automatically receive two copies of this corpus.  2015 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for a fee.

LDC April 2014 Newsletter

New publications:

Domain-Specific Hyponym Relations
GALE Arabic-English Parallel Aligned Treebank -- WebTraining
Multi-Channel WSJ Audio 

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(1) Domain-Specific Hyponym Relations was developed by the Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Technology at Xi’an Jiaotung University, Xi’an, Shaanxi, China. It provides more than 5,000 English hyponym relations in five domains including data mining, computer networks, data structures, Euclidean geometry and microbiology. All hypernym and hyponym words were taken from Wikipedia article titles.

A hyponym relation is a word sense relation that is an IS-A relation. For example, dog is a hyponym of animal and binary tree is a hyponym of tree structure. Among the applications for domain-specific hyponym relations are taxonomy and ontology learning, query result organization in a faceted search and knowledge organization and automated reasoning in knowledge-rich applications.

The data is presented in XML format, and each file provides hyponym relations in one domain. Within each file, the term, Wikipedia URL, hyponym relation and the names of the hyponym and hypernym words are included. The distribution of terms and relations is set forth in the table below:

Dataset	Terms	Hyponym Relations
Data Mining	278	364
Computer Network	336	399
Data Structure	315	578
Euclidean Geometry	455	690
Microbiology	1,028	3,533

Domain-Specific Hyponym Relations is distributed via web download.

2014 Subscription Members will automatically receive two copies of this data on disc. 2014 Standard Members may request a copy as part of their 16 free membership corpora.  This data is made available at no-cost to LDC members and non-members under the Creative Commons Attribution-Noncommercial Share Alike 3.0 license. 

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(2) GALE Arabic-English Parallel Aligned Treebank -- Web Training was developed by LDC and contains 69,766 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.

LDC previously released Arabic-English Parallel Aligned Treebanks as follows:

• Newswire
• Broadcast News Part 1
• Broadcast News Part 2

This release consists of Arabic source web data (newsgroups, weblogs) collected by LDC in 2004 and 2005. All data is encoded as UTF-8. A count of files, words, tokens and segments is below.

Language	Files	Words	Tokens	Segments
Arabic	162	46,710	69,766	3,178

Note: Word count is based on the untokenized Arabic source, 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 -- Web Training is distributed via web download.

2014 Subscription Members will automatically receive two copies of this data on disc. 2014 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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(3) Multi-Channel WSJ Audio (MCWSJ) was developed by the Centre for Speech Technology Research at the University of Edinburgh and contains approximately 100 hours of recorded speech from 45 British English speakers. Participants read Wall Street Journal texts published in 1987-1989 in three recording scenarios: a single stationary speaker, two stationary overlapping speakers and one single moving speaker.

This corpus was designed to address the challenges of speech recognition in meetings, which often occur in rooms with non-ideal acoustic conditions and significant background noise, and may contain large sections of overlapping speech. Using headset microphones represents one approach, but meeting participants may be reluctant to wear them. Microphone arrays are another option. MCWSJ supports research in large vocabulary tasks using microphone arrays. The news sentences read by speakers are taken from WSJCAM0 Cambridge Read News, a corpus originally developed for large vocabulary continuous speech recognition experiments, which in turn was based on CSR-I (WSJ0) Complete, made available by LDC to support large vocabulary continuous speech recognition initiatives.

Speakers reading news text from prompts were recorded using a headset microphone, a lapel microphone and an eight-channel microphone array. In the single speaker scenario, participants read from six fixed positions. Fixed positions were assigned for the entire recording in the overlapping scenario. For the moving scenario, participants moved from one position to the next while reading.

Fifteen speakers were recorded for the single scenario, nine pairs for the overlapping scenario and nine individuals for the moving scenario. Each read approximately 90 sentences.

Multi-Channel WSJ Audio is distributed on 2 DVD-ROM.

2014 Subscription Members will receive a copy of this data provided that they have completed the User License Agreement for Multi-Channel WSJ Audio LDC2014S03. 2014 Standard Members may request a copy as part of their 16 free membership corpora.  Non-members may license this data for a fee.