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New publications:
Avocado Research Email Collection
GALE Chinese-English Word Alignment and Tagging -- Broadcast Training Part 3
RATS Speech Activity Detection
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Only two weeks left to enjoy 2015 membership savings
Don’t miss this savings opportunity. Secure your membership today for access to new corpora as well as discounts on our existing catalog of over 600 holdings. 2015 publications include the following:
- CIEMPIESS - Mexican Spanish radio broadcast audio and transcripts
- GALE Phase 3 and 4 data – all tasks and languages
- Mandarin Chinese Phonetic Segmentation and Tone Corpus - phonetic segmentation and tone labels
- RATS Speech Activity Detection – multilanguage audio for robust speech detection and language identification
- SEAME - Mandarin-English code-switching speech
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(1) Avocado Research Email Collection consists of emails and attachments taken from 279 accounts of a defunct information technology company referred to as "Avocado". Most of the accounts are those of Avocado employees; the remainder represent shared accounts such as "Leads", or system accounts such as "Conference Room Upper Canada".
The collection consists of the processed personal folders of these accounts with metadata describing folder structure, email characteristics and contacts, among others. It is expected to be useful for social network analysis, e-discovery and related fields.
The source data for the collection consisted of Personal Storage Table (PST) files for 282 accounts. A PST file is used by MS Outlook to store emails, calendar entries, contact details, and related information. Data was extracted from the PST files using libpst version 0.6.54. Three files produced no output and and are not included in the collection. Each account is referred to as a "custodian" although some of the accounts do not correspond to humans.
The collection is divided into metadata and text. The metadata is represented in XML, with a single top-level XML file listing the custodians, and then one XML file per custodian listing all items extracted from that custodian's PST files. The full XML tree can be read by loading the top-level file with an XML parser that handles directives. All XML metadata files are encoded in UTF-8. The text contains the extracted text of the items in the custodians' folders, with the extracted text for each item being held in a separate file. The text files are then zipped into a zip file per custodian.
Avocado Research Email Collection is distributed on 1 DVD-ROM. 2015 Subscription Members will automatically receive two copies of this corpus provided that they have completed the license agreement. 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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Alignment identifies minimum translation units and translation relations by using minimum-match and attachment annotation approaches. A set of word tags and alignment link tags are designed in the tagging scheme to describe these translation units and relations. Tagging adds contextual, syntactic and language-specific features to the alignment annotation.
This release consists of Chinese source broadcast conversation (BC) and broadcast news (BN) programming collected by LDC in 2008 and 2009. The distribution by genre, words, character tokens and segments appears below:
Language |
Genre |
Files |
Words |
CharTokens |
Segments |
Chinese |
BC |
92 |
67,354 |
101,032 |
2,714 |
Chinese |
BN |
34 |
93,992 |
140,988 |
3,314 |
Total |
|
126 |
161,346 |
242,020 |
6,028 |
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 tasks 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
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(3) RATS Speech Activity Detection was developed by LDC and is comprised
of approximately 3,000 hours of Levantine Arabic, English,
Farsi, Pashto, and Urdu conversational telephone speech with
automatic and manual annotation of speech segments. The corpus
was created to provide training, development and initial test
sets for the Speech Activity Detection (SAD) task in the DARPA
RATS (Robust Automatic Transcription of Speech) program.The goal of the RATS program was to develop human language technology systems capable of performing speech detection, language identification, speaker identification and keyword spotting on the severely degraded audio signals that are typical of various radio communication channels, especially those employing various types of handheld portable transceiver systems. To support that goal, LDC assembled a system for the transmission, reception and digital capture of audio data that allowed a single source audio signal to be distributed and recorded over eight distinct transceiver configurations simultaneously.
Those configurations included three frequencies -- high, very high and ultra high -- variously combined with amplitude modulation, frequency hopping spread spectrum, narrow-band frequency modulation, single-side-band or wide-band frequency modulation. Annotations on the clear source audio signal, e.g., time boundaries for the duration of speech activity, were projected onto the corresponding eight channels recorded from the radio receivers.
The source audio consists of conversational telephone speech recordings collected by LDC: (1) data collected for the RATS program from Levantine Arabic, Farsi, Pashto and Urdu speakers; and (2) material from the Fisher English (LDC2004S13, LDC2005S13), and Fisher Levantine Arabic telephone studies (LDC2007S02), as well as from CALLFRIEND Farsi (LDC2014S01).
Annotation was performed in three steps. LDC's automatic speech activity detector was run against the audio data to produce a speech segmentation for each file. Manual first pass annotation was then performed as a quick correction of the automatic speech activity detection output. Finally, in a manual second pass annotation step, annotators reviewed first pass output and made adjustments to segments as needed.
All audio files are presented as single-channel, 16-bit PCM, 16000 samples per second; lossless FLAC compression is used on all files; when uncompressed, the files have typical "MS-WAV" (RIFF) file headers.
RATS Speech Activity Detection is distributed on 1 hard drive. 2015 Subscription Members will automatically receive one copy 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.