Upcoming Policy Change to LDC’s Open Memberships
LDC at Interspeech 2022
LanguageARC: Citizen Science for Language
30th Anniversary Highlight: Switchboard
New publications:
Xi’an Guanzhong Object Naming
MASRI Synthetic
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Upcoming Policy Change to LDC’s Open Memberships
LDC is changing its open membership year policy beginning January 1, 2023. Only one membership year will be open for joining – the current membership year. The 2022 membership year will close for joining on December 31, 2022. We expect this change to have a minimal impact on members, while allowing us to streamline our processes to serve members better. LDC’s many membership benefits will remain the same and organizations choosing to join membership years in advance will still be able to do so. If you have any questions about this change, please don’t hesitate to contact our membership office.
LDC at Interspeech 2022
LanguageArc: Citizen Science for Language
LanguageARC is a citizen science web portal for language research developed by LDC with the support of the National Science Foundation (grant #1730377).
LanguageARC brings together researchers and participants from the general public interested in language to form a community dedicated to support and advance language-related research and development. Contributors to this online community can participate in a variety of language-related tasks and activities such as reading text, answering questions, describing images or video, creating or evaluating transcriptions for audio clips or developing translations into their native languages. LanguageARC includes projects in languages other than English, such as French, Sesotho and Swedish. Xi’an Guanzhong Object Naming LDC2022S09, released this month in LDC’s Catalog and described below, is an example of a data set developed using LanguageArc. New projects will be added on an ongoing basis.
Find LanguageArc on Facebook at: https://www.facebook.com/languagearc
30th Anniversary Highlight: Switchboard
Switchboard-1 Release 2 (LDC97S62) is considered the first large collection of spontaneous conversational telephone speech (Graff & Bird, 2000). It consists of approximately 260 hours of recordings collected by Texas Instruments in 1990-1991 (Godfrey et al., 1992). The first release of the corpus (later superseded) was published by NIST and distributed by LDC in 1993.
Participants were 543 speakers (302 male, 241 female) from across the United States who accounted for around 2,400 two-sided telephone conversations. A robot operator handled the calls, giving the caller appropriate recorded prompts, selecting and dialing another person (the callee) to take part in a conversation, introducing a topic for discussion and recording the speech from the two subjects into separate channels until the conversation was finished. Roughly 70 topics were provided, of which about 50 were used frequently. Selection of topics and callees was constrained so that: (1) no two speakers would converse together more than once and (2) no one spoke more than once on a given topic.
This gold standard data set has been used for many HLT applications, including speaker identification, speaker authentication, and speech recognition. It is considered one of the most important benchmarks for recognition tasks involving large vocabulary conversational speech (Deshmukh et al., 1998) as well as a key resource for studying the phonetic properties of spontaneous speech (Greenberg et al., 1996). Annotation tasks based on Switchboard include discourse tags/speech acts, part-of-speech tagging and parsing, and sentiment analysis.
The Switchboard series includes Switchboard Credit Card, Phase II, Phase III, the Switchboard Cellular collection, and new recordings from 18 Switchboard participants in the 2013 Greybeard corpus.
All Switchboard corpora are available in the Catalog for licensing by Consortium members and non-members. Visit Obtaining Data for more information.
New publications:
Xi’an Guanzhong Object Naming is comprised of 15 hours of audio recordings from speakers of the Guanzhong dialect of Mandarin Chinese living in or near Xi'an in Shaangxi Province (China) naming objects that appeared in colored line drawings. The corpus was developed to support traditional and computer aided language documentation.
2022 Subscription Members will automatically receive copies of this corpus. 2022 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.
MASRI Synthetic MASRI (Maltese Automatic Speech Recognition I) Synthetic was developed by the MASRI team at the University of Malta and contains 99 hours of synthesized Maltese speech.
Source sentences were extracted from the Maltese Language Resource Server (MLRS) corpus, comprised of written or transcribed Maltese covering various genres, including parliamentary debates, news, law, opinion, sports, culture, academic, literature and religious texts. Text was processed through the CrimsonWing text-to-speech system to generate speech files. Synthesized speech was created with 210 voices (105 female, 105 male).
MASRI Synthetic is distributed via web download.
2022 Subscription Members will automatically receive copies of this corpus provided they have submitted a completed copy of the special license agreement. 2022 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for a fee.
