2007 NIST Language Recognition Evaluation Supplemental Training Set
| Item Name: | 2007 NIST Language Recognition Evaluation Supplemental Training Set |
| Author(s): | Alvin Martin, Audrey Le, David Graff, Jan van Santen |
| LDC Catalog No.: | LDC2009S05 |
| ISBN: | 1-58563-530-8 |
| ISLRN: | 498-359-265-464-3 |
| DOI: | https://doi.org/10.35111/gqmf-6p19 |
| Release Date: | November 20, 2009 |
| Member Year(s): | 2009 |
| DCMI Type(s): | Sound |
| Sample Type: | 8 bit u-law |
| Sample Rate: | 8000 |
| Data Source(s): | telephone conversations |
| Project(s): | NIST LRE |
| Application(s): | language identification |
| Language(s): | Yue Chinese, Wu Chinese, Urdu, Thai, Tamil, Spanish, Russian, Min Nan Chinese, Mandarin Chinese, Bengali, Egyptian Arabic |
| Language ID(s): | yue, wuu, urd, tha, tam, spa, rus, nan, cmn, ben, arz |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2009S05 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Martin, Alvin, et al. 2007 NIST Language Recognition Evaluation Supplemental Training Set LDC2009S05. Web Download. Philadelphia: Linguistic Data Consortium, 2009. |
| Related Works: | View |
Introduction
2007 NIST Language Recognition Evaluation Supplemental Training Set was developed by the Linguistic Data Consortium (LDC) and the National Institute of Standards and Technology (NIST). It consists of 118 hours of conversational telephone speech segments in the following languages and dialects: Arabic (Egyptian colloquial), Bengali, Min Nan Chinese, Wu Chinese, Taiwan Mandarin, Cantonese, Russian, Mexican Spanish, Thai, Urdu, and Tamil.
The goal of NIST's Language Recognition Evaluation (LRE) is to establish the baseline of current performance capability for language recognition of conversational telephone speech and to lay the groundwork for further research efforts in the field. NIST conducted three previous language recognition evaluations, in 1996, 2003 and 2005. The most significant differences between those evaluations and the 2007 task were the increased number of languages and dialects, the greater emphasis on a basic detection task for evaluation and the variety of evaluation conditions. Thus, in 2007, given a segment of speech and a language of interest to be detected (i.e., a target language), the task was to decide whether that target language was in fact spoken in the given telephone speech segment (yes or no), based on an automated analysis of the data contained in the segment.
Data
The supplemental training material in this release consists of the following:
- Approximately 53 hours of conversational telephone speech segments in Arabic (Egyptian colloquial), Bengali, Cantonese, Min Nan Chinese, Wu Chinese, Russian, Thai, and Urdu. This material is taken from LDC's CALLHOME, CALLFRIEND, and Mixer collections.
- Approximately 65 hours of full telephone conversations in Mandarin Chinese (Taiwan), Spanish (Mexican), and Tamil. This material was collected by Oregon Health and Science University (OHSU), Beaverton, Oregon. The test segments used in the 2005 NIST Language Recognition Evaluation (LDC2008S05) were derived from these full conversations.
In addition to the supplemental material contained in this release, the training data for the 2007 NIST Language Recognition Evaluation (LDC2009S04) consisted of data from previous LRE evaluation test sets, namely, 2003 NIST Language Recognition Evaluation (LDC2006S31) and 2005 NIST Language Recognition Evaluation (LDC2008S05).
LDC released other LREs as:
- 2003 NIST Language Recognition Evaluation (LDC2006S31)
- 2005 NIST Language Recognition Evaluation (LDC2008S05)
- 2007 NIST Language Recognition Evaluation (LDC2009S04)
- 2009 NIST Language Recognition Evaluation Test Set (LDC2014S06)
- 2011 NIST Language Recognition Evaluation Test Set (LDC2018S06)
Samples
For an example of the data in this corpus, please listen to this Egyptian Arabic sample (WAV) from the data set.
Updates
None at this time.