Fisher Levantine Arabic Conversational Telephone Speech
| Item Name: | Fisher Levantine Arabic Conversational Telephone Speech |
| Author(s): | Mohamed Maamouri, Tim Buckwalter, David Graff, Hubert Jin |
| LDC Catalog No.: | LDC2007S02 |
| ISBN: | 1-58563-438-7 |
| ISLRN: | 483-111-978-894-6 |
| DOI: | https://doi.org/10.35111/kq00-ts40 |
| Release Date: | March 16, 2007 |
| Member Year(s): | 2007 |
| DCMI Type(s): | Sound |
| Sample Type: | 2-channel ulaw |
| Sample Rate: | 8000 |
| Data Source(s): | telephone conversations |
| Project(s): | GALE |
| Language(s): | North Levantine Arabic, South Levantine Arabic |
| Language ID(s): | apc, ajp |
| License(s): |
LDC User Agreement for Non-Members |
| Online Documentation: | LDC2007S02 Documents |
| Licensing Instructions: | Subscription & Standard Members, and Non-Members |
| Citation: | Maamouri, Mohamed, et al. Fisher Levantine Arabic Conversational Telephone Speech LDC2007S02. Web Download. Philadelphia: Linguistic Data Consortium, 2007. |
| Related Works: | View |
Introduction
Levantine Arabic is spoken along the western Mediterranean coast from Anatolia to the Sinai Peninsula and encompasses the local dialects of Lebanon, Syria and Palestine. There are two distinct varieties: Northern, centered around Syria and Lebanon; and Southern, spoken in Jordan and Palestine. Northern Levantine Arabic speakers include approximately 8.8 million speakers in Syria and 6 million speakers in Lebanon. Southern Levantine Arabic speakers include approximately 3.5 million speakers in Jordan, 1.6 million speakers in Palestine and nearly one million speakers in Israel.
Fisher Levantine Arabic Conversational Telephone Speech contains 279 telephone conversations totaling 45 hours of speech. The majority of the speakers are from Jordan, Lebanon and Palestine.
| Speaker Distribution by Region | |
| Jordan | 60% |
| Palestine | 15% |
| Lebanon | 15% |
| Syria | 8% |
| other | 2% |
The Fisher telephone conversation collection protocol was created at LDC to address a critical need of developers trying to build robust automatic speech recognition (ASR) systems. Previous collection protocols, such as CALLFRIEND and Switchboard-II and the resulting corpora, have been adapted for ASR research but were in fact developed for language and speaker identification respectively. Although the CALLHOME protocol and corpora were developed to support ASR technology, they feature small numbers of speakers making telephone calls of relatively long duration with narrow vocabulary across the collection. CALLHOME conversations are challengingly natural and intimate. Under the Fisher protocol, a very large number of participants each make a few calls of short duration speaking to other participants, whom they typically do not know, about assigned topics. This maximizes inter-speaker variation and vocabulary breadth although it also increases formality.
Previous protocols such as CALLHOME, CALLFRIEND and Switchboard relied upon participant activity to drive the collection. Fisher is unique in being platform driven rather than participant driven. Participants who wish to initiate a call may do so; however the collection platform initiates the majority of calls. Participants need only answer their phones at the times they specified when registering for the study.
To encourage a broad range of vocabulary, Fisher participants are asked to speak on an assigned topic which is selected at random from a list, which changes every 24 hours and which is assigned to all subjects paired on that day. Some topics are inherited or refined from previous Switchboard studies while others were developed specifically for the Fisher protocol.
Data
The conversations in this corpus are a subset of the conversations in Levantine Arabic QT Training Data Set 5, Speech, LDC2006S29. The individual audio files are in NIST Sphere format. The corresponding transcripts may be found in Fisher Levantine Arabic Conversational Telephone Speech, Transcripts, LDC2007T04.
Samples
For an example of the speech data in this corpus, please listen to this audio sample in wav format.