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Country Report - Singapore. Haizhou Li Institute for Infocomm Research, Singapore Eng Siong Chng Nanyang Technological University, Singapore. November 2010, Oriental COCOSDA , Nepal. 1. Smart Meeting Room (I 2 R).
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Country Report - Singapore Haizhou Li Institute for Infocomm Research, Singapore Eng Siong Chng Nanyang Technological University, Singapore November 2010, Oriental COCOSDA , Nepal
1. Smart Meeting Room (I2R) • Collecting meeting speech data in participation of NIST Speaker Diarization and Rich Transcription evaluation campaign • Users are able to select the audio/video channels for recording • Audio/video signals from multi-channels are captured synchronously • Each meeting session is stored with metadata including: time and date, duration, number of participants, audio channels, video channels, meeting types (presentation, discussion, spontaneous, scenarios, etc. ) • Dedicated storage to facilitate data transferring and handling.
2. SEAME (NTU)- a Mandarin-English Code-switch Speech Corpus in South-East Asia • Motivation: For code-switching speech recognition research (LVCSR, LID etc) in South East Asia (SEA) • Goal: To develop 50 hours of intra-sentential Mandarin/English spontaneous code-switching speech in two locations: • Singapore: Nanyang Technological University (NTU) • Malaysia: Universiti Sains Malaysia (USM) • Process: • Recording (interview and conversations) • Transcription (languages, discourse particle and non-speech signal, other languages, proper noun and short pause) • Language ID boundary labeling • Status: 25 hours of code-switching speech by Oct 2010 • Reference: Dau-Cheng Lyu, Tien-Ping Tan, Eng-Siong Chng, Haizhou Li, "SEAME: a Mandarin-English Code-switching Speech Corpus in South-East Asia", in Interspeech, Japan, September 2010
2. SEAME (summary) ~25 hours (intra-sentential code-switching speech) ~20K utterances, 89 speakers 2.5 language turns of each intra-sentential code-switching speech M AN ENGMAN ENGMANENG Ex. (5 times of language turns) • Speaking rate is measured by number of words per minute on avg.. • Number of turns is measured the counts of each utterance occurring • ENG-MAN and MAN-ENG on avg.