Phonetic knowledge, phonotactics an automatic language id
نویسندگان
چکیده
This study explores a multilingual phonotactic approach to automatic language identification using Broadcast News data. The definition of a multilingual phoneset is discussed and an upper limit on the performance of the phonotactic approach is estimated by eliminating any degradation due to recognition errors. This upper bound is compared to automatic language identification based on a phonotactic approach. The eight languages of interest are: Arabic, Mandarin , English, French, German, Italian, Portuguese and Spanish. A perceptual test has been carried out to compare human and machine performance in similar configurations. Different phoneset classes have been experimented with, ranging from a binary C/V distinction to a shared phone set of 70 phones. Experiments show that phonotactic constraints are in theory able to identify a language (among 8) with close to 100% on very short sequences of 1-2 seconds. Automatic and human performances on very short sequences both remain below the theoretical performances.
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