Learning pronunciation and formulation variants in continuous speech applications

Most voice driven applications are based on recognition grammars. In complex applications it is difficult to exactly predict how the users will formulate their requests even if a careful study of the user's behavior has been performed. Moreover, it is possible that a speaker's word pronunciation does not match the phonetic transcription of the system, mainly in the case of foreign words. Loquendo has developed a tool that collects field data, detects the most significant weaknesses of the application due to pronunciation of formulation mismatches, and filters the collected field corpora. This permits the application designers to perform their analysis only on a reasonable amount of preprocessed and automatically labeled data. This paper presents the approaches that have been devised to detect pronunciation variants of vocabulary words and linguistic formulations not covered by the recognition grammar. Results showing the improvements that have been obtained including automatically detected formulations in three grammars for two languages are also detailed.