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It is well known that canonical Spanish, the dialectal variant `central' of Spain, so called Castilian, can be transcribed by rules. This paper deals with the automatic grapheme to phoneme transcription rules in several Spanish dialects from Latin America. Spanish is a language spoken by more than 300 million people, has an important geographical dispersion compared among other languages and has been historically influenced by many native languages. In this paper authors expand the Castilian transcription rules to a set of different dialectal variants of Latin America. Transcriptions are based on SAMPA symbols. The paper includes an identification of sounds that doesn't appear in Castilian, extend accepted SAMPA symbols for Spanish (Castilian) to different dialectal variants, describes the necessary rules to implement an automatic Orthographic to Phonetic transcription in several dialectal Spanish variants and show some quantitative results of dialectal differences., Peer Reviewed, Postprint (published version)

The problem of detecting a given set of words in fluent speech is one of the most interesting topics in speech recognition for practical real time applications. This paper present the TELEMACO system for automatic voice dialling which is based on the use of the keyword spotting technology to detect the dialling commands in fluent speech used by the IBERCOM Spanish telephone system. The user interface is based on a PC computer with a DSP board. The DSP board runs the speech recognition task and the interaction with the telephone line. The keyword vocabulary is composed by commands to dial, answer, hang-up, cancel, recall, store, etc. Each keyword is modeled by means of a discrete Hidden Markov Model. To model the non-keyword speech, syllabic fillers models and background models are used. The keyword spotting algorithm is a null grammar time-synchronous Viterbi search with two search spaces. The first search is over all the models (keywords and fillers) and the second search is only over the filler model. Thus, we can compare the behaviour of the filler model with the candidate keyword for each detection and decide if the keyword has been uttered or not. This process is done frame by frame. When a keyword is detected, the DSP board send the recognition word to the PC to take the corresponding action. The system has been implemented in a Windows environment., Peer Reviewed, Postprint (published version)