Leandro Rodríguez Liñares

Specific features of the Galician language and implications for speech technology development

In this article, we present the main linguistic and phonetic features of Galician which need to be considered in the development of speech technology applications for this language. We also describe the solutions adopted in our text-to-speech system, also useful for speech recognition and speech-to-speech translation. On the phonetic plane in particular, the handling of vocal contact and the determination of mid-vowel openness are discussed. On the linguistic plane we place special emphasis on the handling of clitics and verbs. It should be noted that in Galician there is high interrelation between phonetics and grammatical information. Therefore, the task of morphosyntactic disambiguation is also addressed. Moreover, this task is fundamental for a higher level linguistic analysis.

TelCorreo: A Bilingual E-mail Client over the Telephone

In this paper we present TelCorreo [1]: an e-mail client that allows the Galician Internet users to read their e-mail messages from locations where there is no web-connected computer available. This task is performed using speech through the telephone, and the system uses speech technology developed in Galician, including a speech recognition system and a text-to-speech converter.

A Speaker Authentication Module in TelCorreo

Our experiments in Speaker Recognition showed that the combination of Speaker Verification and Utterance Verification techniques is an efficient way of improving the performance of a Speaker Authentication System. This technique is now implemented in the speaker authentication module of TelCorreo, an e-mail client that allows Internet users to read their e-mail using speech through the telephone.

Application of Acoustic Discriminative Training in an Ergodic HMM for Speaker Identification

We present a novel architecture for a Speaker Recognition system over the telephone. The proposed system introduces acoustic information into a HMM-based recognizer. This is achieved by using a phonetic classifier during the training phase. Three broad phonetic classes: voiced frames, unvoiced frames and transitions, are defined. We design speaker templates by the combination of four single state HMMs into a four state HMM after re-estimation of the transition probabilities. Experiments conducted with two databases are reported, and the results show that this architecture performs better than others without phonetic classification.