Modern language learning courses are no longer exclusively based on books or face-to-face lectures. More and more lessons make use of multimedia and personalized learning methods. Many of these are based on e-learning solutions. Learning via the Internet provides 7/24 services that require sizeable human resources. Therefore we witness a growing economic pressure to employ computer-assisted methods for improving language learning in quality, efficiency and scalability. In this paper, we will address three applications of language technologies for language learning: 1) Methods and strategies for pronunciation training in second language learning, e.g., multimodal feedback via visualization of sound features, speech verification and prosody transplantation; 2) Dialogue-based language learning games; 3) Application of parsing and generation technologies to the automatic generation of paraphrases for the semi-automatic production of learning material.

In the area of Computer Assisted Language Learning(CALL), second language (L2) learners’ spoken data is an important resource for analysing and annotating typical L2 pronunciation errors. The annotation of L2 pronunciation errors in spoken data is not an easy task though, normally it requires manual annotation from trained linguists or phoneticians. In order to facilitate this task, in this paper, we present the MAT tool, a web-based tool intended to facilitate the annotation of L2 learners’ pronunciation errors at various levels. The tool has been designed taking into account recent studies on error detection in pronunciation training. It also aims at providing an easy and fast annotation process via a comprehensive and friendly user interface. The tool is based on the MARY TTS open source platform, from which it uses the components: text analyser (tokeniser, syllabifier, phonemiser), phonetic aligner and speech signal processor. Annotation results at sentence, word, syllable and phoneme levels are stored in XML format. The tool is currently under evaluation with a L2 learners’ spoken corpus recorded in the SPRINTER (Language Technology for Interactive, Multi-Media Online Language Learning) project.

This paper describes an open source voice creation toolkit that supports the creation of unit selection and HMM-based voices, for the MARY (Modular Architecture for Research on speech Synthesis) TTS platform. We aim to provide the tools and generic reusable run-time system modules so that people interested in supporting a new language and creating new voices for MARY TTS can do so. The toolkit has been successfully applied to the creation of British English, Turkish, Telugu and Mandarin Chinese language components and voices. These languages are now supported by MARY TTS as well as German and US English. The toolkit can be easily employed to create voices in the languages already supported by MARY TTS. The voice creation toolkit is mainly intended to be used by research groups on speech technology throughout the world, notably those who do not have their own pre-existing technology yet. We try to provide them with a reusable technology that lowers the entrance barrier for them, making it easier to get started. The toolkit is developed in Java and includes intuitive Graphical User Interface (GUI) for most of the common tasks in the creation of a synthetic voice.