any educators, these may still seem like distant goals, and yet we believe that they are not beyond reach. In what follows, we identify four of the most persistent issues in building speech-enabled language learning applications and suggest how they might be resolved to enable a more widespread commercial implementation of speech technology in CALL.
1. More research is necessary on modeling and predicting multi-turn dialogs.
An intelligent open response language tutor must not only correctly recognize a given speech input, but in addition understand what has been said and evaluate the meaning of the utterance for pragmatic appropriateness. Automatic speech understanding requires Natural Language Processing (NLP) capabilities, a technology for extracting grammatical, semantic, and pragmatic information from written or spoken discourse. NLP has been successfully deployed in expert systems and information retrieval. One of the first voice-interactive dialog systems using NLP was the DARPA-sponsored Air Travel Information System (Pallett, 1995), which enables the user to obtain flight information and make ticket reservations over the telephone. Similar commercial systems have been implemented for automatic retrieval of weather and restaurant information, virtual environments, and telephone auto-attendants. Many of the lessons learned in developing such systems can be valuable for designing CALL applications for practicing conversational skills.
2. More and better training data are needed to support basic research on modeling non-native conversational speech.
One of the most needed resources for developing open response conversational CALL applications is large corpora of non-native transcribed speech data, of both read and conversational speech. Since accents vary depending on the student's first language, separate databases must either be collected for each L1 subgroup, or a representative sample of speakers of different languages ​​must be included in the database. Creating such databases is extremely labor and cost intensive - a phone level transcription of spontaneous conversational data can cost up to one dollar per phone. A number of multilingual conversational databases of telephone speech are publicly available through the Linguistic Data Consortium (LDC), including Switchboard (US English) and CALLHOME (English, Japanese, Spanish, Chinese, Arabic, German). Our own effort in collaboration with John Hopkins University (Byrne, Knodt, Khudanpur, & Bernstein, 1998; Knodt, Bernstein, & Todic, 1998) has been to collect and model spontaneous English conversations between Hispanic natives. All of these efforts will improve our understanding of the disfluent speech of language learners and help model this speech type for the purpose of human-machine communication.
В
DEFINING AND ACQUIRING LITERACY IN THE AGE OF INFORMATION
Moll defined literacy as "a particular way of using language for a variety of purposes, as a sociocultural practice with intellectual significance "(1994, p. 201). While traditional definitions of literacy have focused on reading and writing, the definition of literacy today is more complex. The process of becoming literate today involves more than learning how to use language effectively; rather, the process amplifies and changes both the cognitive and the linguistic functioning of the individual in society. One who is literate knows how to gather, analyze, and use information resources to solve problems and make decisions, as well as how to learn both independently and cooperatively. Ultimately literate individuals possess a range of skills that enable them to participate fully in all aspects of modern society, from the workforce to the family to the academic community. Indeed, the development of literacy is "a dynamic and ongoing process of perpetual transformation "(Neilsen, 1989, p. 5), whose evolution is influenced by a person's interests, cultures, and experiences. Researchers have viewed literacy as a multifaceted concept for a number of years (Johns, 1997). However, succeeding in a digital, information-oriented society demands multiliteracies, that is, competence in an even more diverse set of functional, academic, critical, and electronic skills.
To be considered multiliterate, students today must acquire a battery of skills that will enable them to take advantage of the diverse modes of communication made possible by new technologies and to participate in global learning communities. Although becoming multiliterate is not an easy task for any student, it is especially difficult for ESL students operating in a second language. In their attempts to become multiliterate, ESL students must acquire linguistic competence in a new language and at the same time develop the cognitive and sociocultural skills necessary to ...
