Abstract :
In the past decade, the performance of spoken language understanding systems has improved dramatically, including speech recognition, dialog systems, speech summarization, and text and speech translation. This has resulted in an increasingly widespread use of speech and language technologies in a wide variety of applications. With more than 6,900 languages in the world and the current trend of globalization, one of the most important challenges in spoken language technologies today is the need to support multiple input and output languages, especially if applications are intended for international markets, linguistically diverse user communities, and nonnative speakers. In many cases these applications have to support even multiple languages simultaneously to meet the needs of a multicultural society. Consequently, new algorithms and tools are required that support the simultaneous recognition of mixed-language input, the summarization of multilingual text and spoken documents, the generation of output in the appropriate language, or the accurate translation from one language to another. This article surveys significant ongoing research programs as well as trends, prognoses, and open research issues with a special emphasis on multilingual speech processing as described in detail in the work of Schultz and Hirschberg (2006) and multilingual language processing as presented in the work of Fung (2006).
Keywords :
language translation; linguistics; natural language processing; speech processing; text analysis; language translation; mixed-language; multicultural society; multilingual speech processing; multilingual spoken language processing; multilingual text summarization; spoken document; spoken language understanding system; Data mining; Databases; Globalization; Hidden Markov models; Natural languages; Signal processing algorithms; Speech analysis; Speech processing; Speech recognition; Speech synthesis;