In:
ACM Transactions on Speech and Language Processing, Association for Computing Machinery (ACM), Vol. 9, No. 2 ( 2012-07), p. 1-27
Abstract:
Developing a multilingual speech translation system requires efforts in constructing automatic speech recognition (ASR), machine translation (MT), and text-to-speech synthesis (TTS) components for all possible source and target languages. If the numerous ASR, MT, and TTS systems for different language pairs developed independently in different parts of the world could be connected, multilingual speech translation systems for a multitude of language pairs could be achieved. Yet, there is currently no common, flexible framework that can provide an entire speech translation process by bringing together heterogeneous speech translation components. In this article we therefore propose a distributed architecture framework for multilingual speech translation in which all speech translation components are provided on distributed servers and cooperate over a network. This framework can facilitate the connection of different components and functions. To show the overall mechanism, we first present our state-of-the-art technologies for multilingual ASR, MT, and TTS components, and then describe how to combine those systems into the proposed network-based framework. The client applications are implemented on a handheld mobile terminal device, and all data exchanges among client users and spoken language technology servers are managed through a Web protocol. To support multiparty communication, an additional communication server is provided for simultaneously distributing the speech translation results from one user to multiple users. Field testing shows that the system is capable of realizing multiparty multilingual speech translation for real-time and location-independent communication.
Type of Medium:
Online Resource
ISSN:
1550-4875
,
1550-4883
DOI:
10.1145/2287710.2287712
Language:
English
Publisher:
Association for Computing Machinery (ACM)
Publication Date:
2012
detail.hit.zdb_id:
2178011-0
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