postposing is a feature of spoken language. it is a process that postposes a preverbal constituent to a position after the verb, without changing the overall meaning of the sentence. in this study we focus on this linguistic phenomenon and its relation to factors such as grammatical weight, definiteness, animacy and information structure. to investigate the occurrence of this process and its in...

signing is an important informative – affective aspect of language which is overshadowed by the traditional speaking – writing distinction and the priority of written form over spoken form in both linguistics and literary criticism. this paper attempts to introduce a new form of language which can be referred to as signing language, which can shed light on understanding and analysis of the obli...

Recent advances in ASR and spoken language processing have led to improved systems for automated assessment for spoken language. However, it is still challenging for automated scoring systems to achieve high performance in terms of the agreement with human experts when applied to non-native children’s spontaneous speech. The subpar performance is mainly caused by the relatively low recognition ...

In recent years, there has been dramatic progress in both speech and language processing, which spurs efforts to combine speech and language technologies in spoken document processing applications. However, speech is different from text in many respects, most notably in the lack of explicit punctuation and formatting. Thus, spoken document processing requires automatic segmentation to achieve g...

This paper describes a language modeling method using largescale spoken language data retrieved from the Web for spontaneous speech recognition. We downloaded 15 million Web pages on a comprehensive range topics. Next, spoken languagelike texts were selected from the downloaded Web data using the naı̈ve Bayes classifier, and typical linguistic phenomena such as fillers and pauses were added usin...

Spoken language systems (SLS) communicate with users in natural language through speech. There are two main problems related to processing the spoken input in SLS. The first one is automatic speech recognition (ASR) which recognizes what the user says. The second one is spoken language understanding (SLU) which understands what the user means. We focus on the language model (LM) component of SL...

The demands on a natural language understanding system used for spoken language differ somewhat from the demands of text processing. For processing spoken language, there is a tension between the system being as robust as necessary, and as constrained as possible. The robust system will a t tempt to find as sensible an interpretation as possible, even in the presence of performance errors by th...

Since the quality of the language model directly affects the performance of the spoken dialog system (SDS), we should use a statistical language model (LM) trained with a large amount of data that is matched to the task domain. When porting an SDS to another language, however, it is costly to re-collect a large amount of user utterances in the target language. We thus use the language resources...

We propose a novel universal acoustic characterization approach to spoken language identification (LID), in which any spoken language is described with a common set of fundamental units defined “universally.” Specifically, manner and place of articulation form this unit inventory and are used to build a set of universal attribute models with data-driven techniques. Using the vector space modeli...