Application of Out-Of-Language Detection To Spoken-Term Detection

This paper investigates the detection of English spoken terms in a conversational multi-language scenario. The speech is processed using a large vocabulary continuous speech recognition system. The recognition output is represented in the form of word recognition lattices which are then used to search required terms. Due to the potential multi-lingual speech segments at the input, the spoken term detection system is combined with a module performing out-of-language detection to adjust its confidence scores. First, experimental results of spoken term detection are provided on the conversational telephone speech database distributed by NIST in 2006. Then, the system is evaluated on a multi-lingual database with and without employment of the out-of-language detection module, where we are only interested in detecting English terms (stored in the index database). Several strategies to combine these two systems in an efficient way are proposed and evaluated. Around 7% relative improvement over a stand-alone STD is achieved

Automatic Speech Indexing System of Bilingual Video Parliament Interventions

This paper presents the development and evaluation of an automatic audio indexing system designed for a special task: work in a bilingual environment in the Parliament of the Canton of Valais in Switzerland, with two official languages, German and French. As several speakers are bilingual, language changes may occur within speaker or even within utterance. Two audio indexing approaches are presented and compared: in the first, speech indexing is based on bilingual automatic speech recognition; in the second, language identification is used after speaker diarization in order to select the corresponding monolingual speech recognizer for decoding. The approaches are later combined. Speaker adaptive training is also addressed and evaluated. Accuracy of language identification and speech recognition for the monolingual and bilingual cases are presented and compared, in parallel with a brief description of the system and the user interface. Finally, the audio indexing system is also evaluated from an information retrieval point of view

Current trends in multilingual speech processing

In this paper, we describe recent work at Idiap Research Institute in the domain of multilingual speech processing and provide some insights into emerging challenges for the research community. Multilingual speech processing has been a topic of ongoing interest to the research community for many years and the field is now receiving renewed interest owing to two strong driving forces. Firstly, technical advances in speech recognition and synthesis are posing new challenges and opportunities to researchers. For example, discriminative features are seeing wide application by the speech recognition community, but additional issues arise when using such features in a multilingual setting. Another example is the apparent convergence of speech recognition and speech synthesis technologies in the form of statistical parametric methodologies. This convergence enables the investigation of new approaches to unified modelling for automatic speech recognition and text-to-speech synthesis (TTS) as well as cross-lingual speaker adaptation for TTS. The second driving force is the impetus being provided by both government and industry for technologies to help break down domestic and international language barriers, these also being barriers to the expansion of policy and commerce. Speech-to-speech and speech-to-text translation are thus emerging as key technologies at the heart of which lies multilingual speech processin