Amit Srivastava

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In recent years, Twitter has become one of the most important modes for social networking and disseminating content on a variety of topics. It has developed into a popular medium for political discourse and social organization during elections. There has been growing body of literature demonstrating the ability to predict the outcome of elections from(More)
Audio transcriptions from Automatic Speech Recognition systems are a continuous stream of words that are difficult to read. Segmenting these transcriptions into thematically distinct stories and categorizing the stories by topics increases readability and comprehensibility. However, manually defined topic categories are rarely available, and the cost of(More)
because it is impossible to efficiently locate information in large audio archives. By itself, speech does not permit content-based searches for information like those commonly employed for text documents over the Internet. But now, after more than a decade of steady advances in speech recognition, speaker identification, and language understanding , it is(More)
This paper describes a low-latency online speaker adaptation framework. The main objective is to apply fast speaker adaptation to a real-time (RT) large vocabulary continuous speech recognition (LVCSR) engine. In this framework, speaker adaptation is performed on speaker turns generated by online speaker change detection and speaker clustering. To maximize(More)
This paper describes the recent development of an Audio Indexing System for Chinese (Mandarin) broadcast news. Key issues of the three major components: automatic speech recognition, speaker identification and named entity extraction are addressed. The Chinese-language-specific challenges are discussed and our solutions are described. The recognition(More)