We present an attention-based sequence-to-sequence neural network which can directly
translate speech from one language into speech in another language, without relying on an …

Recently, we have seen an increasing interest in the area of speech-to-text translation. This
has led to astonishing improvements in this area. In contrast, the activities in the area of …

This paper presents an approach for transfer of speaker intent in speech-to-speech machine
translation (S2SMT). Specifically, we describe techniques to retain the prominence patterns …

In this paper, we study the importance of context in predicting the citation worthiness of
sentences in scholarly articles. We formulate this problem as a sequence labeling task …

We describe here a collection of speech data of bilingual and trilingual speakers of English,
French, German and Italian. In the context of speech to speech translation (S2ST), this …

Code Mixing-phenomenon where lexical items from one language are embedded in the
utterance of another-is relatively frequent in multilingual communities and therefore speech …

We investigate speaker adaptation in the context of deep neural network (DNN) based
speech synthesis. More specifically, our current work focuses on the exploitation of auxiliary …

Verifying that a live human is interacting with an automated speech based system is needed
in some applications such as biometric authentication. In this paper, we present a method to …

In this article, we propose a speaker-dependent model interpolation method for statistical
emotional speech synthesis. The basic idea is to combine the neutral model set of the target …

In this paper we provide the state-of-the-art of existing proprietary and free and open source
software (FOSS) automatic speech recognition (ASR), speech synthesizers, and Machine …