Speech & natural language publications

This paper describes a two-step approach for keyword spotting task in which a query-by-example search is followed by noise robust exemplar matching rescoring. 

In this paper, we investigate several automatic transcription schemes for using raw bilingual broadcast news data in semi-supervised bilingual acoustic model training.

This paper revisits two neural network architectures developed for noise and channel robust ASR, and applies them to building a state-of-art multilingual QbE system.

In this paper we analyze articulatory measures to gain further insight into how articulation is affected by depression.

This work aims to estimate the propagation of such distortion in the form of network activation entropy, which is measured over a short-time running window on the activation from each…

We benchmark these approaches on several distinctly different databases, after we describe our SRICON-UAM team system submission for the NIST 2016 SRE. 

Speech conveys many things beyond content, including aspects of stance and attitude that have not been much studied.

In this paper, we focus on situations in which either (1) the system-modeled languages are not observed during use or (2) the test data contains OOS languages that are unseen…

This work explores using deep neural networks (DNNs) and convolutional neural networks (CNNs) for mapping speech data into its corresponding articulatory space. Our speech-inversion results indicate that the CNN models…

This work addresses lexical unit discovery for languages without (usable) written resources.