10 accepted papers
Real-time voice conversion and speaker anonymization require causal, low-latency synthesis without sacrificing intelligibility or naturalness. Current systems have a core representational mismatch: content is time-varying, while speaker identity is injected as a static global embedding. We introduce…
We present a multitask learning approach to the problem of hypoglycemia (HG) prediction in diabetes. The approach is based on a state-of-the-art time series forecasting model, N-BEATS, and extends it by adding a classification task so that the model performs both glucose forecasting (i.e., predictin…
We present a dictionary-learning algorithm for reducing the sparse coding residual of an exemplar-based method for native-to-nonnative voice conversion (VC). The proposed algorithm iteratively updates the source and target speaker dictionaries to reduce both the residual and voice conversion error,…
Measuring dietary intake is a major challenge in the management of chronic diseases. Current methods rely on self-report measures, which are cumbersome to obtain and often unreliable. This article presents an approach to estimate dietary intake automatically by analyzing the post-prandial glucose re…
Diet monitoring is an important component of interventions in type 2 diabetes, but is time intensive and often inaccurate. To address this issue, we describe an approach to monitor diet automatically, by analyzing fluctuations in glucose after a meal is consumed. In particular, we evaluate three sta…
Accent conversion (AC) aims to transform non-native speech to sound as if the speaker had a native accent. This can be achieved by mapping source spectra from a native speaker into the acoustic space of the non-native speaker. In prior work, we proposed an AC approach that matches frames between the…
In previous work we presented a Sparse, Anchor-Based Representation of speech (SABR) that uses phonemic “anchors” to represent an utterance with a set of sparse non-negative weights. SABR is speaker-independent: combining weights from a source speaker with anchors from a target speaker can be used f…
Exemplar-based methods for voice conversion often use a large number of randomly-selected exemplars to ensure good coverage. As a result, the factorization step can be costly. This paper presents two algorithms that can be used to construct compact sets of exemplars. The first algorithm uses a forwa…
Technology-based therapy tools can be of great benefit to children with developmental speech disabilities as they typically require sustained practice with a speech therapist for several years. Towards this aim, over the past 4 years we have developed speech processing tools to automatically detect…
We describe a method for adapting a physical vocal tract model's anatomical and gestural parameters using acoustic information to match a target speaker. Physical vocal tract models are hard to adjust to match a speaker, as doing so requires information which is difficult to capture, such as X-Ray o…